第 190 期·中文精讀

喬丹·埃倫伯格:高維形狀與幾何的數學

Jordan Ellenberg: Mathematics of High-Dimensional Shapes and Geometries

數學家從高維幾何的直覺出發,聊數學思維、證明之美與教育中的解題訓練。

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Jordan Ellenberg 在新書《Shape》裡寫:幾何是數學裡的香菜。

有人因為它徹底開竅,有人因為它整年迷失。喜歡的人說,其他章節我都能湊合,只有幾何那一刻,數學突然講得通了,為什麼不是所有課都這樣?討厭的人跑來跟 Ellenberg 抱怨,代數我能算,X 是個數,我把它揪出來就行,可幾何那一整年到底在幹什麼?

兩撥人唯一達成共識的是:幾何跟別的數學不一樣。

這個"不一樣"到底是什麼,是這期三個多小時對話裡反覆繞回來的問題。Ellenberg 是威斯康星大學的數學家,也是《How Not To Be Wrong》和《Shape》的作者。他擅長把數學從公式堆裡拽出來,放回人做事的現場。

六歲那年,一個音響木箱讓他看見了乘法交換律

Ellenberg 講自己怎麼愛上數學,場景特別具體。七十年代,家裡的音響外面套著一個深色木箱,箱子上打了孔讓聲音透出來,孔排成六行八列的矩形陣列。

一個六七歲的小孩在客廳裡發呆,盯著這堆孔看。看著看著,焦點一進一出,他突然意識到一件事:這裡有六行、每行八個孔,同時也有八列、每列六個孔。八個六,六個八,是同一批四十八個孔。

他早就背過乘法表,知道六乘八等於八乘六。但知道一個事實,和親眼看見這個事實為什麼成立,是兩回事。那一刻沒有人告訴他,資訊是自己的眼睛直接讀出來的。

他說這跟婆什迦羅(Bhashkara)證明勾股定理的方式是同一件事。婆什迦羅的手稿裡只有一個圖,文字部分據說就寫了一個詞:看吧。把同樣的幾塊拼圖換一種擺法,拼出另一個形狀,兩個形狀面積必然相等,因為它們由同一批零件構成。

Ellenberg 從成年人的視角回看那個木箱時刻,認定那是他一生中非常幾何的一刻。代數事實(兩個數相乘,順序無關)被一塊矩形賦予了視覺上的理由。他後來成為代數幾何學家,某種意義上從那個下午就註定了。

對稱性這個詞,在數學裡被撐得很大

日常語言裡說一個東西對稱,通常指它有對稱軸,左半邊和右半邊長得一樣,或者上下一樣,或者四重對稱。Ellenberg 在大學時迷上的是這套東西的抽象版本,群論。但他說,現代數學裡"對稱"的含義早就溢位了這個範圍。

任何把一個形狀或空間對映到自身的變換,都可以叫對稱。他書裡舉了個自己編的例子:把一個圖形縱向拉長一倍、橫向壓縮一半。古典意義上這當然不算對稱,因為它改變了形狀。但這個操作定義得乾乾淨淨,有輸入有輸出,能重複施加,也能求逆。他給它起了個滑稽的名字,叫"擠壓"(scrunch),因為數學裡本來沒有這個詞。你可以研究什麼樣的圖形在擠壓之下保持不變,就像研究什麼樣的圖形在左右翻轉之下保持不變。

再往上抽一層,就是 Ellenberg 認為支配了當代數學一百五十年的那個核心問題:什麼時候我們認為兩個東西是同一個?

這聽起來像廢話。一個三角形,和另一個尺寸完全相同但放在別處的三角形,是同一個還是兩個?你說這是兩個東西,一個在這兒一個在那兒。可你要是證明了關於第一個的定理,這個定理對第二個多半也成立。

術語叫全等。換個說法,存在一個叫"平移"的對稱,把一切往左挪三英寸,我們希望所有理論都滿足平移不變性。如果一個定理挪三英寸就失效了,那才叫奇怪。

數學是給不同的東西起同一個名字的藝術。(泊松,Ellenberg 引用)

MNIST 難在哪:我們認識的對稱群不夠用

Ellenberg 把這個話題直接接到了機器學習上。他提到 MNIST 手寫數字資料集,說每次盯著它看都覺得有點上頭:一和二的區別到底是什麼?為什麼所有的手寫二彼此相似?哪些變換算"還是同一個數字",哪些變換算"變成別的數字了"?

他說,如果人類識別數字靠的是我們熟悉的那類對稱,問題早就解決了。旋轉是我們理解得極其透徹的一種對稱。假如"1"的所有變體只是某個標準字型裡的 1 旋轉了若干度,寫個程式就能檢測,輕鬆得很。

但實際上不是。我們區分 2 和 3 時用的那套東西,不屬於任何已知的經典對稱群。Ellenberg 說他如果看到有人用某種經典對稱的框架完全刻畫了 2 和 3 的區別,他會非常震驚。他傾向於認為我們做的事情比那更復雜。

Lex 在這裡提了一個他覺得關鍵的點:靜態影象不夠,變形過程本身攜帶資訊。他寫過把 2 連續變形成 3 的程式,看影片的時候,你能相當準確地指出哪一幀開始它不再是 2。但如果只給你一張靜止的中間態圖片,你可能會猶豫,甚至叫它 7。

Ellenberg 順著這個往下說,這恰好也是現代幾何的一個洞察:研究物件可以是靜態的形狀,也可以是形狀的變換。泊松研究三體問題時就撞上了這件事。

從兩個球到三個球,問題從課本習題變成了一百五十年的謎

兩個天體在彼此引力下怎麼動,牛頓時代就清楚了:要麼互相繞著畫橢圓,穩定;要麼一個沿雙曲線掠過另一個,不穩定。兩種情況,分類乾淨。

加到三個,整個動物園就開啟了。這就是三體問題。

泊松(Henri Poincaré)在 1880 年代為瑞典國王懸賞的這個題目做出第一次實質進展,並因此成名。他發現的是混沌動力學的最早例子:穩定解和不穩定解糾纏在一起,初始條件的極小改變會讓長期行為完全不同。一百五十年過去,這個問題仍然遠遠沒有被吃透。

Ellenberg 強調泊松做這件事時被迫發明了一樣東西。要描述三個天體的運動,光記錄位置不夠。每個天體有位置(x、y、z 三個座標),還有此刻的速度。真正該盯的東西長這樣:六維相空間裡的一個點,六個座標同時編碼位置和速度,一顆行星的完整狀態就是這麼一個點。

於是泊松需要一套能談論任意維空間的幾何。他開創的學科當時叫 analysis situs,直譯大概是"位置的分析",這名字顯然沒流行起來,今天叫拓撲學。他那篇論文的開頭幾乎是宣言:今天沒有人懷疑 n 維空間的幾何是實際存在的東西。

Ellenberg 補了一句:泊松從沒離開過物理,但物理把他逼到了高維,他需要一個足夠豐富的形式系統。而一旦你搭起這個系統,它就必然包含非物理的東西。這時候你有兩個選擇。你可以說那些部分是垃圾。也可以採取數學家的態度:這個框架很優雅,很好用,而且裝下了所有物理內容,那也許整個框架都值得研究。後來的事你們都知道了,相對論出現,四維時空成了現實,幾何工具箱早就備好了。

費馬大定理:一個錯誤證明催生了整個現代數論

話題轉到費馬大定理。Ellenberg 先把歷史捋清楚:費馬在丟番圖《算術》的頁邊寫了那句話,說這個方程沒有解,我有一個絕妙的證明,可惜頁邊太窄寫不下。

然後他潑了盆冷水。從歷史材料看,費馬並沒有這個證明。很長一段時間人們願意相信有個失傳的神秘證明,故事很浪漫。但費馬後來證明了若干特殊情況,也跟人通訊討論過這個問題,從他處理那些特殊情況的方式看,他很清楚自己搞不定一般情形。也許他某一刻有過一個深刻的直覺,然後丟了,這已經無法考證。可以確定的是,他晚年並不認為自己藏著一個完整證明。

這個問題的失敗史,在數論裡留下了比問題本身更多的東西。十九世紀有個叫拉梅(Lamé)的人宣佈證明了,證明是錯的。庫默爾(Kummer)去搞清楚拉梅錯在哪,結果撞開了一扇大門。

我們習慣的那個事實是:每個整數都能唯一分解成素數的乘積。12 就是兩個 2 一個 3,沒有別的拆法,你沒法讓 12 裡冒出個 5,也沒法讓它包含四個 3。這個唯一性太基本了,基本到我們把它當成上帝定的規矩。

庫默爾發現,如果你在比整數稍微一般一點的數系裡工作(而這些數系恰好跟費馬問題相關),唯一分解就不成立了。

Ellenberg 在這裡表達了一個很數學家的立場。你剛誇完唯一分解多美多簡潔,我告訴你一般數系裡它塌了,你可能會說這真糟糕。他說不,這很好,因為一整個新世界現象冒出來了,你用原來那副眼鏡永遠看不到。

我高度支援複雜化,因為每一次複雜化都是研究新東西的機會。(Jordan Ellenberg)

形變理論:把"挪一點點"這件事變成一門學問

懷爾斯(Andrew Wiles)和理查德·泰勒(Richard Taylor)最終解決問題的核心工具之一叫形變理論(deformation theory),部分由 Ellenberg 的博士導師 Barry Mazur 創立。

Ellenberg 解釋得很剋制:費馬問題裡出現的那些物件(他提到伽羅瓦表示和模形式,但說這些詞對聽眾沒什麼用)可以被"形變",也就是挪動一點點。形變理論的想法是,如果你非常清楚一個東西能在哪些方向上做無窮小的移動,你也許能把這些區域性資訊拼起來,理解它能在其中移動的整個全域性空間。懷爾斯他們的論證歸結起來,是證明兩個這樣的全域性空間其實是同一個,這就是傳說中證明裡那個"R 等於 T"。

但這套"挪一點點"跟我們在微積分裡學的距離概念不是一回事。這裡就要說到 Ellenberg 書裡反覆出現的一個主題:距離這個概念不是上帝給的。

日常英語裡我們一直在用各種距離。說某人是近親,指的可不是他住隔壁,那是另一套度量。做自然語言處理時,詞與詞之間有語義距離、搭配距離,兩個詞是不是經常出現在相似上下文裡,這跟它們在字典裡隔多少頁毫無關係。

數論裡有一種更離譜的距離,叫 2-adic 距離。普通人說兩個數接近,是指差很小,7 和 8 差 1,很近。2-adic 數論學家說,兩個數接近,是指它們的差是 2 的某個大次冪的倍數。於是 1 和 49 很近,因為差是 48,是 16 的倍數,16 是挺大的 2 的冪。而 1 和 2 很遠,差是 1,連 2 的一次冪都不是。

更怪的是 1 和 1/64,差是 2 的負六次方,在這個度量裡它們是天文數字般的距離。

Lex 的腦子在這裡卡住了,然後他自己找到了鑰匙:這幾乎就是把二進位制數倒著寫。普通二進位制展開裡,一個數很小,意味著小數點後一長串零。在 2-adic 度量裡,一個數很小,意味著它末尾有一長串零,然後才是小數點。Ellenberg 說這個比喻非常好,他早該這麼講。

為什麼這種怪東西有用?因為懷爾斯證明裡用到的形變,正是在這個 2-adic 意義上"挪一點點"。換一套距離,你就能談那些在通常意義下根本不算"附近"的變化,然後從區域性推出整體。

Ellenberg 順手把這個思路推廣到了數學之外:如果你給人類社會定義一種距離,兩個人很近當且僅當他們彼此相愛,然後在這個度量下分析七十億人,也許能看出關於暴力、關於創業、關於制度的一些東西。經濟學某種程度上就在幹這事,但值得把"換一種距離函式"當成一種自覺的方法。

素數:假裝它們是隨機撒的土

談到素數時,Ellenberg 從定義開始較真。素數不能分解,但你說 5 等於 5 乘 1,這也是一種分解。他說這不算,因為這件事對任何數都能做,沒有內容。真正有內容的是把 12 拆成 6 乘 2 再去拆,一路拆到拆不動,剩下的那堆東西就是素數。它們是構成所有整數的原子。

關於 1 是不是素數,他專門說明:歷史上不同時期有不同看法,現在不算,這是定義的選擇,談不上發現了什麼真理。數學定義是我們為了某種目的挑的工具,無所謂哪個定義"真的對"。

然後是一段很好玩的現場演示。他講費馬小定理構成的一種素性測試:取一個神秘數字 n,算 2 的 n 次方,除以 n,看餘數。如果 n 是素數,餘數一定是 2。6 不行,2 的 6 次方是 64,除以 6 餘 4。5 行,32 除以 5 餘 2。7 行,128 除以 7 餘 2。

麻煩的地方在於,這個測試只有一個方向可靠:餘數不是 2,那 n 肯定不是素數;餘數是 2,n 很可能但不確定是素數。存在一批"偽素數",最小的一個是 341,它透過了測試但不是素數。

接著是素數分佈。素數有無窮多個,歐幾里得就證明了。但隨著數字變大,素數越來越稀疏,頭十個數里有四個素數,佔 40%,十位數里絕不可能有 40% 是素數,因為能被整除的機會多了太多。

孿生素數猜想問的是:差為 2 的素數對(3 和 5,11 和 13,17 和 19)有沒有無窮多對?

Ellenberg 在這裡糾正了一個很常見的理解偏差。人們聽到孿生素數猜想,會以為數學家相信素數之間藏著某種深刻結構,讓它們一次又一次靠近。恰恰相反。相信孿生素數猜想,等於相信素數分佈得相當隨機。如果它們真的像隨機撒的土,那按機率算,就該有無窮多對孿生素數。

我們說相信孿生素數猜想,是說我們相信素數像隨機撒的一樣散著。要是真那樣,純靠運氣你就該期望有無窮多對孿生素數。我們是在說,我們預期它們的行為就跟隨機撒的土一樣。(Jordan Ellenberg)

素性是完全確定的,沒有任何隨機性介入。但把素數當成從某個隨機過程裡產生的樣本來研究,效果驚人地好。Ellenberg 說這在數學裡是常規操作:即使面對確定性的規律,也先假裝它不確定,看看行為是否大致吻合,不吻合就微調隨機模型,直到匹配為止。

這個做法的目的不在證明,它服務於一個更前置的任務:先搞清楚該相信什麼。因為最糟的情況是你拼命去證明一個假命題。

Ellenberg 在這裡虛擬了一場和 Sam Harris 式決定論者的對話:你說素數不是隨機過程,它們是完全確定的。我說好,你堅持你的,與此同時我在從"假裝它們隨機"裡源源不斷地挖出洞察,而你挖不出來。所以現實是什麼並不重要,重要的是哪個思考框架能產出最多洞察。

他順勢把這條原則用回到人身上:把別人當成有慾望、有意圖、會故意做事的行動者,即使這個描述在哲學上不成立,你依然會更好地理解發生了什麼。

康威:把數學做成了遊戲,也把遊戲做成了數學

Ellenberg 對約翰·康威(John Conway)的評價是:二十世紀數學家裡少有的那種性格與工作完全纏繞在一起的人。外面的人常以為數學是冷的,跟做數學的人的人生無關。不是。你的性格就在裡面,跟你寫的小說、畫的畫、走路的姿勢一樣。

康威把一切都當成遊戲。他不停地發明遊戲、發明古怪的名字,然後把遊戲拿來做數學分析,分析到跟 Knuth 合作搞出一套數系,超實數(surreal numbers),其中每個數本身就是一個兩人博弈。牛頓時代被人嘲笑為"消失量的鬼魂"的無窮小,在這套系統裡堂堂正正地住下來了,作為某種博弈。

他最有名的創造是生命遊戲(Game of Life)。嚴格說這裡沒有對手,你面對的只是一條寫在方格紙上的規則:每個格子看周圍八個鄰居,活著的格子鄰居太少或太多就死,死了的格子鄰居數量合適就出生。規則一句話寫得完。七十年代他真的是拿筆在方格紙上推演。

從一小片塗黑的格子出發,可以長出豐富到不可思議的結構:滑翔機(glider)會跑,滑翔機槍(glider gun)會不停吐出滑翔機。你甚至可以用生物學的語言描述這些"物種"之間的互動。

Ellenberg 強調了一件常被忽略的事:隨便挑一條規則,什麼都不會發生。絕大多數規則集產生不了任何有趣行為。只有少數被調到恰當位置的規則,才會湧現出複雜結構,而我們並不清楚怎麼預先分辨哪些規則行、哪些不行。

Wolfram 在這條路上走得最遠,也因此在學界邊緣待著。Ellenberg 說把自我放一邊看,他的工作相當精彩,那種達爾文式的探索,把簡單規則鋪開玩上千頁,本身就是有價值的。他的 rule 30 挑戰很簡單也很難:能不能預測中間那一列?沒人做出來。Wolfram 管這叫"不可約性",但 Ellenberg 的評價是,這是詩,不是定理。

康威本人對生命遊戲的態度是矛盾的。他當然知道這是自己在圈外最出名的東西,但他也清楚自己做過遠比這深刻的數學,被簡化成一個"生命遊戲那個人",多少讓他不舒服。

龐加萊猜想:真正的幾何是"所有幾何構成的空間"的幾何

龐加萊猜想問的是三維空間的分類。Ellenberg 用馬克杯做道具解釋:杯子表面畫一個圈,你可以把它收縮成一個點。但要是圈套在杯把上,你怎麼挪都收不緊,除非把杯子弄破。"單連通"指的就是任何圈都能收成一個點。龐加萊猜想說,一個三維空間如果滿足單連通,它就是標準的三維空間。

證明的關鍵動作是往上跳一層:你要理解的是所有三維幾何構成的那個空間,那個具體的三維空間本身反而退到了第二位。在這個更高層的空間裡,你可以讓某個未知空間沿裡奇流(Ricci flow)運動,看它流向哪裡。奇怪的是,它總會流到標準三維空間去。既然從一個神秘空間出發能連續變形到標準空間,中間沒有任何突變,那它一開始就跟標準空間是同一個。

技術上最難的一塊,是證明這個流動過程中不會出現奇點,也就是不會突然長出尖角、喪失光滑性。這活兒是佩雷爾曼(Grigori Perelman)幹成的,而且不是孤軍奮戰,前面有理查德·漢密爾頓等人鋪了幾十年的路。Ellenberg 特意強調這一點,懷爾斯的證明也一樣:從十九世紀的庫默爾,到弗雷、Mazur、裡貝特,很多人在砌拱門的石塊,最後才有人放上拱心石。

佩雷爾曼拒領菲爾茲獎。Ellenberg 的看法是:從某種宏大的精神意義上說,獎項不重要,理解宇宙才重要。但另一方面,大多數被授予這個獎的人都接受了,所以他的選擇確實不尋常。這件事的提醒是,人的一生中大概會有那麼一兩次,社會希望你做的事和你相信的東西衝突,你得站住。這就是正直。它不需要讓旁人理解。

吸管有幾個洞:一場數學家也會吵起來的爭論

Ellenberg 在書裡拿這個問題開刀。你隨便問一屋子人,喜劇效果立刻出現:每個人都覺得答案明擺著,然後發現別人給出的明顯答案跟自己不一樣,接著就吵起來了,還吵得挺兇。

零派很罕見:他們說你拿一塊長方形塑膠片把兩邊粘起來就是吸管,長方形塑膠片上沒有洞,我也沒在上面戳洞,哪來的洞。Ellenberg 說這個立場你得一貫到底:那你也得說貝果沒有洞,因為貝果是把一根長條麵糰兩頭捏在一起做的。你要真這麼說,那我不知道你是個什麼樣的人。

一派說一個洞:洞是一個區域,它貫穿整個吸管,就一個。兩派說兩個洞:上面一個口,下面一個口。兩派還喜歡拿水瓶做現場演示,擰開蓋子說這裡面有一個洞,現在我在這兒戳個洞讓水漏出來,這不就變成吸管了?於是一派會問:原來有一個洞,我又戳了一個新的,你現在還認為只有一個洞?

