第 321 期·中文精讀

雷·庫茲韋爾:奇點、超級智慧與永生

Ray Kurzweil: Singularity, Superintelligence, and Immortality

未來學家談技術的指數級增長、2029 年預言的依據、人機融合與延壽路徑,以及超級智慧的潛在風險。

官方音訊00:00 / --:--
中文精讀由 AI 基於原始訪談改寫,非官方翻譯,可能存在偏差或錯誤;表述以原音訊與官方文稿為準。說明

2029 年,一臺機器會透過圖靈測試。雷·庫茲韋爾(Ray Kurzweil)在 1999 年的《精神機器的時代》(The Age of Spiritual Machines)裡寫下了這個數字,2005 年在《奇點臨近》(The Singularity is Near)裡又寫了一遍。斯坦福當時被這個預測驚動,召集全球 AI 專家開會評估,然後做了投票。平均預測是一百年之後,20% 的人認為永遠不會發生,80% 認為會發生但不相信自己能活著看到。

二十多年過去,同一批專家給出的時間點一路下滑。一年前一個叫 Meticulous 的專案重新評估,AI 專家給出的答案是 2042 年。幾周前又做了一次,答案變成了 2030 年。庫茲韋爾自己的數字,二十三年一個都沒動。

Lex Fridman 在第 321 期播客裡問他,2045 年的奇點預測還成立嗎。庫茲韋爾的回答是,不僅成立,他正在寫一本新書,叫《奇點更近了》(Singularity is Nearer)。

這場對話從圖靈測試講到意識,從意識講到把大腦接進雲端,從雲端講到數字複製品和永生,中間夾著算力曲線、奈米機器人、灰蠱、極端貧困的民調資料,最後落在一個詞上:愛。庫茲韋爾談技術時全程用現在時,彷彿那些東西已經存在。他談愛的時候,用的也是現在時。

十五分鐘的圖靈測試遠遠不夠

1950 年那篇論文裡,圖靈談到測試的部分只有寥寥幾行。他說如果對話進行十五分鐘,就足以判斷。庫茲韋爾不認同這個時長。

他看到現在的大語言模型已經能在短對話裡騙過不少人,你可以跟它聊上幾個小時。聊得越久,破綻越多。所以他給出的版本要嚴格得多:對話要持續幾個小時,人類裁判得是懂行的,知道計算機能做什麼、不能做什麼。普通人或者普通工程師,可能根本不知道怎麼去挑戰系統。

“你要的是它真的能說服你它是人類,無論這需要什麼代價。也許需要幾天,也許需要幾周,但它必須真的說服你。”(雷·庫茲韋爾)

大語言模型在哪兒露餡?庫茲韋爾舉的例子很具體。你問“10 頭大象有幾條腿”,它說每頭 4 條,10 頭 40 條,答得挺好。你接著問“11 頭大象有幾條腿”,它好像聽不懂這個問題了。斷裂的地方在推斷鏈,它沒辦法把“4 乘以 11”這個鏈條穩定地走下去。

庫茲韋爾也補了一句讓人沒法反駁的話:人類做這類多步推理同樣經常出錯,大量民調裡都能看到這一點。所以圖靈測試本身定義得很模糊,它是一種直覺判斷,看它到底能不能說服你,談不上科學標準。

他的判斷是,2029 年透過嚴格版測試的會是大語言模型,但一定是進化過的大語言模型,今天這一代還不行。而一旦它真的透過了,他願意承認它有意識。

意識是個沒法證明的東西

庫茲韋爾對意識的態度很坦率。他相信 Lex 有意識,可這只是個信念,拿不出證明。你沒法證明一隻動物有沒有意識,更沒法證明一臺行為完全像人的機器有沒有意識。他打了個比方:你說一幅畫很美,很多人也能同樣感受到,但你沒法證明它美。

馬文·明斯基(Marvin Minsky)的立場是,意識不邏輯、不科學,關於它的所有討論都不值得信。庫茲韋爾觀察到另一件事:明斯基真的面對一個有意識的人時,行為完全是另一套。他會像對待一個有意識的存在那樣對待對方。

“他說意識不重要,但他實際的行為是另一套。這個人身上有很多矛盾。”(雷·庫茲韋爾)

關於機器意識有一種觀點流傳很廣:任何能做決策的東西都有意識,你的電燈開關也有意識,只是層級很低、沒什麼意思。一臺能做出更有趣決策的計算機,意識層級比開關高,但還沒到人類水平。庫茲韋爾沒有否定這種說法,他只指出關於意識有太多不同的看法,誰也說服不了誰。