一派會反問:那你告訴我,第一個洞在哪兒結束,第二個洞又從哪兒開始?

Ellenberg 說,遇到讓人糊塗的問題,數學有兩個動作。一個是把問題變簡單,比如降到低維,先想圓和線段。另一個是把問題變難,把複雜情況攤開來講,比如不聊吸管了,聊褲子。

大多數人會說褲子有三個洞:腰一個,兩條腿各一個。但他女兒說,褲子只有兩個洞,因為腰不過是兩條腿的洞粘在一起。

這個孩子的答案恰好抓住了同調論(homology)的核心:洞是有算術的,可以相加。腰洞等於左腿洞加右腿洞,等式兩邊都不是數字,是某種幾何物件,這大概就是拓撲學最讓人撓頭的地方。

用吸管演示這個"加法":你吸一口奶昔,從頭進多少,從另一頭就出多少。兩個口彼此牽連,各自的流量不能單獨變動。褲子的版本是:左腿流進去的量加上右腿流進去的量,等於從腰流出來的量。

所以現代數學家的說法是:有兩個洞,但一個是另一個的負號。Ellenberg 把這個想法歸功於 Emmy Noether,是她把這個學科放到了現代基礎上。在此之前,泊松和貝蒂(Betti)已經在往這個方向走,但真正讓"洞之間的關係"變成一門可以計算的學問,是 Noether 的手筆。

數學怎麼學:讓問題帶你進去,而不是讓課程表帶你進去

Lex 問怎麼學數學,尤其是成年後想重新撿起來的人。Ellenberg 說他答不出唯一答案,因為這件事本質上是自我認知的旅程,得知道什麼對你有用,而這因人而異。

有人就是能抱著教科書啃,這確實是一種可行路徑,對一部分人有效,對另一部分人無效。對另一部分人,入口是 Martin Gardner 在《科學美國人》上寫了幾十年的專欄"數學遊戲",那種純粹的玩心,集結成書之後雖然年頭久了,但每一代新讀者翻到都還是新鮮的。還有人適合做競賽題,俄國和保加利亞的題集出了一本又一本。還有人適合看製作精良的影片。

然後他講了一個自己在研究生院的故事。他有段時間被自己的無知壓得喘不過氣,跟系裡的代數幾何教授 Joe Harris 說,我想休學一年,把 EGA(《代數幾何原理》,一千五百多頁的多卷本聖經)從頭讀到尾。

Harris 說這主意很蠢。

為什麼蠢?因為你不會真的去讀。你會因為手上有個問題要解決,需要 EGA 裡的某條結論,才去學那一條。沒有真問題牽著,你學不進去。

Ellenberg 把這條經驗推廣開來:數學很難,任何做對的事都難。正因為難,別人告訴你"你該學 XYZ",如果你其實不在乎,你就學不會。你得把它掛到一件你真正在乎的事情上。可能是一個工程問題,一個物理問題,一個機器學習問題。讓問題驅動你的學習,課程表驅動不了任何人。

Lex 補了一段關於"難"的看法。他說自己討厭跑步,討厭運動,跑步時唯一享受的是跑完之後那一整天的感覺。做數學的體驗幾乎一樣:一堆概念在腦子裡懸著,記號含混,圖畫缺了好幾塊,你得扛住那種"明顯沒搞懂但還得往前推"的挫敗感。而記住那種"難了很久,然後在某一刻,整張圖完整了"的美感,是支撐人反覆回來的東西。

Ellenberg 對"享受"這個詞做了修正:他不覺得需要享受死衚衕,死衚衕很氣人。人得接受它是過程的一部分。

Lex 在這裡丟擲了 David Goggins 的那套心態:大多數人到這兒就放棄了,如果我不放棄,就有機會看到別人沒看到的東西。Ellenberg 的反擊很乾脆:那按這個邏輯,每年內森熱狗大賽的冠軍吃到第 35 個熱狗時也完全可以這麼說,大多數人到這兒就停了。兩人就此達成一致,這個問題沒有標準答案。

給年輕人的建議:做那個高自尊的選擇

Ellenberg 有兩個孩子,所以這不是思想實驗。他說他常跟學生講,人走到岔路口時總被自我懷疑纏住,不確定自己能幹什麼,不確定真想幹什麼。

他的建議是:把自我懷疑那個變數抽掉,想象一個完全自信版本的你會怎麼選,然後照著做,看看會發生什麼。

他特意加了限定:這不是說你該消滅懷疑,人大概應該有懷疑。但有時候,按照那個沒有懷疑的人的方式去行動,是對的。

Ellenberg 說這話時提了一句,他其實還沒跟自己孩子講過。Lex 說那應該講,這是個非常有用的辦法。

關於"人生的意義能不能用數學找到",Ellenberg 的回答挺乾脆。他提到帕斯卡,這位數學天才同時也是極認真的宗教神秘主義者。人們以為帕斯卡的賭注是用數學論證你該信神,但他真讀帕斯卡的原文,發現幾乎相反。你要是問帕斯卡為什麼信,他會說我遇見了神,他有過一次強烈的神秘體驗,那就夠了,跟數學論證無關。數學論證說的是行為層面的理由:你無論如何都要下注,那就押一個期望值更高的。

你已經有數學了,有探索心智的方式,有了不起的技術,還有愛和友誼。你還想知道這一切的意義是什麼?享受它吧。(Jordan Ellenberg)

他書裡還有另一位數學家的說法值得一提。Hilda Hudson 參與了今天用來追蹤傳染病的 SIR 模型的前身工作,同時是極其虔誠的教徒。她說數學的真理不是上帝思想裡最重要的那些,但它是唯一我們能精確知道的那部分。而泊松的態度更冷一點:就算有個神明把宇宙的真相用神的語言講給我們聽,我們也理解不了,所以那不重要。我們的任務是搞清楚那些我們搞得清楚的部分。

Erdős 提供了第三種版本。他管那本收錄了每個定理最漂亮證明的書叫"天書"(The Book),看到特別優雅的證法就說這出自天書。他本人不信教,還管上帝叫"最高法西斯",但天書他一直掛在嘴邊。這位一輩子在幾個行李箱之間輾轉、跟幾百個合作者聯名發論文的人,最終把自己的社交網路變成了一個度量衡,Erdős 數至今還在數學家之間流傳。衡量兩個人遠近的,是合作鏈條的長短,這跟地理毫無關係,正好回到前面那個"換一把尺子"的話題。

為什麼"簡單"這個執念值得警惕

Lex 提到費曼那句流傳很廣的話:如果你不能把一件事簡單地講清楚,說明你沒真懂。Ellenberg 的反應直接:假的。然後他補一句,但要問它有沒有深刻之處,那當然有。

真實的東西不簡單,少數簡單,大部分不簡單。學著一遍遍解釋,會幫你理解,這部分是真的。至於費曼有沒有真說過這話,本身就有爭議,而且 Ellenberg 懷疑費曼那樣的人不會真的字面相信它,他喜歡說漂亮話,他享受說這話的感覺。

Lex 補充了一個觀察:他見過不少物理學家從"相信世界可以被簡單解釋"裡獲得巨大快樂,即使他們的解釋其實並不簡單。那些解釋更像是一首關於複雜事物的詩,而不是濃縮。Ellenberg 接了一句:詩不是解釋,沒有詩人會說自己寫的是解釋,他們說的是描述,是捕捉。

不過他還是承認,簡潔有一種近乎審美的吸引力,而這種吸引力有時會帶來麻煩。人類歷史上那些以仇恨和暴力為核心的時期,背後常常也有一套極簡的敘事在驅動。簡潔令人愉快,恰如幸福令人愉快,但它本身不構成判斷真假的理由。

回到數學內部。Ellenberg 說,我們還沒學會怎麼在學術數學裡恰當地評價"視覺化"這件事的價值,也沒學會怎麼評價"構建計算基礎設施"這件事的價值。今天所有人都有計算機當夥伴,有人造出幫助數學研究的系統,那也是數學,只是不是傳統意義上寫論文證定理的那種形式。他提到布朗大學的計算與實驗數學研究所,那是 NSF 資助的正規數學機構,他們專門辦過一個主題學期討論數學視覺化,按前沿研究課題的規格來對待。數學界確實在認這件事,只是速度慢。

他還提到 3Blue1Brown 的 Grant Sanderson,用 Python 程式設計做視覺化。你必須真正理解一個主題,才能把它畫成那樣,還得用一種很新穎的方式去想它。整個數學 YouTube 生態的意義在於覆蓋了不同的傳播頻寬:博士導師一對一帶一個學生三五年,頻寬最高,人數最少;課堂幾十上百人,一個學期;書能觸達更多人,讀者投入幾小時;影片觸達的人比任何精裝書都多。每個位置都重要,因為每個人的腦子掛東西的鉤子長得都不一樣。

Lex 在這裡插了一句自己的抱怨:他偶爾逛進拓撲學的領地,感覺那裡數學太密了,密到有點妨礙理解。他說波恩纖維化(Hopf fibration)那類東西,二十年前某個研究生拿 Fortran 寫個程式畫出來,然後就再沒人碰過。拓撲學明明是視覺性的學科,視覺資源卻少得可憐。Ellenberg 給了個不算客氣的回擊:一張波恩纖維化的圖對他什麼用都沒有,但有人告訴他這其實是四元數的一個子群,他立刻就說懂了。你早說這個啊,為什麼給我看那張沒用的圖。

兩人在這裡達成了一項共識,而且它比聽起來重要:解釋沒有唯一正確的方式。人腦上的鉤子和環長得千奇百怪,你不知道什麼東西會掛住,而掛住的東西對不同人不一樣。單一文化是有害的。但也正因為如此,把一群彼此不理解的聰明人摁在一起,逼他們找一箇中間地帶,常常能撞出新東西。寫書這件事本身就會逼出新的想法,因為壓縮的過程會重新組織你原本以為自己已經想清楚的東西。

Ellenberg 用詩和散文做了個類比:你為什麼需要詩?你想傳遞資訊,說清楚不就行了。但詩確實做了點別的事,抒情詩往往把一件用散文講要很久很複雜的事情壓縮排另一種模式,用不一樣的方式擊中你。

菲爾茲獎、AI 和那些被機器吃掉的工作

Lex 問:會不會有一天,一個 AI 拿到菲爾茲獎?

Ellenberg 說不會。

Lex 追問為什麼。

Ellenberg 說,這大概就是人類給自己設的驗證碼吧,用來證明我是個人。

他真正的回答更長:計算機早就吃掉了大量我們以前叫"數學研究"的工作。1890 年,一篇博士論文可以是在某個有限群作用下算出某個多項式環的全部不變數,一個人算一年,這是有價值的知識。今天你寫幾行 Macaulay、Sage、Magma 的程式碼就出來了,那件事我們已經不叫數學了。同一件事,換了工具,就換了身份。這些軟體是符號計算系統,跟 Maple 和 Mathematica 同類,只是更專門。它們不做證明,也不算真的在做數學思考,但它們現在是大多數數學家工作流程的一部分。

至於讓 AI 證有意思的定理,目前成績不佳。他提到一篇用神經網路找反例的論文,效果不錯,但那些被推翻的猜想都不是什麼著名猜想。你要是讓五個研究生認真想想那些問題,多半也能想到那個反例。不過那仍然很酷。

還有 Conway 結的故事。一個結是不是"可切片的"(slice),這跟它能圍出什麼樣的三維曲面、在四維裡怎麼延拓有關,技術細節不重要,重點是這個問題很難算。Conway 結這個特例卡了拓撲學界二十年。2018 年前後,當時在德州大學奧斯汀分校讀博的 Lisa Piccirillo 解決了它,論文九頁,其中兩頁是圖。Ellenberg 是在準備講這個故事時才發現裡面有個奧斯汀的緣分,他自己也沒想到。Piccirillo 現在在 MIT,某種意義上是在跟著 Lex 走。Lex 說反了,是他跟著她走。

這篇論文讓人不得不重新想什麼叫"難"。一個問題是難,因為解法複雜?還是因為全世界頂尖專家搞了二十年都沒搞出來?還是說我們需要一個新的類別,專門描述"很難發現它其實不難"這類問題?

群論、規範場和那個"太快了"的建議

Ellenberg 用一種很樸素的方式介紹群論。人基本是左右對稱的,兩個對稱:翻轉,和不翻轉。等等,你說只有一個?做和不做,這是兩種狀態,所以是兩個。矩形更多,不但能左右翻,還能上下翻,於是四個:不翻、左右翻、上下翻、兩個都做。正方形又多出一批,因為你可以轉九十度,而矩形轉九十度就變樣了,那不算對稱。人兩個,矩形四個,正方形八個。真正讓這套東西成為一門學問的觀察是:這些變換可以複合,你先做一個再做一個,結果是第三個,整批變換在這個運算下自成一個封閉的世界,這就是群。

無限群也很好懂。看一條直線,你可以沿任意一點左右翻轉,也可以整體平移任意距離,這兩種操作無限多,而且能複合,所以直線的對稱群是無限的。洗牌同樣如此:一副牌的所有排列構成一個群,你洗一次我再

洗牌同樣如此:一副牌的所有排列構成一個群,你洗一次我再洗一次,結果是另一種排列,也在這個群裡。

Lex 順勢問規範對稱(gauge symmetry)是什麼,這在物理學裡被反覆提起,卻很少有人講清楚。Ellenberg 坦白自己不是數學物理學家,但給了一個他認為合理的輪廓:物理學一直在問"世界的對稱群到底是什麼"。

如果重力在這裡是這樣,在別處也該是那樣,那麼平移就該是物理定律的一個對稱。從愛因斯坦之前到愛因斯坦之後的那次大轉彎,某種意義上是我們更換了對"世界的對稱群到底是什麼"的判斷。洛倫茲收縮這類現象,在舊框架下看起來是物體接近光速時形狀變了,在新框架下,你會發現它從沒變過形狀,你只是搞錯了什麼叫對稱。換上洛倫茲群之後,所謂變形就消失了,它成了一場幻覺。

Lex 對這個回答仍不滿意,他說自己一直在做一件不太系統的事:為每個複雜概念找一個最小的、可程式設計的、能親手玩的例子。Ellenberg 說這正是最好的教學法,他們就是這麼訓練學生的。

這也解釋了為什麼泊松這種人在數學史上如此重要。他從三體問題出發,被逼到高維幾何,然後那套幾何在幾十年後成了相對論的現成語言。工具先於用途誕生,這在數學裡是常態。

平地:把二維生物拽出它的世界

Lex 問了一個他自己也沒把握的設想:如果你住在一個球面內部,往任何一個方向看,是不是都會看到自己的後腦勺?

Ellenberg 說,這個設想裡"看見"這個詞承擔了太多沒說清楚的東西,光的物理規律在這個場景裡怎麼工作,他一時也拿不準。但他很確定這類想象本身有多重要,因為它一遍遍回到思想史上。

他提到 Edwin Abbott 的《平地》(Flatland)。十九世紀一位牧師寫的漫畫式小說,主角是個正方形,一個二維世界的居民。某天他在家裡,眼前憑空出現一個小圓,然後越變越大,很恐怖。那是球體正在穿過他的世界,截面在擴張。等球體穿到正中間,兩人開始爭論。球體說我來自三維,正方形說你在胡說,沒有那種東西。兩人用幾何推理來回拉鋸,正方形跟不上,直到球體一把把他揪出平面。你在上面看一眼,就明白你的整個世界了。

Ellenberg 說,Abbott 是牧師,這本書有明確的宗教潛臺詞:如果一個更高的存在能把你從這個塵世裡拎出來,讓你從上往下看見真相,那意味著什麼。有意思的是這層寓言最後走向了相當顛覆的方向。正方形被拎出來、學會了推理之後非常興奮,說既然你能讓我理解三維立方體,那我也可以靠推理想清楚四維的我是什麼樣吧。球體怒了:哪來的第四維,就三維,我能看見。

Lex 把這個寓言接到了正題上:數學能做人類視覺做不到的事。我們沒法在腦子裡成像一個四維立方體,但我們完全可以算出六維立方體有多少個頂點。這件事本身就是人類認知裡非常了不起的一部分,視覺化和可推理是兩條腿。

Ellenberg 說,宇宙有沒有超出我們感知的額外維度?很可能有。但你沒法直接驗證,你只能去推那些額外維度會在這個可感知的世界裡留下什麼痕跡。如果痕跡為零,這個問題就開始變得空洞,因為你也可以隨便假設任意多的實體,反正都沒影響。

他還提到拓撲學一個非常迷人的性質:它討論的是內稟屬性,你不需要從世界外面看世界。馬克杯上那個問題,一個從未離開杯麵的生物也能回答。他降到一維做示範:你住在一個圓上,往一個方向走足夠久會回到出發點;你住線上段上,走足夠久會撞到世界的盡頭。這個區別你不需要跳出你的世界就能知道。而如果你住在一個漂浮於三維空間的結上,對你而言它就是一條圓。我們這些有三維眼睛的旁觀者才看得出這個圈打了個結,這件事關乎它如何嵌入外部空間,跟它自己的內稟性質無關。

Lex 承認自己對"我到底住在圓上還是住在結上"這類問題毫無不安,睡得著覺。Ellenberg 說他也是這樣。然後是那個著名的莫比烏斯帶問題:你怎麼知道自己住在一個圓柱面上還是莫比烏斯帶上?Lex 說,你跟朋友說好站這兒別動,我走一圈就回來,然後你走回來,發現朋友被映象了。Ellenberg 笑著指出這個方案的實際困難:你朋友已經被翻成映象了,你還能認出那是你朋友嗎?你連自己會不會被翻過來都不確定。

他說真正可行的辦法,是找一個繞兩圈才能收縮的圈。莫比烏斯帶和實射影平面(一個更擰巴的近親)上有這種構造,你把一根繩子沿某個方向繞一圈,怎麼都拉不緊,但沿同一條路徑再繞一圈,就能收成一個點。這是你在自己世界裡就能察覺的怪事。

Lex 繞了一大圈之後回到正題:既然球體的困境是它看不見第四維,那我們會不會也活在某個更高等存在的"平地"裡?物理學家搞統一場論時動不動就往十維十一維上跑,那到底只是好用的記賬方式,還是宇宙真有我們感知不到的維度?

Ellenberg 的回答很剋制:很可能有,但你只能透過它在這個世界裡留下的可觀測後果來判斷。如果什麼後果都沒有,這個問題就失去了落腳點。你可以隨便假設多少個實體,只要它們不產生任何可觀測差別,那這些假設就是空的。

可操作的部分

  • 下次遇到"這明顯是 X"的判斷,先問一句:在什麼變換下它還是 X?把判定標準寫下來,你會發現大部分時候你說不清,而說不清的地方正是問題所在。
  • 想重學數學,不從教材第一章開始。先找一個你手上真在乎的問題,讓這個問題把你拽進需要的章節。Ellenberg 的導師原話是:不帶著問題,你不會真的讀下去。
  • 給孩子或給外行講數學,用"吸管有幾個洞""褲子有幾個洞"這類問題開場。零成本,會吵起來,而吵架的過程中對方會自己想通同調的第一步:洞可以相加。
  • 做重大決定時,把自我懷疑當噪聲處理。寫出一個完全自信的你會選什麼,然後照著做。做完了再看結果。
  • 看到別人用"把 X 當成 Y"來研究 Z,別急著說這不真實。素數不是隨機的,但當成隨機來研究產出最多洞察。一個描述是否"真",很多時候不如它是否好用重要。
  • 如果你在學一樣被公認為"很直觀"的東西卻完全無感,先別下結論說自己不行。Ellenberg 說幾何是數學裡的香菜,有人一口就上癮,有人整年嘗不出味道,而他自己明明屬於後者。九年級那門歐幾里得幾何課,證明等腰三角形底角相等之類的練習,跟他不來電。真正擊中他的是六歲那年客廳裡一個音響木箱。入口不止一個,換一個再試,這句話對孩子和對成年人都成立。
  • 想親身感受一次維度躍遷的眩暈,讀 Edwin Abbott 的《平地》。故事很短,一晚上能讀完,最鋒利的一刀在結尾:正方形學會了推廣,追問他自己的四維版本,球體勃然大怒。你可以在那一刻停下來,想想自己有多少次扮演了那個球體。
  • 想在手機上親眼看看複雜結構怎麼從一行規則裡長出來,裝一個 Golly。康威生命遊戲的規則一句話寫得完,從一小片塗黑的格子能長出滑翔機,能長出不停吐出滑翔機的槍。順便驗證 Ellenberg 提到的那件反直覺的事:隨手挑一條規則,什麼都不會發生。絕大多數規則集是死的,能湧現複雜行為的是極少數,而我們至今不知道怎麼預先分辨哪些行、哪些不行。Wolfram 的 rule 30 挑戰至今沒人做出來,他那套"不可約性"的說法,Ellenberg 的評價是:這是詩,不是定理。
  • 別把數學競賽當成數學的門票,也別因為競賽而誤解數學。Ellenberg 1987 年第一次參加國際數學奧林匹克,那年在哈瓦那辦,美國人當時去不了古巴,手續極其麻煩,主辦方還把整支美國隊拉去"美國帝國主義博物館"參觀了一圈。他管這叫冷戰的一部分。奧賽的題目都有已知答案,比的是速度;研究面對的是沒人知道答案的問題,比的是別的肌肉。他還順帶澄清了一個流傳很廣的誤會:奧賽金牌發給前十二分之一的選手,一年幾十塊,跟奧運會上每個專案只發一塊金牌完全不是一回事。他提到格羅滕迪克有一次講課時需要舉一個素數做例子,隨口說了 57,而 57 是三乘十九,這件事在某些圈子裡至今還是個笑話。
  • 給自己準備一套"換距離函式"的思維動作。遇到一個怎麼看都看不透的局面,先別急著分析,問一句:我預設的那個衡量遠近的標準,換一個會不會讓問題變形?地理距離之外有語義距離,有親疏距離,有利益一致性的距離。素數在 2-adic 距離下,1 和 49 是近鄰,1 和 2 是老死不相往來。同一批物件,換一把尺子,藏著的關係就浮出來了。
  • 最後一條,關於什麼時候該停下來。Ellenberg 的導師攔住了那個想休學一年讀完一千五百頁 EGA 的年輕人,理由不是書不好,是你不會真的讀。凡是難的事,熱情都得掛在具體的問題上。如果你現在的學習計劃裡全是"我應該懂",沒有一句"我想知道",那就先停,去找那個你真的想知道的問題。找不到就先不學,這也是一種誠實的判斷。
文稿來自公開 Kaggle 資料集(rajneesh231/lex-fridman-podcast-transcript),為早期自動轉錄存檔,可能存在識別錯誤。
The following is a conversation with Jordan Ellenberg, a mathematician at University of Wisconsin and an author who masterfully reveals the beauty and power of mathematics in his 2014 book, How Not To Be Wrong, and his new book, just released recently, called Shape, The Hidden Geometry of Information, Biology, Strategy, Democracy, and Everything Else. Quick mention of our sponsors, Secret Sauce, ExpressVPN, Blinkist, and Indeed. Check them out in the description to support this podcast. As a side note, let me say that geometry is what made me fall in love with mathematics when I was young. It first showed me that something definitive could be stated about this world through intuitive visual proofs. Somehow, that convinced me that math is not just abstract numbers devoid of life, but a part of life, part of this world, part of our search for meaning. This is the Lex Friedman podcast, and here is my conversation with Jordan Ellenberg. If the brain is a cake. It is? Well, let's just go with me on this, okay? Okay, we'll pause it. So for Noam Chomsky, language, the universal grammar, the framework from which language springs is like most of the cake, the delicious chocolate center, and then the rest of cognition that we think of is built on top, extra layers, maybe the icing on the cake, maybe consciousness is just like a cherry on top. Where do you put in this cake mathematical thinking? Is it as fundamental as language? In the Chomsky view, is it more fundamental than language? Is it echoes of the same kind of abstract framework that he's thinking about in terms of language that they're all really tightly interconnected? That's a really interesting question. You're getting me to reflect on this question of whether the feeling of producing mathematical output, if you want, is like the process of uttering language or producing linguistic output. I think it feels something like that, and it's certainly the case. Let me put it this way. It's hard to imagine doing mathematics in a completely nonlinguistic way. It's hard to imagine doing mathematics without talking about mathematics and sort of thinking in propositions. But maybe it's just because that's the way I do mathematics, and maybe I can't imagine it any other way, right? Well, what about visualizing shapes, visualizing concepts to which language is not obviously attachable? Ah, that's a really interesting question. And one thing it reminds me of is one thing I talk about in the book is dissection proofs, these very beautiful proofs of geometric propositions. There's a very famous one by Baskara of the Pythagorean theorem, proofs which are purely visual, proofs where you show that two quantities are the same by taking the same pieces and putting them together one way and making one shape and putting them together another way and making a different shape, and then observing that those two shapes must have the same area because they were built out of the same pieces. There's a famous story, and it's a little bit disputed about how accurate this is, but that in Baskara's manuscript, he sort of gives this proof, just gives the diagram, and then the entire verbal content of the proof is he just writes under it, behold. Like that's it. And it's like, there's some dispute about exactly how accurate that is. But so then there's an interesting question. If your proof is a diagram, if your proof is a picture, or even if your proof is like a movie of the same pieces like coming together in two different formations to make two different things, is that language? I'm not sure I have a good answer. What do you think? I think it is. I think the process of manipulating the visual elements is the same as the process of manipulating the elements of language. And I think probably the manipulating, the aggregation, the stitching stuff together is the important part. It's not the actual specific elements. It's more like, to me, language is a process and math is a process. It's not just specific symbols. It's in action. It's ultimately created through action, through change. And so you're constantly evolving ideas. Of course, we kind of attach, there's a certain destination you arrive to that you attach to and you call that a proof, but that's not, that doesn't need to end there. It's just at the end of the chapter and then it goes on and on and on in that kind of way. But I gotta ask you about geometry and it's a prominent topic in your new book, Shape. So for me, geometry is the thing, just like as you're saying, made me fall in love with mathematics when I was young. So being able to prove something visually just did something to my brain that it had this, it planted this hopeful seed that you can understand the world, like perfectly. Maybe it's an OCD thing, but from a mathematics perspective, like humans are messy, the world is messy, biology is messy. Your parents are yelling or making you do stuff, but you can cut through all that BS and truly understand the world through mathematics and nothing like geometry did that for me. For you, you did not immediately fall in love with geometry, so how do you think about geometry? Why is it a special field in mathematics? And how did you fall in love with it if you have? Wow, you've given me like a lot to say. And certainly the experience that you describe is so typical, but there's two versions of it. One thing I say in the book is that geometry is the cilantro of math. People are not neutral about it. There's people who like you are like, the rest of it I could take or leave, but then at this one moment, it made sense. This class made sense, why wasn't it all like that? There's other people, I can tell you, because they come and talk to me all the time, who are like, I understood all the stuff where you're trying to figure out what X was, there's some mystery you're trying to solve it, X is a number, I figured it out. But then there was this geometry, like what was that? What happened that year? Like I didn't get it. I was like lost the whole year and I didn't understand like why we even spent the time doing that. So, but what everybody agrees on is that it's somehow different, right? There's something special about it. We're gonna walk around in circles a little bit, but we'll get there. You asked me how I fell in love with math. I have a story about this. When I was a small child, I don't know, maybe like I was six or seven, I don't know. I'm from the 70s. I think you're from a different decade than that. But in the 70s, we had a cool wooden box around your stereo. That was the look, everything was dark wood. And the box had a bunch of holes in it to let the sound out. And the holes were in this rectangular array, a six by eight array of holes. And I was just kind of like zoning out in the living room as kids do, looking at this six by eight rectangular array of holes. And if you like, just by kind of like focusing in and out, just by kind of looking at this box, looking at this rectangle, I was like, well, there's six rows of eight holes each, but there's also eight columns of six holes each. Whoa. So eight sixes and six eights. It's just like the dissection proofs we were just talking about, but it's the same holes. It's the same 48 holes. That's how many there are, no matter whether you count them as rows or count them as columns. And this was like unbelievable to me. Am I allowed to cuss on your podcast? I don't know if that's, are we FCC regulated? Okay, it was fucking unbelievable. Okay, that's the last time. Get it in there. This story merits it. So two different perspectives in the same physical reality. Exactly. And it's just as you say. I knew that six times eight was the same as eight times six. I knew my times tables. I knew that that was a fact. But did I really know it until that moment? That's the question, right? I sort of knew that the times table was symmetric, but I didn't know why that was the case until that moment. And in that moment I could see like, oh, I didn't have to have somebody tell me that. That's information that you can just directly access. That's a really amazing moment. And as math teachers, that's something that we're really trying to bring to our students. And I was one of those who did not love the kind of Euclidean geometry ninth grade class of like prove that an isosceles triangle has equal angles at the base, like this kind of thing. It didn't vibe with me the way that algebra and numbers did. But if you go back to that moment, from my adult perspective, looking back at what happened with that rectangle, I think that is a very geometric moment. In fact, that moment exactly encapsulates the intertwining of algebra and geometry. This algebraic fact that, well, in the instance, eight times six is equal to six times eight. But in general, that whatever two numbers you have, you multiply them one way. And it's the same as if you multiply them in the other order. It attaches it to this geometric fact about a rectangle, which in some sense makes it true. So, who knows, maybe I was always fated to be an algebraic geometer, which is what I am as a researcher. So that's the kind of transformation. And you talk about symmetry in your book. What the heck is symmetry? What the heck is these kinds of transformation on objects that once you transform them, they seem to be similar? What do you make of it? What's its use in mathematics or maybe broadly in understanding our world? Well, it's an absolutely fundamental concept. And it starts with the word symmetry in the way that we usually use it when we're just like talking English and not talking mathematics, right? Sort of something is, when we say something is symmetrical, we usually means it has what's called an axis of symmetry. Maybe like the left half of it looks the same as the right half. That would be like a left, right axis of symmetry. Or maybe the top half looks like the bottom half or both. Maybe there's sort of a fourfold symmetry where the top looks like the bottom and the left looks like the right or more. And that can take you in a lot of different directions. The abstract study of what the possible combinations of symmetries there are, a subject which is called group theory was actually one of my first loves in mathematics when I thought about a lot when I was in college. But the notion of symmetry is actually much more general than the things that we would call symmetry if we were looking at like a classical building or a painting or something like that. Nowadays in math, we could use a symmetry to refer to any kind of transformation of an image or a space or an object. So what I talk about in the book is take a figure and stretch it vertically, make it twice as big vertically and make it half as wide. That I would call a symmetry. It's not a symmetry in the classical sense, but it's a well defined transformation that has an input and an output. I give you some shape and it gets kind of, I call this in the book a scrunch. I just had to make up some sort of funny sounding name for it because it doesn't really have a name. And just as you can sort of study which kinds of objects are symmetrical under the operations of switching left and right or switching top and bottom or rotating 40 degrees or what have you, you could study what kinds of things are preserved by this kind of scrunch symmetry. And this kind of more general idea of what a symmetry can be. Let me put it this way. A fundamental mathematical idea, in some sense, I might even say the idea that dominates contemporary mathematics. Or by contemporary, by the way, I mean like the last like 150 years. We're on a very long time scale in math. I don't mean like yesterday. I mean like a century or so up till now. Is this idea that it's a fundamental question of when do we consider two things to be the same? That might seem like a complete triviality. It's not. For instance, if I have a triangle and I have a triangle of the exact same dimensions, but it's over here, are those the same or different? Well, you might say, well, look, there's two different things. This one's over here, this one's over there. On the other hand, if you prove a theorem about this one, it's probably still true about this one if it has like all the same side lanes and angles and like looks exactly the same. The term of art, if you want it, you would say they're congruent. But one way of saying it is there's a symmetry called translation, which just means move everything three inches to the left. And we want all of our theories to be translation invariant. What that means is that if you prove a theorem about a thing that's over here, and then you move it three inches to the left, it would be kind of weird if all of your theorems like didn't still work. So this question of like, what are the symmetries and which things that you want to study are invariant under those symmetries is absolutely fundamental. Boy, this is getting a little abstract, right? It's not at all abstract. I think this is completely central to everything I think about in terms of artificial intelligence. I don't know if you know about the MNIST dataset, what's handwritten digits. And you know, I don't smoke much weed or any really, but it certainly feels like it when I look at MNIST and think about this stuff, which is like, what's the difference between one and two? And why are all the twos similar to each other? What kind of transformations are within the category of what makes a thing the same? And what kind of transformations are those that make it different? And symmetries core to that. In fact, whatever the hell our brain is doing, it's really good at constructing these arbitrary and sometimes novel, which is really important when you look at like the IQ test or they feel novel, ideas of symmetry of like playing with objects, we're able to see things that are the same and not and construct almost like little geometric theories of what makes things the same and not and how to make programs do that in AI is a total open question. And so I kind of stared and wonder how, what kind of symmetries are enough to solve the MNIST handwritten digit recognition problem and write that down. And exactly, and what's so fascinating about the work in that direction from the point of view of a mathematician like me and a geometer is that the kind of groups of symmetries, the types of symmetries that we know of are not sufficient. So in other words, like we're just gonna keep on going into the weeds on this. The deeper, the better. A kind of symmetry that we understand very well is rotation. So here's what would be easy. If humans, if we recognize the digit as a one, if it was like literally a rotation by some number of degrees or some fixed one in some typeface like Palatino or something, that would be very easy to understand. It would be very easy to like write a program that could detect whether something was a rotation of a fixed digit one. Whatever we're doing when you recognize the digit one and distinguish it from the digit two, it's not that. It's not just incorporating one of the types of symmetries that we understand. Now, I would say that I would be shocked if there was some kind of classical symmetry type formulation that captured what we're doing when we tell the difference between a two and a three. To be honest, I think what we're doing is actually more complicated than that. I feel like it must be. They're so simple, these numbers. I mean, they're really geometric objects. Like we can draw out one, two, three. It does seem like it should be formalizable. That's why it's so strange. Do you think it's formalizable when something stops being a two and starts being a three? Right, you can imagine something continuously deforming from being a two to a three. Yeah, but that's, there is a moment. Like I have myself written programs that literally morph twos and threes and so on. And you watch, and there is moments that you notice depending on the trajectory of that transformation, that morphing, that it is a three and a two. There's a hard line. Wait, so if you ask people, if you showed them this morph, if you ask a bunch of people, do they all agree about where the transition happened? Because I would be surprised. I think so. Oh my God, okay, we have an empirical dispute. But here's the problem. Here's the problem, that if I just showed that moment that I agreed on. Well, that's not fair. No, but say I said, so I want to move away from the agreement because that's a fascinating actually question that I want to backtrack from because I just dogmatically said, because I could be very, very wrong. But the morphing really helps that like the change, because I mean, partially it's because our perception systems, see this, it's all probably tied in there. Somehow the change from one to the other, like seeing the video of it allows you to pinpoint the place where a two becomes a three much better. If I just showed you one picture, I think you might really, really struggle. You might call a seven. I think there's something also that we don't often think about, which is it's not just about the static image, it's the transformation of the image, or it's not a static shape, it's the transformation of the shape. There's something in the movement that seems to be not just about our perception system, but fundamental to our cognition, like how we think about stuff. Yeah, and that's part of geometry too. And in fact, again, another insight of modern geometry is this idea that maybe we would naively think we're gonna study, I don't know, like Poincare, we're gonna study the three body problem. We're gonna study sort of like three objects in space moving around subject only to the force of each other's gravity, which sounds very simple, right? And if you don't know about this problem, you're probably like, okay, so you just like put it in your computer and see what they do. Well, guess what? That's like a problem that Poincare won a huge prize for like making the first real progress on in the 1880s. And we still don't know that much about it 150 years later. I mean, it's a humongous mystery. You just opened the door and we're gonna walk right in before we return to symmetry. What's the, who's Poincare and what's this conjecture that he came up with? Why is it such a hard problem? Okay, so Poincare, he ends up being a major figure in the book and I didn't even really intend for him to be such a big figure, but he's first and foremost a geometer, right? So he's a mathematician who kind of comes up in late 19th century France at a time when French math is really starting to flower. Actually, I learned a lot. I mean, in math, we're not really trained on our own history. We got a PhD in math, learned about math. So I learned a lot. There's this whole kind of moment where France has just been beaten in the Franco Prussian war. And they're like, oh my God, what did we do wrong? And they were like, we gotta get strong in math like the Germans. We have to be like more like the Germans. So this never happens to us again. So it's very much, it's like the Sputnik moment, like what happens in America in the 50s and 60s with the Soviet Union. This is happening to France and they're trying to kind of like instantly like modernize. That's fascinating that the humans and mathematics are intricately connected to the history of humans. The Cold War is I think fundamental to the way people saw science and math in the Soviet Union. I don't know if that was true in the United States, but certainly it was in the Soviet Union. It definitely was, and I would love to hear more It's funny because I've spoken with him a couple of times, spoken to him a lot offline as well. He really doesn't think he's doing anything new, meaning like he sees himself as very different from maybe like a researcher, but it feels to me like he's creating something totally new. Like that act of understanding and visualizing is as powerful or has the same kind of inkling of power as does the process of proving something. It doesn't have that clear destination, but it's pulling out an insight and creating multiple sets of perspective that arrive at that insight. And to be honest, it's something that I think we haven't quite figured out how to value inside academic mathematics in the same way, and this is a bit older, that I think we haven't quite figured out how to value the development of computational infrastructure. We all have computers as our partners now and people build computers that sort of assist and participate in our mathematics. They build those systems and that's a kind of mathematics too, but not in the traditional form of proving theorems and writing papers. But I think it's coming. Look, I mean, I think, for example, the Institute for Computational Experimental Mathematics at Brown, which is like, it's a NSF funded math institute, very much part of sort of traditional math academia. They did an entire theme semester about visualizing mathematics, looking at the same kind of thing that they would do for like an up and coming research topic. Like that's pretty cool. So I think there really is buy in from the mathematics community to recognize that this kind of stuff is important and counts as part of mathematics, like part of what we're actually here to do. Yeah, I'm hoping to see more and more of that from like MIT faculty, from faculty, from all the top universities in the world. Let me ask you this weird question about the Fields Medal, which is the Nobel Prize in Mathematics. Do you think, since we're talking about computers, there will one day come a time when a computer, an AI system will win a Fields Medal? No. Of course, that's what a human would say. Why not? Is that like, that's like my captcha? That's like the proof that I'm a human? Is that like the lie that I know? Yeah. What is, how does he want me to answer? Is there something interesting to be said about that? Yeah, I mean, I am tremendously interested in what AI can do in pure mathematics. I mean, it's, of course, it's a parochial interest, right? You're like, why am I interested in like, how it can like help feed the world or help solve like real social problems? I'm like, can it do more math? Like, what can I do? We all have our interests, right? But I think it is a really interesting conceptual question. And here too, I think it's important to be kind of historical because it's certainly true that there's lots of things that we used to call research in mathematics that we would now call computation. Tasks that we've now offloaded to machines. Like, you know, in 1890, somebody could be like, here's my PhD thesis. I computed all the invariants of this polynomial ring under the action of some finite group. Doesn't matter what those words mean, just it's like some thing that in 1890 would take a person a year to do and would be a valuable thing that you might wanna know. And it's still a valuable thing that you might wanna know, but now you type a few lines of code in Macaulay or Sage or Magma and you just have it. So we don't think of that as math anymore, even though it's the same thing. What's Macaulay, Sage and Magma? Oh, those are computer algebra programs. So those are like sort of bespoke systems that lots of mathematicians use. That's similar to Maple and... Yeah, oh yeah, so it's similar to Maple and Mathematica, yeah, but a little more specialized, but yeah. It's programs that work with symbols and allow you to do, can you do proofs? Can you do kind of little leaps and proofs? They're not really built for that. And that's a whole other story. But these tools are part of the process of mathematics now. Right, they are now for most mathematicians, I would say, part of the process of mathematics. And so, you know, there's a story I tell in the book, which I'm fascinated by, which is, you know, so far, attempts to get AIs to prove interesting theorems have not done so well. It doesn't mean they can. There's actually a paper I just saw, which has a very nice use of a neural net to find counter examples to conjecture. Somebody said like, well, maybe this is always that. And you can be like, well, let me sort of train an AI to sort of try to find things where that's not true. And it actually succeeded. Now, in this case, if you look at the things that it found, you say like, okay, I mean, these are not famous conjectures. Okay, so like somebody wrote this down, maybe this is so. Looking at what the AI came up with, you're like, you know, I bet if like five grad students had thought about that problem, they wouldn't have come up with that. I mean, when you see it, you're like, okay, that is one of the things you might try if you sort of like put some work into it. Still, it's pretty awesome. But the story I tell in the book, which I'm fascinated by is there is, okay, we're gonna go back to knots. There's a knot called the Conway knot. After John Conway, maybe we'll talk about a very interesting character also. Yeah, it's a small tangent. Somebody I was supposed to talk to and unfortunately he passed away and he's somebody I find as an incredible mathematician, incredible human being. Oh, and I am sorry that you didn't get a chance because having had the chance to talk to him a lot when I was