他願意認真對待的是倫理問題。假如一臺機器在 2029 年透過了嚴格圖靈測試,人類要不要開始爭論“關掉它算不算謀殺”?庫茲韋爾說這個問題確實會來,只是還沒真的發生。

他判斷轉變是漸進的。今天大部分人不會認為大語言模型有意識,包括他自己。等這些模型的各種毛病被一個個解決,接受它有意識的人會越來越多。到 2029 年,相當一部分人會相信它是有意識的。這條曲線已經開始了,只是還沒走完。Google 有個工程師聲稱某個模型有意識,那只是一個人,不代表什麼。等這種事變成規模現象,文明才會真正開始討論 AI 在這個世界上的位置。

2030 年代:把新皮層接到雲上

庫茲韋爾把下一步放在 2030 年代:把新皮層(neocortex)直接連到計算機上。新皮層是我們思考的地方,結構像一座金字塔,越往上越小,最頂層非常小。腦機介面要接就接在那一層。

他用手機打比方。節目是純音訊,但庫茲韋爾在現場舉起了智慧手機,說這臺裝置已經大幅放大了他的智慧。他寫第一本書《智慧機器時代》(The Age of Intelligent Machines)的時候,從計算機裡拿不到任何資訊,得去圖書館找書、翻到某一頁、走到影印機前。那時候他最重要的資訊工具,是一卷喂影印機的 25 美分硬幣。

手機已經讓他比沒有手機時聰明得多。麻煩在於幾個環節:他老是把它放下就忘了放哪兒,雖然從來沒真丟過;要用的時候得先找到,再開啟,中間有一串動作。更理想的狀態是被動式,像你醒著時大腦一直在那兒一樣,裝置一直在,聽到你的對話,知道你在聊哪個女演員,直接把資訊遞給你。庫茲韋爾說這件事今天技術上就差不多能做。

再往前一步是進到大腦裡面。現在已經有一些腦機介面原型,能工作,頻寬遠遠不夠。Neuralink 是這條路上的嘗試,目前頻寬不足。庫茲韋爾認為它會先被批准用於真正需要的人,比如肌肉無法動彈、無法交流的人,對他們價值巨大。他認識幾個這樣的人,腦子裡有想法,身體傳不出來。最終所有人都會用。

頻寬夠了之後會發生什麼?人和人之間的交流可能不再需要語言這種低頻寬機制。庫茲韋爾說我們不知道那會是什麼樣,但計算機之間可以瞬間共享資訊,一秒鐘傳完很多本書。人也能做到。他的說法是,這會把我們變成腦子裡裝著一部電話的存在,而且是瞬時的。

一臺手動打字機開啟的六十年

庫茲韋爾對技術的痴迷,起點是一臺手動打字機。那是外祖母的,老太太寫了一本書,講她母親 1868 年在歐洲創辦的學校。那是歐洲第一所給女孩提供高等教育的學校,一直教到 14 年級。當時女孩能讀到九年級就算幸運,很多人根本沒有受教育的機會。

外祖母把書拿給他看,他對學校的故事毫無興趣,對那臺打字機著了迷。把一張白紙塞進去,打出來的字看起來就像書裡印出來的。而且他能看懂它是怎麼運作的。

“魔術不一樣。如果一個人知道魔術是怎麼變的,魔術就消失了。但這是技術。即使你知道它怎麼運作,魔力還在。”(雷·庫茲韋爾)

他五六歲,還沒有“技術”這個詞。之後他開始在街區裡到處撿零件,從腳踏車上、從壞掉的收音機上。那個年代,五六歲的孩子被允許自己在街區裡亂跑,現在不會了。他撿了一堆零件但不知道怎麼組裝,跟人說只要搞明白怎麼把這些東西拼起來,他就能解決任何問題。他去找那些“很老的大女孩”,大概 10 歲,跟她們說,只要我搞明白這個,我們就能飛,什麼都能做。她們說,你想象力真豐富。

三年級,他八歲,做了一個虛擬現實劇場,人可以上臺揮動手臂,全部由一個控制箱操控,全是機械結構。這個專案在他班上大受歡迎。後來他一路做科學展專案,拿到了西屋科學天才獎(Westinghouse Science Talent Search)。五六歲那年定下的方向,走了六十年。

用現在時描述還不存在的東西

Lex 問他怎麼思考、怎麼保持創造力。庫茲韋爾的回答很具體:把自己放到“你要創造的東西已經存在”的位置上,然後去解釋它怎麼運作。

你先描繪一個你希望存在的世界,假定它已經存在,然後倒推。你甚至要想象自己正在做一場演講,講你是怎麼把它造出來的。這樣你就必須往回推每一步,一直推到這個東西真的能跑起來。這需要想象力,也需要第一性原理的思維。