a postdoc, yeah, you missed out. There's no way to sugarcoat it. I'm sorry that you didn't get that chance. Yeah, it is what it is. So knots. Yeah, so there was a question and again, it doesn't matter the technicalities of the question, but it's a question of whether the knot is slice. It has to do with something about what kinds of three dimensional surfaces and four dimensions can be bounded by this knot. But nevermind what it means, it's some question. And it's actually very hard to compute whether a knot is slice or not. And in particular, the question of the Conway knot, whether it was slice or not, was particularly vexed until it was solved just a few years ago by Lisa Piccarillo, who actually, now that I think of it, was here in Austin. I believe she was a grad student at UT Austin at the time. I didn't even realize there was an Austin connection to this story until I started telling it. In fact, I think she's now at MIT, so she's basically following you around. If I remember correctly. The reverse. There's a lot of really interesting richness to this story. One thing about it is her paper was rather, was very short, it was very short and simple. Nine pages of which two were pictures. Very short for like a paper solving a major conjecture. And it really makes you think about what we mean by difficulty in mathematics. Like, do you say, oh, actually the problem wasn't difficult because you could solve it so simply? Or do you say like, well, no, evidently it was difficult because like the world's top topologists, many, you know, worked on it for 20 years and nobody could solve it, so therefore it is difficult. Or is it that we need sort of some new category of things that about which it's difficult to figure out that they're not difficult? I mean, this is the computer science formulation, but the sort of the journey to arrive at the simple answer may be difficult, but once you have the answer, it will then appear simple. And I mean, there might be a large category. I hope there's a large set of such solutions, because, you know, once we stand at the end of the scientific process that we're at the very beginning of, or at least it feels like, I hope there's just simple answers to everything that we'll look and it'll be simple laws that govern the universe, simple explanation of what is consciousness, what is love, is mortality fundamental to life, what's the meaning of life, are humans special or we're just another sort of reflection of all that is beautiful in the universe in terms of like life forms, all of it is life and just has different, when taken from a different perspective is all life can seem more valuable or not, but really it's all part of the same thing. All those will have a nice, like two equations, maybe one equation, but. Why do you think you want those questions to have simple answers? I think just like symmetry and the breaking of symmetry is beautiful somehow. There's something beautiful about simplicity. I think it, what is that? So it's aesthetic. It's aesthetic, yeah. Or, but it's aesthetic in the way that happiness is an aesthetic. Like, why is that so joyful that a simple explanation that governs a large number of cases is really appealing? Even when it's not, like obviously we get a huge amount of trouble with that because oftentimes it doesn't have to be connected with reality or even that explanation could be exceptionally harmful. Most of like the world's history that has, that was governed by hate and violence had a very simple explanation at the core that was used to cause the violence and the hatred. So like we get into trouble with that, but why is that so appealing? And in this nice forms in mathematics, like you look at the Einstein papers, why are those so beautiful? And why is the Andrew Wiles proof of the Fermat's last theorem not quite so beautiful? Like what's beautiful about that story is the human struggle of like the human story of perseverance, of the drama, of not knowing if the proof is correct and ups and downs and all of those kinds of things. That's the interesting part. But the fact that the proof is huge and nobody understands, well, from my outsider's perspective, nobody understands what the heck it is, is not as beautiful as it could have been. I wish it was what Fermat originally said, which is, you know, it's not, it's not small enough to fit in the margins of this page, but maybe if he had like a full page or maybe a couple of post it notes, he would have enough to do the proof. What do you make of, if we could take another of a multitude of tangents, what do you make of Fermat's last theorem? Because the statement, there's a few theorems, there's a few problems that are deemed by the world throughout its history to be exceptionally difficult. And that one in particular is really simple to formulate and really hard to come up with a proof for. And it was like taunted as simple by Fermat himself. Is there something interesting to be said about that X to the N plus Y to the N equals Z to the N for N of three or greater, is there a solution to this? And then how do you go about proving that? Like, how would you try to prove that? And what do you learn from the proof that eventually emerged by Andrew Wiles? Yeah, so right, so to give, let me just say the background, because I don't know if everybody listening knows the story. So, you know, Fermat was an early number theorist, at least sort of an early mathematician, those special adjacent didn't really exist back then. He comes up in the book actually, in the context of a different theorem of his that has to do with testing, whether a number is prime or not. So I write about, he was one of the ones who was salty and like, he would exchange these letters where he and his correspondents would like try to top each other and vex each other with questions and stuff like this. But this particular thing, it's called Fermat's Last Theorem because it's a note he wrote in his copy of the Disquisitiones Arithmetic I. Like he wrote, here's an equation, it has no solutions. I can prove it, but the proof's like a little too long to fit in the margin of this book. He was just like writing a note to himself. Now, let me just say historically, we know that Fermat did not have a proof of this theorem. For a long time, people were like this mysterious proof that was lost, a very romantic story, right? But a fair amount later, he did prove special cases of this theorem and wrote about it, talked to people about the problem. It's very clear from the way that he wrote where he can solve certain examples of this type of equation that he did not know how to do the whole thing. He may have had a deep, simple intuition about how to solve the whole thing that he had at that moment without ever being able to come up with a complete proof. And that intuition maybe lost the time. Maybe, but you're right, that is unknowable. But I think what we can know is that later, he certainly did not think that he had a proof that he was concealing from people. He thought he didn't know how to prove it, and I also think he didn't know how to prove it. Now, I understand the appeal of saying like, wouldn't it be cool if this very simple equation there was like a very simple, clever, wonderful proof that you could do in a page or two. And that would be great, but you know what? There's lots of equations like that that are solved by very clever methods like that, including the special cases that Fermat wrote about, the method of descent, which is like very wonderful and important. But in the end, those are nice things that like you teach in an undergraduate class, and it is what it is, but they're not big. On the other hand, work on the Fermat problem, that's what we like to call it because it's not really his theorem because we don't think he proved it. So, I mean, work on the Fermat problem developed this like incredible richness of number theory that we now live in today. Like, and not, by the way, just Wiles, Andrew Wiles being the person who, together with Richard Taylor, finally proved this theorem. But you know how you have this whole moment that people try to prove this theorem and they fail, and there's a famous false proof by LeMay from the 19th century, where Kummer, in understanding what mistake LeMay had made in this incorrect proof, basically understands something incredible, which is that a thing we know about numbers is that you can factor them and you can factor them uniquely. There's only one way to break a number up into primes. Like if we think of a number like 12, 12 is two times three times two. I had to think about it. Or it's two times two times three, of course you can reorder them. But there's no other way to do it. There's no universe in which 12 is something times five, or in which there's like four threes in it. Nope, 12 is like two twos and a three. Like that is what it is. And that's such a fundamental feature of arithmetic that we almost think of it like God's law. You know what I mean? It has to be that way. That's a really powerful idea. It's so cool that every number is uniquely made up of other numbers. And like made up meaning like there's these like basic atoms that form molecules that get built on top of each other. I love it. I mean, when I teach undergraduate number theory, it's like, it's the first really deep theorem that you prove. What's amazing is the fact that you can factor a number into primes is much easier. Essentially Euclid knew it, although he didn't quite put it in that way. The fact that you can do it at all. What's deep is the fact that there's only one way to do it or however you sort of chop the number up, you end up with the same set of prime factors. And indeed what people finally understood at the end of the 19th century is that if you work in number systems slightly more general than the ones we're used to, which it turns out are relevant to Fermat, all of a sudden this stops being true. Things get, I mean, things get more complicated and now because you were praising simplicity before you were like, it's so beautiful, unique factorization. It's so great. Like, so when I tell you that in more general number systems, there is no unique factorization. Maybe you're like, that's bad. I'm like, no, that's good because there's like a whole new world of phenomena to study that you just can't see through the lens of the numbers that we're used to. So I'm for complication. I'm highly in favor of complication because every complication is like an opportunity for new things to study. And is that the big kind of one of the big insights for you from Andrew Wiles's proof? Is there interesting insights about the process that you used to prove that sort of resonates with you as a mathematician? Is there an interesting concept that emerged from it? Is there interesting human aspects to the proof? Whether there's interesting human aspects to the proof itself is an interesting question. Certainly it has a huge amount of richness. Sort of at its heart is an argument of what's called deformation theory, which was in part created by my PhD advisor, Barry Mazer. Can you speak to what deformation theory is? I can speak to what it's like. How about that? What does it rhyme with? Right, well, the reason that Barry called it deformation theory, I think he's the one who gave it the name. I hope I'm not wrong in saying it's a name. In your book, you have calling different things by the same name as one of the things in the beautiful map that opens the book. Yes, and this is a perfect example. So this is another phrase of Poincare, this like incredible generator of slogans and aphorisms. He said, mathematics is the art of calling different things by the same name. That very thing we do, right? When we're like this triangle and this triangle, come on, they're the same triangle, they're just in a different place, right? So in the same way, it came to be understood that the kinds of objects that you study when you study Fermat's Last Theorem, and let's not even be too careful about what these objects are. I can tell you there are gaol representations in modular forms, but saying those words is not gonna mean so much. But whatever they are, they're things that can be deformed, moved around a little bit. And I think the insight of what Andrew and then Andrew and Richard were able to do was to say something like this. A deformation means moving something just a tiny bit, like an infinitesimal amount. If you really are good at understanding which ways a thing can move in a tiny, tiny, tiny, infinitesimal amount in certain directions, maybe you can piece that information together to understand the whole global space in which it can move. And essentially, their argument comes down to showing that two of those big global spaces are actually the same, the fabled R equals T, part of their proof, which is at the heart of it. And it involves this very careful principle like that. But that being said, what I just said, it's probably not what you're thinking, because what you're thinking when you think, oh, I have a point in space and I move it around like a little tiny bit, you're using your notion of distance that's from calculus. We know what it means for like two points on the real line to be close together. So yet another thing that comes up in the book a lot is this fact that the notion of distance is not given to us by God. We could mean a lot of different things by distance. And just in the English language, we do that all the time. We talk about somebody being a close relative. It doesn't mean they live next door to you, right? It means something else. There's a different notion of distance we have in mind. And there are lots of notions of distances that you could use. In the natural language processing community and AI, there might be some notion of semantic distance or lexical distance between two words. How much do they tend to arise in the same context? That's incredibly important for doing autocomplete and like machine translation and stuff like that. And it doesn't have anything to do with are they next to each other in the dictionary, right? It's a different kind of distance. Okay, ready? In this kind of number theory, there was a crazy distance called the peatic distance. I didn't write about this that much in the book because even though I love it and it's a big part of my research life, it gets a little bit into the weeds, but your listeners are gonna hear about it now. Please. What a normal person says when they say two numbers are close, they say like their difference is like a small number, like seven and eight are close because their difference is one and one's pretty small. If we were to be what's called a two attic number theorist, we'd say, oh, two numbers are close if their difference is a multiple of a large power of two. So like one and 49 are close because their difference is 48 and 48 is a multiple of 16, which is a pretty large power of two. Whereas one and two are pretty far away because the difference between them is one, which is not even a multiple of a power of two at all. That's odd. You wanna know what's really far from one? Like one and 1 64th because their difference is a negative power of two, two to the minus six. So those points are quite, quite far away. Two to the power of a large N would be two, if that's the difference between two numbers then they're close. Yeah, so two to a large power is in this metric a very small number and two to a negative power is a very big number. That's two attic. Okay, I can't even visualize that. It takes practice. It takes practice. If you've ever heard of the Cantor set, it looks kind of like that. So it is crazy that this is good for anything, right? I mean, this just sounds like a definition that someone would make up to torment you. But what's amazing is there's a general theory of distance where you say any definition you make to satisfy certain axioms deserves to be called a distance and this. See, I'm sorry to interrupt. My brain, you broke my brain. Awesome. 10 seconds ago. Cause I'm also starting to map for the two attic case to binary numbers. And you know, cause we romanticize those. So I was trying to. Oh, that's exactly the right way to think of it. I was trying to mess with number, I was trying to see, okay, which ones are close. And then I'm starting to visualize different binary numbers and how they, which ones are close to each other. And I'm not sure. Well, I think there's a. No, no, it's very similar. That's exactly the right way to think of it. It's almost like binary numbers written in reverse. Because in a binary expansion, two numbers are close. A number that's small is like 0.0000 something. Something that's the decimal and it starts with a lot of zeros. In the two attic metric, a binary number is very small if it ends with a lot of zeros and then the decimal point. Gotcha. So it is kind of like binary numbers written backwards is actually, I should have said, that's what I should have said, Lex. That's a very good metaphor. Okay, but so why is that interesting except for the fact that it's a beautiful kind of framework, different kind of framework of which to think about distances. And you're talking about not just the two attic, but the generalization of that. Why is that interesting? Yeah, the NEP. And so that, because that's the kind of deformation that comes up in Wiles's proof, that deformation where moving something a little bit means a little bit in this two attic sense. Trippy, okay. No, I mean, it's such a, I mean, I just get excited talking about it and I just taught this like in the fall semester that. But it like reformulating, why is, so you pick a different measure of distance over which you can talk about very tiny changes and then use that to then prove things about the entire thing. Yes, although, honestly, what I would say, I mean, it's true that we use it to prove things, but I would say we use it to understand things. And then because we understand things better, then we can prove things. But the goal is always the understanding. The goal is not so much to prove things. The goal is not to know what's true or false. I mean, this is something I write about in the book, Near the End. And it's something that, it's a wonderful, wonderful essay by Bill Thurston, kind of one of the great geometers of our time, who unfortunately passed away a few years ago, called on proof and progress in mathematics. And he writes very wonderfully about how, we're not, it's not a theorem factory where you have a production quota. I mean, the point of mathematics is to help humans understand things. And the way we test that is that we're proving new theorems along the way. That's the benchmark, but that's not the goal. Yeah, but just as a kind of, absolutely, but as a tool, it's kind of interesting to approach a problem by saying, how can I change the distance function? Like what, the nature of distance, because that might start to lead to insights for deeper understanding. Like if I were to try to describe human society by a distance, two people are close if they love each other. Right. And then start to do a full analysis on the everybody that lives on earth currently, the 7 billion people. And from that perspective, as opposed to the geographic perspective of distance. And then maybe there could be a bunch of insights about the source of violence, the source of maybe entrepreneurial success or invention or economic success or different systems, communism, capitalism start to, I mean, that's, I guess what economics tries to do, but really saying, okay, let's think outside the box about totally new distance functions that could unlock something profound about the space. Yeah, because think about it. Okay, here's, I mean, now we're gonna talk about AI, which you know a lot more about than I do. So just start laughing uproariously if I say something that's completely wrong. We both know very little relative to what we will know centuries from now. That is a really good humble way to think about it. I like it. Okay, so let's just go for it. Okay, so I think you'll agree with this, that in some sense, what's good about AI is that we can't test any case in advance, the whole point of AI is to make, or one point of it, I guess, is to make good predictions about cases we haven't yet seen. And in some sense, that's always gonna involve some notion of distance, because it's always gonna involve somehow taking a case we haven't seen and saying what cases that we have seen is it close to, is it like, is it somehow an interpolation between. Now, when we do that, in order to talk about things being like other things, implicitly or explicitly, we're invoking some notion of distance, and boy, we better get it right. If you try to do natural language processing and your idea of distance between words is how close they are in the dictionary, when you write them in alphabetical order, you are gonna get pretty bad translations, right? No, the notion of distance has to come from somewhere else. Yeah, that's essentially what neural networks are doing, that's what word embeddings are doing is coming up with. In the case of word embeddings, literally, literally what they are doing is learning a distance. But those are super complicated distance functions, and it's almost nice to think maybe there's a nice transformation that's simple. Sorry, there's a nice formulation of the distance. Again with the simple. So you don't, let me ask you about this. From an understanding perspective, there's the Richard Feynman, maybe attributed to him, but maybe many others, is this idea that if you can't explain something simply that you don't understand it. In how many cases, how often is that true? Do you find there's some profound truth in that? Oh, okay, so you were about to ask, is it true? To which I would say flatly, no. But then you said, you followed that up with, is there some profound truth in it? And I'm like, okay, sure. So there's some truth in it. It's not true. But it's not true. It's just not. That's such a mathematician answer. The truth that is in it is that learning to explain something helps you understand it. But real things are not simple. A few things are, most are not. And to be honest, we don't really know whether Feynman really said that right or something like that is sort of disputed. But I don't think Feynman could have literally believed that whether or not he said it. And he was the kind of guy, I didn't know him, but I've been reading his writing, he liked to sort of say stuff, like stuff that sounded good. You know what I mean? So it's totally strikes me as the kind of thing he could have said because he liked the way saying it made him feel, but also knowing that he didn't like literally mean it. Well, I definitely have a lot of friends and I've talked to a lot of physicists and they do derive joy from believing that they can explain stuff simply or believing it's possible to explain stuff simply, even when the explanation is not actually that simple. Like I've heard people think that the explanation is simple and they do the explanation. And I think it is simple, but it's not capturing the phenomena that we're discussing. It's capturing, it's somehow maps in their mind, but it's taking as a starting point, as an assumption that there's a deep knowledge and a deep understanding that's actually very complicated. And the simplicity is almost like a poem about the more complicated thing as opposed to a distillation. And I love poems, but a poem is not an explanation. Well, some people might disagree with that, but certainly from a mathematical perspective. No poet would disagree with it. No poet would disagree. You don't think there's some things that can only be described imprecisely? As an explanation. I don't think any poet would say their poem is an explanation. They might say it's a description. They might say it's sort of capturing sort of. Well, some people might say the only truth is like music. Not the only truth, but some truths can only be expressed through art. And I mean, that's the whole thing we're talking about religion and myth. And there's some things that are limited cognitive capabilities and the tools of mathematics or the tools of physics are just not going to allow us to capture. Like it's possible consciousness is one of those things. And. Yes, that is definitely possible. But I would even say, look, I mean, consciousness is a thing about which we're still in the dark as to whether there's an explanation we would understand it as an explanation at all. By the way, okay. I got to give yet one more amazing Poincare quote because this guy just never stopped coming up with great quotes that, Paul Erdős, another fellow who appears in the book. And by the way, he thinks about this notion of distance of like personal affinity, kind of like what you're talking about, the kind of social network and that notion of distance that comes from that. So that's something that Paul Erdős. Erdős did? Well, he thought about distances and networks. I guess he didn't probably, he didn't think about the social network. Oh, that's fascinating. And that's how it started that story of Erdős number. Yeah, okay. It's hard to distract. But you know, Erdős was sort of famous for saying, and this is sort of long lines we're saying, he talked about the book, capital T, capital B, the book. And that's the book where God keeps the right proof of every theorem. So when he saw a proof he really liked, it was like really elegant, really simple. Like that's from the book. That's like you found one of the ones that's in the book. He wasn't a religious guy, by the way. He referred to God as the supreme fascist. He was like, but somehow he was like, I don't really believe in God, but I believe in God's book. I mean, it was, but Poincare on the other hand, and by the way, there were other managers. Hilda Hudson is one who comes up in this book. She also kind of saw math. She's one of the people who sort of develops the disease model that we now use, that we use to sort of track pandemics, this SIR model that sort of originally comes from her work with Ronald Ross. But she was also super, super, super devout. And she also sort of on the other side of the religious coin was like, yeah, math is how we communicate with God. She has a great, all these people are incredibly quotable. She says, you know, math is, the truth, the things about mathematics, she's like, they're not the most important of God thoughts, but they're the only ones that we can know precisely. So she's like, this is the one place where we get to sort of see what God's thinking when we do mathematics. Again, not a fan of poetry or music. Some people will say Hendrix is like, some people say chapter one of that book is mathematics, and then chapter two is like classic rock. Right? So like, it's not clear that the... I'm sorry, you just sent me off on a tangent, just imagining like Erdos at a Hendrix concert, like trying to figure out if it was from the book or not. What I was coming to was just to say, but what Poincaré said about this is he's like, you know, if like, this is all worked out in the language of the divine, and if a divine being like came down and told it to us, we wouldn't be able to understand it, so it doesn't matter. So Poincaré was of the view that there were things that were sort of like inhumanly complex, and that was how they really were. Our job is to figure out the things that are not like that. That are not like that. All this talk of primes got me hungry for primes. You wrote a blog post, The Beauty of Bounding Gaps, a huge discovery about prime numbers and what it means for the future of math. Can you tell me about prime numbers? What the heck are those? What are twin primes? What are prime gaps? What are bounding gaps and primes? What are all these things? And what, if anything, or what exactly is beautiful about them? Yeah, so, you know, prime numbers are one of the things that number theorists study the most and have for millennia. They are numbers which can't be factored. And then you say, like, five. And then you're like, wait, I can factor five. Five is five times one. Okay, not like that. That is a factorization. It absolutely is a way of expressing five as a product of two things. But don't you agree there's like something trivial about it? It's something you could do to any number. It doesn't have content the way that if I say that 12 is six times two or 35 is seven times five, I've really done something to it. I've broken up. So those are the kind of factorizations that count. And a number that doesn't have a factorization like that is called prime, except, historical side note, one, which at some times in mathematical history has been deemed to be a prime, but currently is not. And I think that's for the best. But I bring it up only because sometimes people think that, you know, these definitions are kind of, if we think about them hard enough, we can figure out which definition is true. No. There's just an artifact of mathematics. So it's a question of which definition is best for us, for our purposes. Well, those edge cases are weird, right? So it can't be, it doesn't count when you use yourself as a number or one as part of the factorization or as the entirety of the factorization. So you somehow get to the meat of the number by factorizing it. And that seems to get to the core of all of mathematics. Yeah, you take any number and you factorize it until you can factorize no more. And what you have left is some big pile of primes. I mean, by definition, when you can't factor anymore, when you're done, when you can't break the numbers up anymore, what's left must be prime. You know, 12 breaks into two and two and three. So these numbers are the atoms, the building blocks of all numbers. And there's a lot we know about them, or there's much more that we don't know about them. I'll tell you the first few. There's two, three, five, seven, 11. By the way, they're all gonna be odd from then on because if they were even, I could factor out two out of them. But it's not all the odd numbers. Nine isn't prime because it's three times three. 15 isn't prime because it's three times five, but 13 is. Where were we? Two, three, five, seven, 11, 13, 17, 19. Not 21, but 23 is, et cetera, et cetera. Okay, so you could go on. How high could you go if we were just sitting here? By the way, your own brain. If continuous, without interruption, would you be able to go over 100? I think so. There's always those ones that trip people up. There's a famous one, the Grotendeek prime 57, like sort of Alexander Grotendeek, the great algebraic geometer was sort of giving some lecture involving a choice of a prime in general. And somebody said, can't you just choose a prime? And he said, okay, 57, which is in fact not prime. It's three times 19. Oh, damn. But it was like, I promise you in some circles it's a funny story. But there's a humor in it. Yes, I would say over 100, I definitely don't remember. Like 107, I think, I'm not sure. Okay, like, I mean. So is there a category of like fake primes that are easily mistaken to be prime? Like 57, I wonder. Yeah, so I would say 57 and 51 are definitely like prime offenders. Oh, I didn't do that on purpose. Oh, well done. Didn't do it on purpose. Anyway, they're definitely ones that people, or 91 is another classic, seven times 13. It really feels kind of prime, doesn't it? But it is not. Yeah. But there's also, by the way, but there's also an actual notion of pseudo prime, which is a thing with a formal definition, which is not a psychological thing. It is a prime which passes a primality test devised by Fermat, which is a very good test, which if a number fails this test, it's definitely not prime. And so there was some hope that, oh, maybe if a number passes the test, then it definitely is prime. That would give a very simple criterion for primality. Unfortunately, it's only perfect in one direction. So there are numbers, I want to say 341 is the smallest, which pass the test but are not prime, 341. Is this test easily explainable or no? Yes, actually. Ready, let me give you the simplest version of it. You can dress it up a little bit, but here's the basic idea. I take the number, the mystery number, I raise two to that power. So let's say your mystery number is six. Are you sorry you asked me? Are you ready? No, you're breaking my brain again, but yes. Let's do it. We're going to do a live demonstration. Let's say your number is six. So I'm going to raise two to the sixth power. Okay, so if I were working on it, I'd be like that's two cubes squared, so that's eight times eight, so that's 64. Now we're going to divide by six, but I don't actually care what the quotient is, only the remainder. So let's see, 64 divided by six is, well, there's a quotient of 10, but the remainder is four. So you failed because the answer has to be two. For any prime, let's do it with five, which is prime. Two to the fifth is 32. Divide 32 by five, and you get six with a remainder of two. With a remainder of two, yeah. For seven, two to the seventh is 128. Divide that by seven, and let's see, I think that's seven times 14, is that right? No. Seven times 18 is 126 with a remainder of two, right? 128 is a multiple of seven plus two. So if that remainder is not two, then it's definitely not prime. And then if it is, it's likely a prime, but not for sure. It's likely a prime, but not for sure. And there's actually a beautiful geometric proof which is in the book, actually. That's like one of the most granular parts of the book because it's such a beautiful proof, I couldn't not give it. So you draw a lot of like opal and pearl necklaces and spin them. That's kind of the geometric nature of this proof of Fermat's Little Theorem. So yeah, so with pseudo primes, there are primes that are kind of faking it. They pass that test, but there are numbers that are faking it that pass that test, but are not actually prime. But the point is, there are many, many, many theorems about prime numbers. There's a bunch of questions to ask. Is there an infinite number of primes? Can we say something about the gap between primes as the numbers grow larger and larger and larger and so on? Yeah, it's a perfect example of your desire for simplicity in all things. You know what would be really simple? If there was only finitely many primes and then there would be this finite set of atoms that all numbers would be built up. That would be very simple and good in certain ways, but it's completely false. And number theory would be totally different if that were the case. It's just not true. In fact, this is something else that Euclid knew. So this is a very, very old fact, like much before, long before we've had anything like modern number theory. The primes are infinite. The primes that there are, right. There's an infinite number of primes. So what about the gaps between the primes? Right, so one thing that people recognized and really thought about a lot is that the primes, on average, seem to get farther and farther apart as they get bigger and bigger. In other words, it's less and less common. Like I already told you of the first 10 numbers, two, three, five, seven, four of them are prime. That's a lot, 40%. If I looked at 10 digit numbers, no way would 40% of those be prime. Being prime would be a lot rarer. In some sense, because there's a lot more things for them to be divisible by. That's one way of thinking of it. It's a lot more possible for there to be a factorization because there's a lot of things you can try to factor out of it. As the numbers get bigger and bigger, primality gets rarer and rarer, and the extent to which that's the case, that's pretty well understood. But then you can ask more fine grained questions, and here is one. A twin prime is a pair of primes that are two apart, like three and five, or like 11 and 13, or like 17 and 19. And one thing we still don't know is are there infinitely many of those? We know on average, they get farther and farther apart, but that doesn't mean there couldn't be occasional folks that come close together. And indeed, we think that there are. And one interesting question, I mean, this is, because I think you might say, well, how could one possibly have a right to have an opinion about something like that? We don't have any way of describing a process that makes primes. Sure, you can look at your computer and see a lot of them, but the fact that there's a lot, why is that evidence that there's infinitely many, right? Maybe I can go on the computer and find 10 million. Well, 10 million is pretty far from infinity, right? So how is that evidence? There's a lot of things. There's like a lot more than 10 million atoms. That doesn't mean there's infinitely many atoms in the universe, right? I mean, on most people's physical theories, there's probably not, as I understand it. Okay, so why would we think this? The answer is that it turns out to be like incredibly productive and enlightening to think about primes as if they were random numbers, as if they were randomly distributed according to a certain law. Now they're not, they're not random. There's no chance involved. There it's completely deterministic whether a number is prime or not. And yet it just turns out to be phenomenally useful in mathematics to say, even if something is governed by a deterministic law, let's just pretend it wasn't. Let's just pretend that they were produced by some random process and see if the behavior is roughly the same. And if it's not, maybe change the random process, maybe make the randomness a little bit different and tweak it and see if you can find a random process that matches the behavior we see. And then maybe you predict that other behaviors of the system are like that of the random process. And so that's kind of like, it's funny because I think when you talk to people at the twin prime conjecture, people think you're saying, wow, there's like some deep structure there that like makes those primes be like close together again and again. And no, it's the opposite of deep structure. What we say when we say we believe the twin prime conjecture is that we believe the primes are like sort of strewn around pretty randomly. And if they were, then by chance, you would expect there to be infinitely many twin primes. And we're saying, yeah, we expect them to behave just like they would if they were random dirt. The fascinating parallel here is, I just got a chance to talk to Sam Harris and he uses the prime numbers as an example. Often, I don't know if you're familiar with who Sam is. He uses that as an example of there being no free will. Wait, where does he get this? Well, he just uses as an example of, it might seem like this is a random number generator, but it's all like formally defined. So if we keep getting more and more primes, then like that might feel like a new discovery and that might feel like a new experience, but it's not. It was always written in the cards. But it's funny that you say that because a lot of people think of like randomness, the fundamental randomness within the nature of reality might be the source of something that we experience as free will. And you're saying it's like useful to look at prime numbers as a random process in order to prove stuff about them. But fundamentally, of course, it's not a random process. Well, not in order to prove some stuff about them so much as to figure out what we expect to be true and then try to prove that. Because here's what you don't want to do. Try really hard to prove something that's false. That makes it really hard to prove the thing if it's false. So you certainly want to have some heuristic ways of guessing, making good guesses about what's true. So yeah, here's what I would say. You're going to be imaginary Sam Harris now. Like you are talking about prime numbers and you are like, but prime numbers are completely deterministic. And I'm saying like, well, but let's treat them like a random process. And then you say, but you're just saying something that's not true. They're not a random process, they're deterministic. And I'm like, okay, great. You hold to your insistence that it's not a random process. Meanwhile, I'm generating insight about the primes that you're not because I'm willing to sort of pretend that there's something that they're not in order to understand what's going on. Yeah, so it doesn't matter what the reality is. What matters is what framework of thought results in the maximum number of insights. Yeah, because I feel, look, I'm sorry, but I feel like you have more insights about people. If you think of them as like beings that have wants and needs and desires and do stuff on purpose, even if that's not true, you still understand better what's going on by treating them in that way. Don't you find, look, when you work on machine learning, don't you find yourself sort of talking about what the machine is trying to do in a certain instance? Do you not find yourself drawn to that language? Well, it knows this, it's trying to do that, it's learning that. I'm certainly drawn to that language to the point where I receive quite a bit of criticisms for it because I, you know, like. Oh, I'm on your side, man. So especially in robotics, I don't know why, but robotics people don't like to name their robots. They certainly don't like to gender their robots because the moment you gender a robot, you start to anthropomorphize. If you say he or she, you start to, in your mind, construct like a life story. In your mind, you can't help it. There's like, you create like a humorous story to this person. You start to, this person, this robot, you start to project your own. But I think that's what we do to each other. And I think that's actually really useful for the engineering process, especially for human robot interaction. And yes, for machine learning systems, for helping you build an intuition about a particular problem. It's almost like asking this question, you know, when a machine learning system fails in a particular edge case, asking like, what were you thinking about? Like, like asking, like almost like when you're talking about to a child who just did something bad, you want to understand like what was, how did they see the world? Maybe there's a totally new, maybe you're the one that's thinking about the world incorrectly. And yeah, that anthropomorphization process, I think is ultimately good for insight. And the same is, I agree with you. I tend to believe about free will as well. Let me ask you a ridiculous question, if it's okay. Of course. I've just recently, most people go on like rabbit hole, like YouTube things. And I went on a rabbit hole often do of Wikipedia. And I found a page on finiteism, ultra finiteism and intuitionism or into, I forget what it's called. Yeah, intuitionism. Intuitionism. That seemed pretty, pretty interesting. I have it on my to do list actually like look into like, is there people who like formally attract, like real mathematicians are trying to argue for this. But the belief there, I think, let's say finiteism that infinity is fake. Meaning, infinity might be like a useful hack for certain, like a useful tool in mathematics, but it really gets us into trouble because there's no infinity in the real world. Maybe I'm sort of not expressing that fully correctly, but basically saying like there's things that once you add into mathematics, things that are not provably within the physical world, you're starting to inject to corrupt your framework of reason. What do you think about that? I mean, I think, okay, so first of all, I'm not an expert and I couldn't even tell you what the difference is between those three terms, finiteism, ultra finiteism and intuitionism, although I know they're related and I tend to associate them with the Netherlands in the 1930s. Okay, I'll tell you, can I just quickly comment because I read the Wikipedia page. The difference in ultra. That's like the ultimate sentence of the modern age. Can I just comment because I read the Wikipedia page. That sums up our moment. Bro, I'm basically an expert. Ultra finiteism. So, finiteism says that the only infinity you're allowed to have is that the natural numbers are infinite. So, like those numbers are infinite. So, like one, two, three, four, five, the integers are infinite. The ultra finiteism says, nope, even that infinity is fake. I'll bet ultra finiteism came second. I'll bet it's like when there's like a hardcore scene and then one guy's like, oh, now there's a lot of people in the scene. I have to find a way to be more hardcore than the hardcore people. It's all back to the emo, Doc. Okay, so is there any, are you ever, because I'm often uncomfortable with infinity, like psychologically. I have trouble when that sneaks in there. It's because it works so damn well, I get a little suspicious, because it could be almost like a crutch or an oversimplification that's missing something profound about reality. Well, so first of all, okay, if you say like, is there like a serious way of doing mathematics that doesn't really treat infinity as a real thing or maybe it's kind of agnostic and it's like, I'm not really gonna make a firm statement about whether it's a real thing or not. Yeah, that's called most of the history of mathematics. So it's only after Cantor that we really are sort of, okay, we're gonna like have a notion of like the cardinality of an infinite set and like do something that you might call like the modern theory of infinity. That said, obviously everybody was drawn to this notion and no, not everybody was comfortable with it. Look, I mean, this is what happens with Newton. I mean, so Newton understands that to talk about tangents and to talk about instantaneous velocity, he has to do something that we would now call taking a limit, right? The fabled dy over dx, if you sort of go back to your calculus class, for those who have taken calculus and remember this mysterious thing. And you know, what is it? What is it? Well, he'd say like, well, it's like, you sort of divide the length of this line segment by the length of this other line segment. And then you make them a little shorter and you divide again. And then you make them a little shorter and you divide again. And then you just keep on doing that until they're like infinitely short and then you divide them again. These quantities that are like, they're not zero, but they're also smaller than any actual number, these infinitesimals. Well, people were queasy about it and they weren't wrong to be queasy about it, right? From a modern perspective, it was not really well formed. There's this very famous critique of Newton by Bishop Berkeley, where he says like, what these things you define, like, you know, they're not zero, but they're smaller than any number. Are they the ghosts of departed quantities? That was this like ultra burn of Newton. And on the one hand, he was right. It wasn't really rigorous by modern standards. On the other hand, like Newton was out there doing calculus and other people were not, right? It works, it works. I think a sort of intuitionist view, for instance, I would say would express serious doubt. And by the way, it's not just infinity. It's like saying, I think we would express serious doubt that like the real numbers exist. Now, most people are comfortable with the real numbers. Well, computer scientists with floating point number, I mean, floating point arithmetic. That's a great point, actually. I think in some sense, this flavor of doing math, saying we shouldn't talk about things that we cannot specify in a finite amount of time, there's something very computational in flavor about that. And it's probably not a coincidence that it becomes popular in the 30s and 40s, which is also like kind of like the dawn of ideas about formal computation, right? You probably know the timeline better than I do. Sorry, what becomes popular? These ideas that maybe we should be doing math in this more restrictive way where even a thing that, because look, the origin of all this is like, number represents a magnitude, like the length of a line. So I mean, the idea that there's a continuum, there's sort of like, it's pretty old, but just because something is old doesn't mean we can't reject it if we want to. Well, a lot of the fundamental ideas in computer science, when you talk about the complexity of problems, to Turing himself, they rely on an infinity as well. The ideas that kind of challenge that, the whole space of machine learning, I would say, challenges that. It's almost like the engineering approach to things, like the floating point arithmetic. The other one that, back to John Conway, that challenges this idea, I mean, maybe to tie in the ideas of deformation theory and limits to infinity is this idea of cellular automata with John Conway looking at the game of life, Stephen Wolfram's work, that I've been a big fan of for a while, cellular automata. I was wondering if you have, if you have ever encountered these kinds of objects, you ever looked at them as a mathematician, where you have very simple rules of tiny little objects that when taken as a whole create incredible complexities, but are very difficult to analyze, very difficult to make sense of, even though the one individual object, one part, it's like what we were saying about Andrew Wiles, you can look at the deformation of a small piece to tell you about the whole. It feels like with cellular automata or any kind of complex systems, it's often very difficult to say something about the whole thing, even when you can precisely describe the operation of the local neighborhoods. Yeah, I mean, I love that subject. I haven't really done research on it myself. I've played around with it. I'll send you a fun blog post I wrote where I made some cool texture patterns from cellular automata that I, but. And those are really always compelling is like you create simple rules and they create some beautiful textures. It doesn't make any sense. Actually, did you see, there was a great paper. I don't know if you saw this, like a machine learning paper. Yes. I don't know if you saw the one I'm talking about where they were like learning the texture as like let's try to like reverse engineer and like learn a cellular automaton that can reduce texture that looks like this from the images. Very cool. And as you say, the thing you said is I feel the same way when I read machine learning paper is that what's especially interesting is the cases where it doesn't work. Like what does it do when it doesn't do the thing that you tried to train it to do? That's extremely interesting. Yeah, yeah, that was a cool paper. So yeah, so let's start with the game of life. Let's start with, or let's start with John Conway. So Conway. So yeah, so let's start with John Conway again. Just, I don't know, from my outsider's perspective, there's not many mathematicians that stand out throughout the history of the 20th century. And he's one of them. I feel like he's not sufficiently recognized. I think he's pretty recognized. Okay, well. I mean, he was a full professor at Princeton for most of his life. He was sort of certainly at the pinnacle of. Yeah, but I found myself every time I talk about Conway and how excited I am about him, I have to constantly explain to people who he is. And that's always a sad sign to me. But that's probably true for a lot of mathematicians. I was about to say, I feel like you have a very elevated idea of how famous. This is what happens when you grow up in the Soviet Union or you think the mathematicians are like very, very famous. Yeah, but I'm not actually so convinced at a tiny tangent that that shouldn't be so. I mean, there's, it's not obvious to me that that's one of the, like if I were to analyze American society, that perhaps elevating mathematical and scientific thinking to a little bit higher level would benefit the society. Well, both in discovering the beauty of what it is to be human and for actually creating cool technology, better iPhones. But anyway, John Conway. Yeah, and Conway is such a perfect example of somebody whose humanity was, and his personality was like wound up with his mathematics, right? And so it's not, sometimes I think people who are outside the field think of mathematics as this kind of like cold thing that you do separate from your existence as a human being. No way, your personality is in there, just as it would be in like a novel you wrote or a painting you painted or just like the way you walk down the street. Like it's in there, it's you doing it. And Conway was certainly a singular personality. I think anybody would say that he was playful, like everything was a game to him. Now, what you might think I'm gonna say, and it's true is that he sort of was very playful in his way of doing mathematics, but it's also true, it went both ways. He also sort of made mathematics out of games. He like looked at, he was a constant inventor of games or like crazy names. And then he would sort of analyze those games mathematically to the point that he, and then later collaborating with Knuth like, created this number system, the serial numbers in which actually each number is a game. There's a wonderful book about this called, I mean, there are his own books. And then there's like a book that he wrote with Berlekamp and Guy called Winning Ways, which is such a rich source of ideas. And he too kind of has his own crazy number system in which by the way, there are these infinitesimals, the ghosts of departed quantities. They're in there now, not as ghosts, but as like certain kind of two player games. So, he was a guy, so I knew him when I was a postdoc about how it was in the Soviet Union. I mean, there was, and we'll talk about the Olympiad. I just remember that there was this feeling like the world hung in a balance and you could save the world with the tools of science. And mathematics was like the superpower that fuels science. And so like people were seen as, you know, people in America often idolize athletes, but ultimately the best athletes in the world, they just throw a ball into a basket. So like there's not, what people really enjoy about sports, I love sports, is like excellence at the highest level. But when you take that with mathematics and science, people also enjoyed excellence in science and mathematics in the Soviet Union, but there's an extra sense that that excellence would lead to a better world. So that created all the usual things you think about with the Olympics, which is like extreme competitiveness. But it also created this sense that in the modern era in America, somebody like Elon Musk, whatever you think of him, like Jeff Bezos, those folks, they inspire the possibility that one person or a group of smart people can change the world. Like not just be good at what they do, but actually change the world. Mathematics was at the core of that. I don't know, there's a romanticism around it too. Like when you read books about in America, people romanticize certain things like baseball, for example. There's like these beautiful poetic writing about the game of baseball. The same was the feeling with mathematics and science in the Soviet Union, and it was in the air. Everybody was forced to take high level mathematics courses. Like you took a lot of math, you took a lot of science and a lot of like really rigorous literature. Like the level of education in Russia, this could be true in China, I'm not sure, in a lot of countries is in whatever that's called, it's K to 12 in America, but like young people education. The level they were challenged to learn at is incredible. It's like America falls far behind, I would say. America then quickly catches up and then exceeds everybody else as you start approaching the end of high school to college. Like the university system in the United States arguably is the best in the world. But like what we challenge everybody, it's not just like the good, the A students, but everybody to learn in the Soviet Union was fascinating. I think I'm gonna pick up on something you said. I think you would love a book called Dual at Dawn by Amir Alexander, which I think some of the things you're responding to and what I wrote, I think I first got turned on to by Amir's work, he's a historian of math. And he writes about the story of Everest to Galois, which is a story that's well known to all mathematicians, this kind of like very, very romantic figure who he really sort of like begins the development of this or this theory of groups that I mentioned earlier, this general theory of symmetries and then dies in a duel in his early 20s, like all this stuff, mostly unpublished. It's a very, very romantic story that we all learn. And much of it is true, but Alexander really lays out just how much the way people thought about math in those times in the early 19th century was wound up with, as you say, romanticism. I mean, that's when the romantic movement takes place and he really outlines how people were predisposed to think about mathematics in that way because they thought about poetry that way and they thought about music that way. It was the mood of the era to think about we're reaching for the transcendent, we're sort of reaching for sort of direct contact with the divine. And part of the reason that we think of Gawa that way was because Gawa himself was a creature of that era and he romanticized himself. I mean, now we know he wrote lots of letters and he was kind of like, I mean, in modern terms, we would say he was extremely emo. Like we wrote all these letters about his like florid feelings and like the fire within him about the mathematics. And so it's just as you say that the math history touches human history. They're never separate because math is made of people. I mean, that's what, it's people who do it and we're human beings doing it and we do it within whatever community we're in and we do it affected by the mores of the society around us. So the French, the Germans and Poincare. Yes, okay, so back to Poincare. So he's, you know, it's funny. This book is filled with kind of mathematical characters who often are kind of peevish or get into feuds or sort of have like weird enthusiasms because those people are fun to write about and they sort of like say very salty things. Poincare is actually none of this. As far as I can tell, he was an extremely normal dude who didn't get into fights with people and everybody liked him and he was like pretty personally modest and he had very regular habits. You know what I mean? He did math for like four hours in the morning and four hours in the evening and that was it. Like he had his schedule. I actually, it was like, I still am feeling like somebody's gonna tell me now that the book is out, like, oh, didn't you know about this like incredibly sordid episode? As far as I could tell, a completely normal guy. But he just kind of, in many ways, creates the geometric world in which we live and his first really big success is this prize paper he writes for this prize offered by the King of Sweden for the study of the three body problem. The study of what we can say about, yeah, three astronomical objects moving in what you might think would be this very simple way. Nothing's going on except gravity. So what's the three body problem? Why is it a problem? So the problem is to understand when this motion is stable and when it's not. So stable meaning they would sort of like end up in some kind of periodic orbit. Or I guess it would mean, sorry, stable would mean they never sort of fly off far apart from each other. And unstable would mean like eventually they fly apart. So understanding two bodies is much easier. Yes, exactly. When you have the third wheel is always a problem. This is what Newton knew. Two bodies, they sort of orbit each other in some kind of either in an ellipse, which is the stable case. You know, that's what the planets do that we know. Or one travels on a hyperbola around the other. That's the unstable case. It sort of like zooms in from far away, sort of like whips around the heavier thing and like zooms out. Those are basically the two options. So it's a very simple and easy to classify story. With three bodies, just the small switch from two to three, it's a complete zoo. It's the first, what we would say now is it's the first example of what's called chaotic dynamics, where the stable solutions and the unstable solutions, they're kind of like wound in among each other. And a very, very, very tiny change in the initial conditions can make the longterm behavior of the system completely different. So Poincare was the first to recognize that that phenomenon even existed. What about the conjecture that carries his name? Right, so he also was one of the pioneers of taking geometry, which until that point had been largely the study of two and three dimensional objects, because that's like what we see, right? That's those are the objects we interact with. He developed the subject we now called topology. He called it analysis situs. He was a very well spoken guy with a lot of slogans, but that name did not, you can see why that name did not catch on. So now it's called topology now. Sorry, what was it called before? Analysis situs, which I guess sort of roughly means like the analysis of location or something like that. Like it's a Latin phrase. Partly because he understood that even to understand stuff that's going on in our physical world, you have to study higher dimensional spaces. How does this work? And this is kind of like where my brain went to it because you were talking about not just where things are, but what their path is, how they're moving when we were talking about the path from two to three. He understood that if you wanna study three bodies moving in space, well, each body, it has a location where it is. So it has an X coordinate, a Y coordinate, a Z coordinate, right? I can specify a point in space by giving you three numbers, but it also at each moment has a velocity. So it turns out that really to understand what's going on, you can't think of it as a point or you could, but it's better not to think of it as a point in three dimensional space that's moving. It's better to think of it as a point in six dimensional space where the coordinates are where is it and what's its velocity right now. That's a higher dimensional space called phase space. And if you haven't thought about this before, I admit that it's a little bit mind bending, but what he needed then was a geometry that was flexible enough, not just to talk about two dimensional spaces or three dimensional spaces, but any dimensional space. So the sort of famous first line of this paper where he introduces analysis of Cetus is no one doubts nowadays that the geometry of n dimensional space is an actually existing thing, right? I think that maybe that had been controversial. And he's saying like, look, let's face it, just because it's not physical doesn't mean it's not there. It doesn't mean we shouldn't study it. Interesting. He wasn't jumping to the physical interpretation. Like it can be real, even if it's not perceivable to the human cognition. I think that's right. I think, don't get me wrong, Poincare never strays far from physics. and I knew him at Princeton and our research overlapped in some ways. Now it was on stuff that he had worked on many years before. The stuff I was working on kind of connected with stuff in group theory, which somehow seems to keep coming up. And so I often would like sort of ask him a question. I would sort of come upon him in the common room and I would ask him a question about something. And just anytime you turned him on, you know what I mean? You sort of asked the question, it was just like turning a knob and winding him up and he would just go and you would get a response that was like so rich and went so many places and taught you so much. And usually had nothing to do with your question. Usually your question was just a prompt to him. You couldn't count on actually getting the question answered. Yeah, those brilliant, curious minds even at that age. Yeah, it was definitely a huge loss. But on his game of life, which was I think he developed in the 70s as almost like a side thing, a fun little experiment. His game of life is this, it's a very simple algorithm. It's not really a game per se in the sense of the kinds of games that he liked where people played against each other. But essentially it's a game that you play with marking little squares on the sheet of graph paper. And in the 70s, I think he was like literally doing it with like a pen on graph paper. You have some configuration of squares. Some of the squares in the graph paper are filled in, some are not. And there's a rule, a single rule that tells you at the next stage, which squares are filled in and which squares are not. Sometimes an empty square gets filled in, that's called birth. Sometimes a square that's filled in gets erased, that's called death. And there's rules for which squares are born and which squares die. The rule is very simple. You can write it on one line. And then the great miracle is that you can start from some very innocent looking little small set of boxes and get these results of incredible richness. And of course, nowadays you don't do it on paper. Nowadays you do it in a computer. There's actually a great iPad app called Golly, which I really like that has like Conway's original rule and like, gosh, like hundreds of other variants and it's a lightning fast. So you can just be like, I wanna see 10,000 generations of this rule play out like faster than your eye can even follow. And it's like amazing. So I highly recommend it if this is at all intriguing to you getting Golly on your iOS device. And you can do this kind of process, which I really enjoy doing, which is almost from like putting a Darwin hat on or a biologist hat on and doing analysis of a higher level of abstraction, like the organisms that spring up. Cause there's different kinds of organisms. Like you can think of them as species and they interact with each other. They can, there's gliders, they shoot different, there's like things that can travel around. There's things that can, glider guns that can generate those gliders. You can use the same kind of language as you would about describing a biological system. So it's a wonderful laboratory and it's kind of a rebuke to someone who doesn't think that like very, very rich, complex structure can come from very simple underlying laws. Like it definitely can. Now, here's what's interesting. If you just pick like some random rule, you wouldn't get interesting complexity. I think that's one of the most interesting things of these, one of these most interesting features of this whole subject, that the rules have to be tuned just right. Like a sort of typical rule set doesn't generate any kind of interesting behavior. But some do. And I don't think we have a clear way of understanding which do and which don't. Maybe Steven thinks he does, I don't know. No, no, it's a giant mystery where Steven Wolfram did is, now there's a whole interesting aspect to the fact that he's a little bit of an outcast in the mathematics and physics community because he's so focused on a particular, his particular work. I think if you put ego aside, which I think unfairly some people are not able to look beyond, I think his work is actually quite brilliant. But what he did is exactly this process of Darwin like exploration. He's taking these very simple ideas and writing a thousand page book on them, meaning like, let's play around with this thing. Let's see. And can we figure anything out? Spoiler alert, no, we can't. In fact, he does a challenge. I think it's like rule 30 challenge, which is quite interesting, just simply for machine learning people, for mathematics people, is can you predict the middle column? For his, it's a 1D cellular automata. Can you, generally speaking, can you predict anything about how a particular rule will evolve just in the future? Very simple. Just looking at one particular part of the world, just zooming in on that part, 100 steps ahead, can you predict something? And the challenge is to do that kind of prediction so far as nobody's come up with an answer. But the point is like, we can't. We don't have tools or maybe it's impossible or, I mean, he has these kind of laws of irreducibility that he refers to, but it's poetry. It's like, we can't prove these things. It seems like we can't. That's the basic. It almost sounds like ancient mathematics or something like that, where you're like, the gods will not allow us to predict the cellular automata. But that's fascinating that we can't. I'm not sure what to make of it. And there's power to calling this particular set of rules game of life as Conway did, because not exactly sure, but I think he had a sense that there's some core ideas here that are fundamental to life, to complex systems, to the way life emerge on earth. I'm not sure I think Conway thought that. It's something that, I mean, Conway always had a rather ambivalent relationship with the game of life because I think he saw it as, it was certainly the thing he was most famous for in the outside world. And I think that he, his view, which is correct, is that he had done things that were much deeper mathematically than that. And I think it always aggrieved him a bit that he was the game of life guy when he proved all these wonderful theorems and created all these wonderful games, created the serial numbers. I mean, he was a very tireless guy who just did an incredibly variegated array of stuff. So he was exactly the kind of person who you would never want to reduce to one achievement. You know what I mean? Let me ask you about group theory. You mentioned it a few times. What is group theory? What is an idea from group theory that you find beautiful? Well, so I would say group theory sort of starts as the general theory of symmetries, that people looked at different kinds of things and said, as we said, oh, it could have, maybe all there is is symmetry from left to right, like a human being, right? That's roughly bilaterally symmetric, as we say. So there's two symmetries. And then you're like, well, wait, didn't I say there's just one, there's just left to right? Well, we always count the symmetry of doing nothing. We always count the symmetry that's like there's flip and don't flip. Those are the two configurations that you can be in. So there's two. You know, something like a rectangle is bilaterally symmetric. You can flip it left to right, but you can also flip it top to bottom. So there's actually four symmetries. There's do nothing, flip it left to right and flip it top to bottom or do both of those things. And then a square, there's even more, because now you can rotate it. You can rotate it by 90 degrees. So you can't do that. That's not a symmetry of the rectangle. If you try to rotate it 90 degrees, you get a rectangle oriented in a different way. So a person has two symmetries, a rectangle four, a square eight, different kinds of shapes have different numbers of symmetries. And the real observation is that that's just not like a set of things, they can be combined. You do one symmetry, then you do another. The result of that is some third symmetry. So a group really abstracts away this notion of saying, it's just some collection of transformations you can do to a thing where you combine any two of them to get a third. So, you know, a place where this comes up in computer science is in sorting, because the ways of permuting a set, the ways of taking sort of some set of things you have on the table and putting them in a different order, shuffling a deck of cards, for instance, those are the symmetries of the deck. And there's a lot of them. There's not two, there's not four, there's not eight. Think about how many different orders the deck of card can be in. Each one of those is the result of applying a symmetry to the original deck. So a shuffle is a symmetry, right? You're reordering the cards. If I shuffle and then you shuffle, the result is some other kind of thing. You might call it a double shuffle, which is a more complicated symmetry. So group theory is kind of the study of the general abstract world that encompasses all these kinds of things. But then of course, like lots of things that are way more complicated than that. Like infinite groups of symmetries, for instance. So they can be infinite, huh? Oh yeah. Okay. Well, okay, ready? Think about the symmetries of the line. You're like, okay, I can reflect it left to right, you know, around the origin. Okay, but I could also reflect it left to right, grabbing somewhere else, like at one or two or pi or anywhere. Or I could just slide it some distance. That's a symmetry. Slide it five units over. So there's clearly infinitely many symmetries of the line. That's an example of an infinite group of symmetries. Is it possible to say something that kind of captivates, keeps being brought up by physicists, which is gauge theory, gauge symmetry, as one of the more complicated type of symmetries? Is there an easy explanation of what the heck it is? Is that something that comes up on your mind at all? Well, I'm not a mathematical physicist, but I can say this. It is certainly true that it has been a very useful notion in physics to try to say like, what are the symmetry groups of the world? Like what are the symmetries under which things don't change, right? So we just, I think we talked a little bit earlier about it should be a basic principle that a theorem that's true here is also true over there. And same for a physical law, right? I mean, if gravity is like this over here, it should also be like this over there. Okay, what that's saying is we think translation in space should be a symmetry. All the laws of physics should be unchanged if the symmetry we have in mind is a very simple one like translation. And so then there becomes a question, like what are the symmetries of the actual world with its physical laws? And one way of thinking, this isn't oversimplification, but like one way of thinking of this big shift from before Einstein to after is that we just changed our idea about what the fundamental group of symmetries were. So that things like the Lorenz contraction, things like these bizarre relativistic phenomenon or Lorenz would have said, oh, to make this work, we need a thing to change its shape if it's moving nearly the speed of light. Well, under the new framework, it's much better. You say, oh, no, it wasn't changing its shape. You were just wrong about what counted as a symmetry. Now that we have this new group, the so called Lorenz group, now that we understand what the symmetries really are, we see it was just an illusion that the thing was changing its shape. Yeah, so you can then describe the sameness of things under this weirdness that is general relativity, for example. Yeah, yeah, still, I wish there was a simpler explanation of like exact, I mean, gauge symmetries, pretty simple general concept about rulers being deformed. I've actually just personally been on a search, not a very rigorous or aggressive search, but for something I personally enjoy, which is taking complicated concepts and finding the sort of minimal example that I can play around with, especially programmatically. That's great, I mean, this is what we try to train our students to do, right? I mean, in class, this is exactly what, this is like best pedagogical practice. I do hope there's simple explanation, especially like I've in my sort of drunk random walk, drunk walk, whatever that's called, sometimes stumble into the world of topology and like quickly, like, you know when you go into a party and you realize this is not the right party for me? It's, so whenever I go into topology, it's like so much math everywhere. I don't even know what, it feels like this is me like being a hater, I think there's way too much math. Like there are two, the cool kids who just want to have, like everything is expressed through math. Because they're actually afraid to express stuff simply through language. That's my hater formulation of topology. But at the same time, I'm sure that's very necessary to do sort of rigorous discussion. But I feel like. But don't you think that's what gauge symmetry is like? I mean, it's not a field I know well, but it certainly seems like. Yes, it is like that. But my problem with topology, okay, and even like differential geometry is like, you're talking about beautiful things. Like if they could be visualized, it's open question if everything could be visualized, but you're talking about things that can be visually stunning, I think. But they are hidden underneath all of that math. Like if you look at the papers that are written in topology, if you look at all the discussions on Stack Exchange, they're all math dense, math heavy. And the only kind of visual things that emerge every once in a while, is like something like a Mobius strip. Every once in a while, some kind of simple visualizations. Every once in a while, some kind of simple visualizations. Every once in a while, some kind of simple visualizations. Well, there's the vibration, there's the hop vibration or all those kinds of things that somebody, some grad student from like 20 years ago wrote a program in Fortran to visualize it, and that's it. And it's just, you know, it's makes me sad because those are visual disciplines. Just like computer vision is a visual discipline. So you can provide a lot of visual examples. I wish topology was more excited and in love with visualizing some of the ideas. I mean, you could say that, but I would say for me, a picture of the hop vibration does nothing for me. Whereas like when you're like, oh, it's like about the quaternions. It's like a subgroup of the quaternions. And I'm like, oh, so now I see what's going on. Like, why didn't you just say that? Why were you like showing me this stupid picture instead of telling me what you were talking about? Oh, yeah, yeah. I'm just saying, no, but it goes back to what you were saying about teaching that like people are different in what they'll respond to. So I think there's no, I mean, I'm very opposed to the idea that there's a one right way to explain things. I think there's like a huge variation in like, you know, our brains like have all these like weird like hooks and loops and it's like very hard to know like what's gonna latch on and it's not gonna be the same thing for everybody. So I think monoculture is bad, right? I think that's, and I think we're agreeing on that point that like, it's good that there's like a lot of different ways in and a lot of different ways to describe these ideas because different people are gonna find different things illuminating. But that said, I think there's a lot to be discovered when you force little like silos of brilliant people to kind of find a middle ground or like aggregate or come together in a way. So there's like people that do love visual things. I mean, there's a lot of disciplines, especially in computer science that they're obsessed with visualizing, visualizing data, visualizing neural networks. I mean, neural networks themselves are fundamentally visual. There's a lot of work in computer vision that's very visual. And then coming together with some folks that were like deeply rigorous and are like totally lost in multi dimensional space where it's hard to even bring them back down to 3D. They're very comfortable in this multi dimensional space. So forcing them to kind of work together to communicate because it's not just about public communication of ideas. It's also, I feel like when you're forced to do that public communication like you did with your book, I think deep profound ideas can be discovered that's like applicable for research and for science. Like there's something about that simplification or not simplification, but distillation or condensation or whatever the hell you call it, compression of ideas that somehow actually stimulates creativity. And I'd be excited to see more of that in the mathematics community. Can you? Let me make a crazy metaphor. Maybe it's a little bit like the relation between prose and poetry, right? I mean, if you, you might say like, why do we need anything more than prose? You're trying to convey some information. So you just like say it. Well, poetry does something, right? It's sort of, you might think of it as a kind of compression. Of course, not all poetry is compressed. Like not all, some of it is quite baggy, but like you are kind of, often it's compressed, right? A lyric poem is often sort of like a compression of what would take a long time and be complicated to explain in prose into sort of a different mode that is gonna hit in a different way. We talked about Poincare conjecture. There's a guy, he's Russian, Grigori Perlman. He proved Poincare's conjecture. If you can comment on the proof itself, if that stands out to you as something interesting or the human story of it, which is he turned down the field's metal for the proof. Is there something you find inspiring or insightful about the proof itself or about the man? Yeah, I mean, one thing I really like about the proof and partly that's because it's sort of a thing that happens again and again in this book. I mean, I'm writing about geometry and the way it sort of appears in all these kind of real world problems. But it happens so often that the geometry you think you're studying is somehow not enough. You have to go one level higher in abstraction and study a higher level of geometry. And the way that plays out is that Poincare asks a question about a certain kind of three dimensional object. Is it the usual three dimensional space that we know or is it some kind of exotic thing? And so, of course, this sounds like it's a question about the geometry of the three dimensional space, but no, Perelman understands. And by the way, in a tradition that involves Richard Hamilton and many other people, like most really important mathematical advances, this doesn't happen alone. It doesn't happen in a vacuum. It happens as the culmination of a program that involves many people. Same with Wiles, by the way. I mean, we talked about Wiles and I wanna emphasize that starting all the way back with Kummer, who I mentioned in the 19th century, but Gerhard Frey and Mazer and Ken Ribbit and like many other people are involved in building the other pieces of the arch before you put the keystone in. We stand on the shoulders of giants. Yes. So, what is this idea? The idea is that, well, of course, the geometry of the three dimensional object itself is relevant, but the real geometry you have to understand is the geometry of the space of all three dimensional geometries. Whoa, you're going up a higher level. Because when you do that, you can say, now let's trace out a path in that space. There's a mechanism called Ricci flow. And again, we're outside my research area. So for all the geometric analysts and differential geometers out there listening to this, if I, please, I'm doing my best and I'm roughly saying it. So the Ricci flow allows you to say like, okay, let's start from some mystery three dimensional space, which Poincare would conjecture is essentially the same thing as our familiar three dimensional space, but we don't know that. And now you let it flow. You sort of like let it move in its natural path according to some almost physical process and ask where it winds up. And what you find is that it always winds up. You've continuously deformed it. There's that word deformation again. And what you can prove is that the process doesn't stop until you get to the usual three dimensional space. And since you can get from the mystery thing to the standard space by this process of continually changing and never kind of having any sharp transitions, then the original shape must've been the same as the standard shape. That's the nature of the proof. Now, of course, it's incredibly technical. I think as I understand it, I think the hard part is proving that the favorite word of AI people, you don't get any singularities along the way. But of course, in this context, singularity just means acquiring a sharp kink. It just means becoming non smooth at some point. So just saying something interesting about formal, about the smooth trajectory through this weird space of geometries. But yeah, so what I like about it is that it's just one of many examples of where it's not about the geometry you think it's about. It's about the geometry of all geometries, so to speak. And it's only by kind of like being jerked out of flatland. Same idea. It's only by sort of seeing the whole thing globally at once that you can really make progress on understanding the one thing you thought you were looking at. It's a romantic question, but what do you think about him turning down the Fields Medal? Is that just, are Nobel Prizes and Fields Medals just the cherry on top of the cake and really math itself, the process of curiosity, of pulling at the string of the mystery before us? That's the cake? And then the awards are just icing and clearly I've been fasting and I'm hungry, but do you think it's tragic or just a little curiosity that he turned down the medal? Well, it's interesting because on the one hand, I think it's absolutely true that right, in some kind of like vast spiritual sense, like awards are not important, like not important the way that sort of like understanding the universe is important. On the other hand, most people who are offered that prize accept it, so there's something unusual about his choice there. I wouldn't say I see it as tragic. I mean, maybe if I don't really feel like I have a clear picture of why he chose not to take it. I mean, he's not alone in doing things like this. People sometimes turn down prizes for ideological reasons, but probably more often in mathematics. I mean, I think I'm right in saying that Peter Schultz turned down sort of some big monetary prize because he just, you know, I mean, I think he, at some point you have plenty of money and maybe you think it sends the wrong message about what the point of doing mathematics is. I do find that there's most people accept. You know, most people give it a prize. Most people take it. I mean, people like to be appreciated, but like I said, we're people. Not that different from most other people. But the important reminder that that turning down a prize serves for me is not that there's anything wrong with the prize and there's something wonderful about the prize, I think. The Nobel prize is trickier because so many Nobel prizes are given. First of all, the Nobel prize often forgets many, many of the important people throughout history. Second of all, there's like these weird rules to it that it's only three people and some projects have a huge number of people. And it's like this, it, I don't know. It doesn't kind of highlight the way science is done on some of these projects in the best possible way. But in general, the prizes are great. But what this kind of teaches me and reminds me is sometimes in your life, there'll be moments when the thing that you would really like to do, society would really like you to do, is the thing that goes against something you believe in, whatever that is, some kind of principle. And standing your ground in the face of that is something I believe most people will have a few moments like that in their life, maybe one moment like that, and you have to do it. That's what integrity is. So like, it doesn't have to make sense to the rest of the world, but to stand on that, like to say no, it's interesting, because I think. But do you know that he turned down the prize in service of some principle? Because I don't know that. Well, yes, that seems to be the inkling, but he has never made it super clear. But the inkling is that he had some problems with the whole process of mathematics that includes awards, like this hierarchies and the reputations and all those kinds of things, and individualism that's fundamental to American culture. He probably, because he visited the United States quite a bit that he probably, it's all about experiences. And he may have had some parts of academia, some pockets of academia can be less than inspiring, perhaps sometimes, because of the individual egos involved, not academia, people in general, smart people with egos. And if you interact with a certain kinds of people, you can become cynical too easily. I'm one of those people that I've been really fortunate to interact with incredible people at MIT and academia in general, but I've met some assholes. And I tend to just kind of, when I run into difficult folks, I just kind of smile and send them all my love and just kind of go around. But for others, those experiences can be sticky. Like they can become cynical about the world when folks like that exist. So he may have become a little bit cynical about the process of science. Well, you know, it's a good opportunity. Let's posit that that's his reasoning because I truly don't know. It's an interesting opportunity to go back to almost the very first thing we talked about, the idea of the Mathematical Olympiad, because of course that is, so the International Mathematical Olympiad is like a competition for high school students solving math problems. And in some sense, it's absolutely false to the reality of mathematics, because just as you say, it is a contest where you win prizes. The aim is to sort of be faster than other people. And you're working on sort of canned problems that someone already knows the answer to, like not problems that are unknown. So, you know, in my own life, I think when I was in high school, I was like very motivated by those competitions. And like, I went to the Math Olympiad and... You won it twice and got, I mean... Well, there's something I have to explain to people because it says, I think it says on Wikipedia that I won a gold medal. And in the real Olympics, they only give one gold medal in each event. I just have to emphasize that the International Math Olympiad is not like that. The gold medals are awarded to the top 112th of all participants. So sorry to bust the legend or anything like that. Well, you're an exceptional performer in terms of achieving high scores on the problems and they're very difficult. So you've achieved a high level of performance on the... In this very specialized skill. And by the way, it was a very Cold War activity. You know, in 1987, the first year I went, it was in Havana. Americans couldn't go to Havana back then. It was a very complicated process to get there. And they took the whole American team on a field trip to the Museum of American Imperialism in Havana so we could see what America was all about. How would you recommend a person learn math? So somebody who's young or somebody my age or somebody older who've taken a bunch of math but wants to rediscover the beauty of math and maybe integrate it into their work more solid in the research space and so on. Is there something you could say about the process of... Incorporating mathematical thinking into your life? I mean, the thing is, it's in part a journey of self knowledge. You have to know what's gonna work for you and that's gonna be different for different people. So there are totally people who at any stage of life just start reading math textbooks. That is a thing that you can do and it works for some people and not for others. For others, a gateway is, I always recommend the books of Martin Gardner, another sort of person we haven't talked about but who also, like Conway, embodies that spirit of play. He wrote a column in Scientific American for decades called Mathematical Recreations and there's such joy in it and such fun. And these books, the columns are collected into books and the books are old now but for each generation of people who discover them, they're completely fresh. And they give a totally different way into the subject than reading a formal textbook, which for some people would be the right thing to do. And working contest style problems too, those are bound to books, especially like Russian and Bulgarian problems. There's book after book problems from those contexts. That's gonna motivate some people. For some people, it's gonna be like watching well produced videos, like a totally different format. Like I feel like I'm not answering your question. I'm sort of saying there's no one answer and it's a journey where you figure out what resonates with you. For some people, it's the self discovery is trying to figure out why is it that I wanna know? Okay, I'll tell you a story. Once when I was in grad school, I was very frustrated with my lack of knowledge of a lot of things as we all are because no matter how much we know, we don't know much more and going to grad school means just coming face to face with the incredible overflowing vault of your ignorance. So I told Joe Harris, who was an algebraic geometer, a professor in my department, I was like, I really feel like I don't know enough and I should just take a year of leave and just read EGA, the holy textbook, Elements de Géométrie Algebraique, the Elements of Algebraic Geometry. I'm just gonna, I feel like I don't know enough so I'm just gonna sit and read this like 1500 page many volume book. And he was like, and Professor Harris was like, that's a really stupid idea. And I was like, why is that a stupid idea? Then I would know more algebraic geometry. He's like, because you're not actually gonna do it. Like you learn. I mean, he knew me well enough to say like, you're gonna learn because you're gonna be working on a problem and then there's gonna be a fact from EGA that you need in order to solve your problem that you wanna solve and that's how you're gonna learn it. You're not gonna learn it without a problem to bring you into it. And so for a lot of people, I think if you're like, I'm trying to understand machine learning and I'm like, I can see that there's sort of some mathematical technology that I don't have, I think you like let that problem that you actually care about drive your learning. I mean, one thing I've learned from advising students, math is really hard. In fact, anything that you do right is hard. And because it's hard, like you might sort of have some idea that somebody else gives you, oh, I should learn X, Y and Z. Well, if you don't actually care, you're not gonna do it. You might feel like you should, maybe somebody told you you should, but I think you have to hook it to something that you actually care about. So for a lot of people, that's the way in. You have an engineering problem you're trying to handle, you have a physics problem you're trying to handle, you have a machine learning problem you're trying to handle. Let that not a kind of abstract idea of what the curriculum is, drive your mathematical learning. And also just as a brief comment that math is hard, there's a sense to which hard is a feature, not a bug, in the sense that, again, maybe this is my own learning preference, but I think it's a value to fall in love with the process of doing something hard, overcoming it, and becoming a better person because of it. Like I hate running, I hate exercise, to bring it down to like the simplest hard. And I enjoy the part once it's done, the person I feel like in the rest of the day once I've accomplished it, the actual process, especially the process of getting started in the initial, like it really, I don't feel like doing it. And I really have, the way I feel about running is the way I feel about really anything difficult in the intellectual space, especially in mathematics, but also just something that requires like holding a bunch of concepts in your mind with some uncertainty, like where the terminology or the notation is not very clear. And so you have to kind of hold all those things together and like keep pushing forward through the frustration of really like obviously not understanding certain like parts of the picture, like your giant missing parts of the picture and still not giving up. It's the same way I feel about running. And there's something about falling in love with the feeling of after you went through the journey of not having a complete picture, at the end having a complete picture, and then you get to appreciate the beauty and just remembering that it sucked for a long time and how great it felt when you figured it out, at least at the basic. That's not sort of research thinking, because with research, you probably also have to enjoy the dead ends with learning math from a textbook or from video. There's a nice. I don't think you have to enjoy the dead ends, but I think you have to accept the dead ends. Let's put it that way. Well, yeah, enjoy the suffering of it. So the way I think about it, I do, there's an. I don't enjoy the suffering. It pisses me off. You have to accept that it's part of the process. It's interesting. There's a lot of ways to kind of deal with that dead end. There's a guy who's the ultra marathon runner, Navy SEAL, David Goggins, who kind of, I mean, there's a certain philosophy of like, most people would quit here. And so if most people would quit here and I don't, I'll have an opportunity to discover something beautiful that others haven't yet. And so like any feeling that really sucks, it's like, okay, most people would just like, go do something smarter. And if I stick with this, I will discover a new garden of fruit trees that I can pick. Okay, you say that, but like, what about the guy who like wins the Nathan's hot dog eating contest every year? Like when he eats his 35th hot dog, he like correctly says like, okay, most people would stop here. Are you like lauding that he's like, no, I'm gonna eat the 35th hot dog. I am, I am. In the long arc of history, that man is onto something. Which brings up this question. What advice would you give to young people today, thinking about their career, about their life, whether it's in mathematics, poetry, or hot dog eating contest? And you know, I have kids, so this is actually a live issue for me, right? I actually, it's not a thought experiment. I actually do have to give advice to two young people all the time. They don't listen, but I still give it. You know, one thing I often say to students, I don't think I've actually said this to my kids yet, but I say it to students a lot is, you know, you come to these decision points and everybody is beset by self doubt, right? It's like, not sure like what they're capable of, like not sure what they really wanna do. I always, I sort of tell people like, often when you have a decision to make, one of the choices is the high self esteem choice. And I always tell them, make the high self esteem choice. Make the choice, sort of take yourself out of it and like, if you didn't have those, you can probably figure out what the version of you that feels completely confident would do. And do that and see what happens. And I think that's often like pretty good advice. That's interesting. Sort of like, you know, like with Sims, you can create characters. Create a character of yourself that lacks all the self doubt. Right, but it doesn't mean, I would never say to somebody, you should just go have high self esteem. You shouldn't have doubts. No, you probably should have doubts. It's okay to have them. But sometimes it's good to act in the way that the person who didn't have them would act. That's a really nice way to put it. Yeah, that's like from a third person perspective, take the part of your brain that wants to do big things. What would they do? That's not afraid to do those things. What would they do? Yeah, that's really nice. That's actually a really nice way to formulate it. That's very practical advice. You should give it to your kids. Do you think there's meaning to any of it from a mathematical perspective, this life? If I were to ask you, we talked about primes, talked about proving stuff. Can we say, and then the book that God has, that mathematics allows us to arrive at something about in that book. There's certainly a chapter on the meaning of life in that book. Do you think we humans can get to it? And maybe if you were to write cliff notes, what do you suspect those cliff notes would say? I mean, look, the way I feel is that mathematics, as we've discussed, it underlies the way we think about constructing learning machines. It underlies physics. It can be used. I mean, it does all this stuff. And also you want the meaning of life? I mean, it's like, we already did a lot for you. Like, ask a rabbi. No, I mean, I wrote a lot in the last book, How Not to Be Wrong. I wrote a lot about Pascal, a fascinating guy who is a sort of very serious religious mystic, as well as being an amazing mathematician. And he's well known for Pascal's wager. I mean, he's probably among all mathematicians. He's the one who's best known for this. Can you actually like apply mathematics to kind of these transcendent questions? But what's interesting when I really read Pascal about what he wrote about this, I started to see that people often think, oh, this is him saying, I'm gonna use mathematics to sort of show you why you should believe in God. You know, mathematics has the answer to this question. But he really doesn't say that. He almost kind of says the opposite. If you ask Blaise Pascal, like, why do you believe in God? He'd be like, oh, cause I met God. You know, he had this kind of like psychedelic experience. It's like a mystical experience where as he tells it, he just like directly encountered God. It's like, okay, I guess there's a God, I met him last night. So that's it. That's why he believed. It didn't have to do with any kind. You know, the mathematical argument was like about certain reasons for behaving in a certain way. But he basically said, like, look, like math doesn't tell you that God's there or not. Like, if God's there, he'll tell you. You know, you don't even. I love this. So you have mathematics, you have, what do you have? Like a way to explore the mind, let's say psychedelics. You have like incredible technology. You also have love and friendship. And like, what the hell do you want to know what the meaning of it all is? Just enjoy it. I don't think there's a better way to end it, Jordan. This was a fascinating conversation. I really love the way you explore math in your writing. The willingness to be specific and clear and actually explore difficult ideas, but at the same time stepping outside and figuring out beautiful stuff. And I love the chart at the opening of your new book that shows the chaos, the mess that is your mind. Yes, this is what I was trying to keep in my head all at once while I was writing. And I probably should have drawn this picture earlier in the process. Maybe it would have made my organization easier. I actually drew it only at the end. And many of the things we talked about are on this map. The connections are yet to be fully dissected, investigated. And yes, God is in the picture. Right on the edge, right on the edge, not in the center. Thank you so much for talking to me. It is a huge honor that you would waste your valuable time with me. Thank you, Lex. We went to some amazing places today. This was really fun. Thanks for listening to this conversation with Jordan Ellenberg. And thank you to Secret Sauce, ExpressVPN, Blinkist, and Indeed. Check them out in the description to support this podcast. And now let me leave you with some words from Jordan in his book, How Not To Be Wrong. Knowing mathematics is like wearing a pair of X ray specs that reveal hidden structures underneath the messy and chaotic surface of the world. Thank you for listening and hope to see you next time. He's always motivated by physics, but the physics drove him to need to think about spaces of higher dimension. And so he needed a formalism that was rich enough to enable him to do that. And once you do that, that formalism is also gonna include things that are not physical. And then you have two choices. You can be like, oh, well, that stuff's trash. Or, and this is more of the mathematicians frame of mind, if you have a formalistic framework that like seems really good and sort of seems to be like very elegant and work well, and it includes all the physical stuff, maybe we should think about all of it. Like maybe we should think about it, thinking maybe there's some gold to be mined there. And indeed, like, you know, guess what? Like before long there's relativity and there's space time. And like all of a sudden it's like, oh yeah, maybe it's a good idea. We already had this geometric apparatus like set up for like how to think about four dimensional spaces, like turns out they're real after all. As I said, you know, this is a story much told right in mathematics, not just in this context, but in many. I'd love to dig in a little deeper on that actually, cause I have some intuitions to work out. Okay. My brain. Well, I'm not a mathematical physicist, so we can work them out together. Good. We'll together walk along the path of curiosity, but Poincare conjecture. What is it? The Poincare conjecture is about curved three dimensional spaces. So I was on my way there. I promise. The idea is that we perceive ourselves as living in, we don't say a three dimensional space. We just say three dimensional space. You know, you can go up and down, you can go left and right, you can go forward and back. There's three dimensions in which we can move. In Poincare's theory, there are many possible three dimensional spaces. In the same way that going down one dimension to sort of capture our intuition a little bit more, we know there are lots of different two dimensional surfaces, right? There's a balloon and that looks one way and a donut looks another way and a Mobius strip looks a third way. Those are all like two dimensional surfaces that we can kind of really get a global view of because we live in three dimensional space. So we can see a two dimensional surface sort of sitting in our three dimensional space. Well, to see a three dimensional space whole, we'd have to kind of have four dimensional eyes, right? Which we don't. So we have to use our mathematical eyes. We have to envision. The Poincare conjecture says that there's a very simple way to determine whether a three dimensional space is the standard one, the one that we're used to. And essentially it's that it's what's called fundamental group has nothing interesting in it. And that I can actually say without saying what the fundamental group is, I can tell you what the criterion is. This would be good. Oh, look, I can even use a visual aid. So for the people watching this on YouTube, you will just see this for the people on the podcast, you'll have to visualize it. So Lex has been nice enough to like give me a surface with an interesting topology. It's a mug right here in front of me. A mug, yes. I might say it's a genus one surface, but we could also say it's a mug, same thing. So if I were to draw a little circle on this mug, which way should I draw it so it's visible? Like here, okay. If I draw a little circle on this mug, imagine this to be a loop of string. I could pull that loop of string closed on the surface of the mug, right? That's definitely something I could do. I could shrink it, shrink it, shrink it until it's a point. On the other hand, if I draw a loop that goes around the handle, I can kind of zhuzh it up here and I can zhuzh it down there and I can sort of slide it up and down the handle, but I can't pull it closed, can I? It's trapped. Not without breaking the surface of the mug, right? Not without like going inside. So the condition of being what's called simply connected, this is one of Poincare's inventions, says that any loop of string can be pulled shut. So it's a feature that the mug simply does not have. This is a non simply connected mug and a simply connected mug would be a cup, right? You would burn your hand when you drank coffee out of it. So you're saying the universe is not a mug. Well, I can't speak to the universe, but what I can say is that regular old space is not a mug. Regular old space, if you like sort of actually physically have like a loop of string, you can pull it shut. You can always pull it shut. But what if your piece of string was the size of the universe? Like what if your piece of string was like billions of light years long? Like how do you actually know? I mean, that's still an open question of the shape of the universe. Exactly. I think there's a lot, there is ideas of it being a torus. I mean, there's some trippy ideas and they're not like weird out there controversial. There's legitimate at the center of a cosmology debate. I mean, I think most people think it's flat. I think there's some kind of dodecahedral symmetry or I mean, I remember reading something crazy about somebody saying that they saw the signature of that in the cosmic noise or what have you. I mean. To make the flat earthers happy, I do believe that the current main belief is it's flat. It's flat ish or something like that. The shape of the universe is flat ish. I don't know what the heck that means. I think that has like a very, how are you even supposed to think about the shape of a thing that doesn't have any thing outside of it? I mean. Ah, but that's exactly what topology does. Topology is what's called an intrinsic theory. That's what's so great about it. This question about the mug, you could answer it without ever leaving the mug, right? Because it's a question about a loop drawn on the surface of the mug and what happens if it never leaves that surface. So it's like always there. See, but that's the difference between the topology and say, if you're like trying to visualize a mug, that you can't visualize a mug while living inside the mug. Well, that's true. The visualization is harder, but in some sense, no, you're right. But if the tools of mathematics are there, I, sorry, I don't want to fight, but I think the tools of mathematics are exactly there to enable you to think about what you cannot visualize in this way. Let me give, let's go, always to make things easier, go down to dimension. Let's think about we live in a circle, okay? You can tell whether you live on a circle or a line segment, because if you live in a circle, if you walk a long way in one direction, you find yourself back where you started. And if you live in a line segment, you walk for a long enough one direction, you come to the end of the world. Or if you live on a line, like a whole line, infinite line, then you walk in one direction for a long time and like, well, then there's not a sort of terminating algorithm to figure out whether you live on a line or a circle, but at least you sort of, at least you don't discover that you live on a circle. So all of those are intrinsic things, right? All of those are things that you can figure out about your world without leaving your world. On the other hand, ready? Now we're going to go from intrinsic to extrinsic. Boy, did I not know we were going to talk about this, but why not? Why not? If you can't tell whether you live in a circle or a knot, like imagine like a knot floating in three dimensional space. The person who lives on that knot, to them it's a circle. They walk a long way, they come back to where they started. Now we, with our three dimensional eyes can be like, oh, this one's just a plain circle and this one's knotted up, but that has to do with how they sit in three dimensional space. It doesn't have to do with intrinsic features of those people's world. We can ask you one ape to another. Does it make you, how does it make you feel that you don't know if you live in a circle or on a knot, in a knot, inside the string that forms the knot? I don't even know how to say that. I'm going to be honest with you. I don't know if, I fear you won't like this answer, but it does not bother me at all. I don't lose one minute of sleep over it. So like, does it bother you that if we look at like a Mobius strip, that you don't have an obvious way of knowing whether you are inside of a cylinder, if you live on a surface of a cylinder or you live on the surface of a Mobius strip? No, I think you can tell if you live. Which one? Because what you do is you like tell your friend, hey, stay right here, I'm just going to go for a walk. And then you like walk for a long time in one direction and then you come back and you see your friend again. And if your friend is reversed, then you know you live on a Mobius strip. Well, no, because you won't see your friend, right? Okay, fair point, fair point on that. But you have to believe the stories about, no, I don't even know, would you even know? Would you really? Oh, no, your point is right. Let me try to think of a better, let's see if I can do this on the fly. It may not be correct to talk about cognitive beings living on a Mobius strip because there's a lot of things taken for granted there. And we're constantly imagining actual like three dimensional creatures, like how it actually feels like to live in a Mobius strip is tricky to internalize. I think that on what's called the real protective plane, which is kind of even more sort of like messed up version of the Mobius strip, but with very similar features, this feature of kind of like only having one side, that has the feature that there's a loop of string which can't be pulled closed. But if you loop it around twice along the same path, that you can pull closed. That's extremely weird. Yeah. But that would be a way you could know without leaving your world that something very funny is going on. You know what's extremely weird? Maybe we can comment on, hopefully it's not too much of a tangent is, I remember thinking about this, this might be right, this might be wrong. But if we now talk about a sphere and you're living inside a sphere, that you're going to see everywhere around you, the back of your own head. That I was, cause like I was, this is very counterintuitive to me to think about, maybe it's wrong. But cause I was thinking of like earth, your 3D thing sitting on a sphere. But if you're living inside the sphere, like you're going to see, if you look straight, you're always going to see yourself all the way around. So everywhere you look, there's going to be the back of your own head. I think somehow this depends on something of like how the physics of light works in this scenario, which I'm sort of finding it hard to bend my. That's true. The sea is doing a lot of work. Like saying you see something is doing a lot of work. People have thought about this a lot. I mean, this metaphor of like, what if we're like little creatures in some sort of smaller world? Like how could we apprehend what's outside? That metaphor just comes back and back. And actually I didn't even realize like how frequent it is. It comes up in the book a lot. I know it from a book called Flatland. I don't know if you ever read this when you were a kid. A while ago, yeah. An adult. You know, this sort of comic novel from the 19th century about an entire two dimensional world. It's narrated by a square. That's the main character. And the kind of strangeness that befalls him when one day he's in his house and suddenly there's like a little circle there and they're with him. But then the circle like starts getting bigger and bigger and bigger. And he's like, what the hell is going on? It's like a horror movie, like for two dimensional people. And of course what's happening is that a sphere is entering his world. And as the sphere kind of like moves farther and farther into the plane, it's cross section. The part of it that he can see. To him, it looks like there's like this kind of bizarre being that's like getting larger and larger and larger until it's exactly sort of halfway through. And then they have this kind of like philosophical argument where the sphere is like, I'm a sphere. I'm from the third dimension. The square is like, what are you talking about? There's no such thing. And they have this kind of like sterile argument where the square is not able to kind of like follow the mathematical reasoning of the sphere until the sphere just kind of grabs him and like jerks him out of the plane and pulls him up. And it's like now, like now do you see, like now do you see your whole world that you didn't understand before? So do you think that kind of process is possible for us humans? So we live in the three dimensional world, maybe with the time component four dimensional and then math allows us to go high, into high dimensions comfortably and explore the world from those perspectives. Like, is it possible that the universe is many more dimensions than the ones we experience as human beings? So if you look at the, you know, especially in physics theories of everything, physics theories that try to unify general relativity and quantum field theory, they seem to go to high dimensions to work stuff out through the tools of mathematics. Is it possible? So like the two options are, one is just a nice way to analyze a universe, but the reality is, is as exactly we perceive it, it is three dimensional, or are we just seeing, are we those flatland creatures that are just seeing a tiny slice of reality and the actual reality is many, many, many more dimensions than the three dimensions we perceive? Oh, I certainly think that's possible. Now, how would you figure out whether it was true or not is another question. And I suppose what you would do as with anything else that you can't directly perceive is you would try to understand what effect the presence of those extra dimensions out there would have on the things we can perceive. Like what else can you do, right? And in some sense, if the answer is they would have no effect, then maybe it becomes like a little bit of a sterile question, because what question are you even asking, right? You can kind of posit however many entities that you want. Is it possible to intuit how to mess with the other dimensions while living in a three dimensional world? I mean, that seems like a very challenging thing to do. The reason flatland could be written is because it's coming from a three dimensional writer. Yes, but what happens in the book, I didn't even tell you the whole plot. What happens is the square is so excited and so filled with intellectual joy. By the way, maybe to give the story some context, you asked like, is it possible for us humans to have this experience of being transcendentally jerked out of our world so we can sort of truly see it from above? Well, Edwin Abbott who wrote the book certainly thought so because Edwin Abbott was a minister. So the whole Christian subtext of this book, I had completely not grasped reading this as a kid, that it means a very different thing, right? If sort of a theologian is saying like, oh, what if a higher being could like pull you out of this earthly world you live in so that you can sort of see the truth and like really see it from above as it were. So that's one of the things that's going on for him. And it's a testament to his skill as a writer that his story just works whether that's the framework you're coming to it from or not. But what happens in this book and this part, now looking at it through a Christian lens, it becomes a bit subversive is the square is so excited about what he's learned from the sphere and the sphere explains to him like what a cube would be. Oh, it's like you but three dimensional and the square is very excited and the square is like, okay, I get it now. So like now that you explained to me how just by reason I can figure out what a cube would be like, like a three dimensional version of me, like let's figure out what a four dimensional version of me would be like. And then the sphere is like, what the hell are you talking about? There's no fourth dimension, that's ridiculous. Like there's three dimensions, like that's how many there are, I can see. Like, I mean, it's this sort of comic moment where the sphere is completely unable to conceptualize that there could actually be yet another dimension. So yeah, that takes the religious allegory like a very weird place that I don't really like understand theologically, but. That's a nice way to talk about religion and myth in general as perhaps us trying to struggle, us meaning human civilization, trying to struggle with ideas that are beyond our cognitive capabilities. But it's in fact not beyond our capability. It may be beyond our cognitive capabilities to visualize a four dimensional cube, a tesseract as some like to call it, or a five dimensional cube, or a six dimensional cube, but it is not beyond our cognitive capabilities to figure out how many corners a six dimensional cube would have. That's what's so cool about us. Whether we can visualize it or not, we can still talk about it, we can still reason about it, we can still figure things out about it. That's amazing. Yeah, if we go back to this, first of all, to the mug, but to the example you give in the book of the straw, how many holes does a straw have? And you, listener, may try to answer that in your own head. Yeah, I'm gonna take a drink while everybody thinks about it so we can give you a moment. A slow sip. Is it zero, one, or two, or more than that maybe? Maybe you can get very creative. But it's kind of interesting to each, dissecting each answer as you do in the book is quite brilliant. People should definitely check it out. But if you could try to answer it now, think about all the options and why they may or may not be right. Yeah, and it's one of these questions where people on first hearing it think it's a triviality and they're like, well, the answer is obvious. And then what happens if you ever ask a group of people that something wonderfully comic happens, which is that everyone's like, well, it's completely obvious. And then each person realizes that half the person, the other people in the room have a different obvious answer for the way they have. And then people get really heated. People are like, I can't believe that you think it has two holes or like, I can't believe that you think it has one. And then, you know, you really, like people really learn something about each other and people get heated. I mean, can we go through the possible options here? Is it zero, one, two, three, 10? Sure, so I think, you know, most people, the zero holders are rare. They would say like, well, look, you can make a straw by taking a rectangular piece of plastic and closing it up. A rectangular piece of plastic doesn't have a hole in it. I didn't poke a hole in it when I, so how can I have a hole? They'd be like, it's just one thing. Okay, most people don't see it that way. That's like a... Is there any truth to that kind of conception? Yeah, I think that would be somebody who's account, I mean, what I would say is you could say the same thing about a bagel. You could say, I can make a bagel by taking like a long cylinder of dough, which doesn't have a hole and then schmushing the ends together. Now it's a bagel. So if you're really committed, you can be like, okay, a bagel doesn't have a hole either. But like, who are you if you say a bagel doesn't have a hole? I mean, I don't know. Yeah, so that's almost like an engineering definition of it. Okay, fair enough. So what about the other options? So, you know, one whole people would say... I like how these are like groups of people. Like we've planted our foot, this is what we stand for. There's books written about each belief. You know, I would say, look, there's like a hole and it goes all the way through the straw, right? It's one region of space, that's the hole. And there's one. And two whole people would say like, well, look, there's a hole in the top and a hole at the bottom. I think a common thing you see when people argue about this, they would take something like this bottle of water I'm holding and go open it and they say, well, how many holes are there in this? And you say like, well, there's one hole at the top. Okay, what if I like poke a hole here so that all the water spills out? Well, now it's a straw. Yeah. So if you're a one holder, I say to you like, well, how many holes are in it now? There was one hole in it before and I poked a new hole in it. And then you think there's still one hole even though there was one hole and I made one more? Clearly not, this is two holes. Yeah. And yet if you're a two holder, the one holder will say like, okay, where does one hole begin and the other hole end? Yeah. And in the book, I sort of, you know, in math, there's two things we do when we're faced with a problem that's confusing us. We can make the problem simpler. That's what we were doing a minute ago when we were talking about high dimensional space. And I was like, let's talk about like circles and line segments. Let's like go down a dimension to make it easier. The other big move we have is to make the problem harder and try to sort of really like face up to what are the complications. So, you know, what I do in the book is say like, let's stop talking about straws for a minute and talk about pants. How many holes are there in a pair of pants? So I think most people who say there's two holes in a straw would say there's three holes in a pair of pants. I guess, I mean, I guess we're filming only from here. I could take up, no, I'm not gonna do it. You'll just have to imagine the pants, sorry. Yeah. Lex, if you want to, no, okay, no. That's gonna be in the director's cut. That's that Patreon only footage. There you go. So many people would say there's three holes in a pair of pants. But you know, for instance, my daughter, when I asked, by the way, talking to kids about this is super fun. I highly recommend it. What did she say? She said, well, yeah, I feel a pair of pants like just has two holes because yes, there's the waist, but that's just the two leg holes stuck together. Whoa, okay. Two leg holes, yeah, okay. I mean, that really is a good combination. So she's a one holder for the straw. So she's a one holder for the straw too. And that really does capture something. It captures this fact, which is central to the theory of what's called homology, which is like a central part of modern topology that holes, whatever we may mean by them, they're somehow things which have an arithmetic to them. They're things which can be added. Like the waist, like waist equals leg plus leg is kind of an equation, but it's not an equation about numbers. It's an equation about some kind of geometric, some kind of topological thing, which is very strange. And so, you know, when I come down, you know, like a rabbi, I like to kind of like come up with these answers and somehow like dodge the original question and say like, you're both right, my children. Okay, so. Yeah. So for the straw, I think what a modern mathematician would say is like, the first version would be to say like, well, there are two holes, but they're really both the same hole. Well, that's not quite right. A better way to say it is there's two holes, but one is the negative of the other. Now, what can that mean? One way of thinking about what it means is that if you sip something like a milkshake through the straw, no matter what, the amount of milkshake that's flowing in one end, that same amount is flowing out the other end. So they're not independent from each other. There's some relationship between them. In the same way that if you somehow could like suck a milkshake through a pair of pants, the amount of milkshake, just go with me on this thought experiment. I'm right there with you. The amount of milkshake that's coming in the left leg of the pants, plus the amount of milkshake that's coming in the right leg of the pants, is the same that's coming out the waist of the pants. So just so you know, I fasted for 72 hours the last three days. So I just broke the fast with a little bit of food yesterday. So this sounds, food analogies or metaphors for this podcast work wonderfully because I can intensely picture it. Is that your weekly routine or just in preparation for talking about geometry for three hours? Exactly, this is just for this. It's hardship to purify the mind. No, it's for the first time, I just wanted to try the experience. Oh, wow. And just to pause, to do things that are out of the ordinary, to pause and to reflect on how grateful I am to be just alive and be able to do all the cool shit that I get to do, so. Did you drink water? Yes, yes, yes, yes, yes. Water and salt, so like electrolytes and all those kinds of things. But anyway, so the inflow on the top of the pants equals to the outflow on the bottom of the pants. Exactly, so this idea that, I mean, I think, you know, Poincare really had this idea, this sort of modern idea. I mean, building on stuff other people did, Betty is an important one, of this kind of modern notion of relations between holes. But the idea that holes really had an arithmetic, the really modern view was really Emmy Noether's idea. So she kind of comes in and sort of truly puts the subject on its modern footing that we have now. So, you know, it's always a challenge, you know, in the book, I'm not gonna say I give like a course so that you read this chapter and then you're like, oh, it's just like I took like a semester of algebraic anthropology. It's not like this and it's always a challenge writing about math because there are some things that you can really do on the page and the math is there. And there's other things which it's too much in a book like this to like do them all the page. You can only say something about them, if that makes sense. So, you know, in the book, I try to do some of both. I try to do, I try to, topics that are, you can't really compress and really truly say exactly what they are in this amount of space. I try to say something interesting about them, something meaningful about them so that readers can get the flavor. And then in other places, I really try to get up close and personal and really do the math and have it take place on the page. To some degree be able to give inklings of the beauty of the subject. Yeah, I mean, there's a lot of books that are like, I don't quite know how to express this well. I'm still laboring to do it, but there's a lot of books that are about stuff, but I want my books to not only be about stuff, but to actually have some stuff there on the page in the book for people to interact with directly and not just sort of hear me talk about distant features of it. Right, so not be talking just about ideas, but the actually be expressing the idea. Is there, you know, somebody in the, maybe you can comment, there's a guy, his YouTube channel is 3Blue1Brown, Grant Sanderson. He does that masterfully well. Absolutely. Of visualizing, of expressing a particular idea and then talking about it as well back and forth. What do you think about Grant? It's fantastic. I mean, the flowering of math YouTube is like such a wonderful thing because math teaching, there's so many different venues through which we can teach people math. There's the traditional one, right? Where I'm in a classroom with, depending on the class, it could be 30 people, it could be a hundred people, it could, God help me, be a 500 people if it's like the big calculus lecture or whatever it may be. And there's sort of some, but there's some set of people of that order of magnitude and I'm with them, we have a long time. I'm with them for a whole semester and I can ask them to do homework and we talk together. We have office hours, if they have one on one questions, a lot of, it's like a very high level of engagement, but how many people am I actually hitting at a time? Like not that many, right? And you can, and there's kind of an inverse relationship where the more, the fewer people you're talking to, the more engagement you can ask for. The ultimate of course is like the mentorship relation of like a PhD advisor and a graduate student where you spend a lot of one on one time together for like three to five years. And the ultimate high level of engagement to one person. Books, this can get to a lot more people that are ever gonna sit in my classroom and you spend like however many hours it takes to read a book. Somebody like Three Blue One Brown or Numberphile or people like Vi Hart. I mean, YouTube, let's face it, has bigger reach than a book. Like there's YouTube videos that have many, many, many more views than like any hardback book like not written by a Kardashian or an Obama is gonna sell, right? So that's, I mean, and then those are, some of them are like longer, 20 minutes long, some of them are five minutes long, but they're shorter. And then even some of you look like Eugenia Chang who's a wonderful category theorist in Chicago. I mean, she was on, I think the Daily Show or is it, I mean, she was on, she has 30 seconds, but then there's like 30 seconds to sort of say something about mathematics to like untold millions of people. So everywhere along this curve is important. And one thing I feel like is great right now is that people are just broadcasting on all the channels because we each have our skills, right? Somehow along the way, like I learned how to write books. I had this kind of weird life as a writer where I sort of spent a lot of time like thinking about how to put English words together into sentences and sentences together into paragraphs, like at length, which is this kind of like weird specialized skill. And that's one thing, but like sort of being able to make like winning, good looking, eye catching videos is like a totally different skill. And probably somewhere out there, there's probably sort of some like heavy metal band that's like teaching math through heavy metal and like using their skills to do that. I hope there is at any rate. Their music and so on, yeah. But there is something to the process. I mean, Grant does this especially well, which is in order to be able to visualize something, now he writes programs, so it's programmatic visualization. So like the things he is basically mostly through his Manum library and Python, everything is drawn through Python. You have to truly understand the topic to be able to visualize it in that way and not just understand it, but really kind of think in a very novel way.

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