“當我談論我們想發明的東西時,我會用現在時,就像它已經存在。這不只是給我自己信心,也是給所有一起做這件事的人信心。我們只需要把每一步按順序做出來,讓它成真。”(雷·庫茲韋爾)

這個方法背後有一個更大的主題:時機。庫茲韋爾搞未來學最初的動機非常功利,是給自己的產品定時間表。他 1970 年代做 OCR(光學字元識別),因為 OCR 不需要太多算力。語音識別得等,等到 1980 年代才算力夠用。

同樣的邏輯解釋了為什麼 GPT-3 這一代模型是在兩年前才成立。四年前根本不可行,GPT-2 做出來了,效果不行。非得等算力的指數增長跨過某個門檻。庫茲韋爾說,十億引數的模型不太行,做到一千億引數,效果就相當不錯了,現在大家在往萬億引數走。

用引數來解釋這件事,他的說法很樸素:假設你只有一個引數,想判斷一個東西是不是大象。你就檢測它有沒有鼻子,有鼻子就是大象,沒有就不是。這個辦法能湊合,但你分不清鼻子到底是什麼,別的動物也可能有鼻子,你會非常困惑。一千億個引數意味著它能處理極其複雜的判斷,各種各樣的鼻子。人的引數比這還多一點,但模型已經接近能模擬人類的水平了。未來學本質上是對時機的學習:世界會怎麼演化,某種能力什麼時候才會出現。這個能力後來變成了一件事本身,因為未來圖景里人類生活方式的改變太劇烈,值得單獨講出來。

Danielle 的勇氣

庫茲韋爾的書裡有個角色叫 Danielle,核心特質是勇氣,敢於質疑那些限制人類想象力的假設。Lex 問他,普通人怎麼獲得這種勇氣。

庫茲韋爾的回答是看人們怎麼超越當前的範圍、造出新的東西。他舉了 Uber:在它存在之前,你根本不會覺得這件事可行,而它確實改變了人們工作的方式。Danielle 的做法是,觀察處境,想象怎麼越過各種障礙,然後去做。她還是個很好的溝通者,能把這些想法講給別人聽。

書裡有些很實際的建議:學程式設計、記錄自己的生活、去當物理學家。庫茲韋爾說,這些建議的核心是讓年輕人相信他們可以改變世界。你的頭腦、你的身體可以改變世界,也不要讓別人告訴你不行。Lex 追問了一句“不讓任何人告訴你不行”,庫茲韋爾說,對,就是這樣。

父親的複製品與一個字的答案

庫茲韋爾講了一件他真做過的事。幾年前有一個產品,你問任何問題,它會去讀 20 萬本書,從中找出最能回答你問題的那一句話。他把這個技術用在了另一個方向上:不讀 20 萬本書,只讀一本,那本書是他把父親弗雷德裡克·庫茲韋爾(Frederick Kurzweil)寫過的所有東西收集起來編成的。

他本來不覺得會有效。父親是合唱團和樂隊的指揮,寫的東西多是座位怎麼排、經費怎麼籌這類瑣事,看起來沒什麼意思。真去問的時候,答案出奇地好。他問,最有趣的作曲家是誰?回答是,那當然是勃拉姆斯。然後它會接著說勃拉姆斯有多了不起,以及音樂教育為什麼重要。

於是你可以和父親的複製品對話。庫茲韋爾說,這個對話比和父親本人聊天還有意思。父親本人會操心合唱團排練的座位怎麼排,關注日常瑣事而不是大問題。

Lex 問他有沒有問過“生命的意義是什麼”。問了。父親的回答是一個字:愛。

庫茲韋爾說他想念父親,雖然已經過去 52 年,人會習慣想念。他真正和父親有深入交流,是在父親生命的最後幾年。那時父親生病在家,他有時間跟父親聊音樂和其他事情。他學到的是,父親把自己完全交給了音樂。父親非常害羞,人多的時候往往不怎麼社交,一創作音樂就像變了一個人。Lex 問,你身上有這種東西嗎?庫茲韋爾說,我五歲就投入技術了。那種光,在他身上是另一種形式。

複製品的權利歸誰

Lex 把話題推向一個尖銳的方向:如果有一堆庫茲韋爾的複製品,我花五美元下載一個當朋友,你本人甚至不知道,你會怎麼想?

庫茲韋爾說這不構成問題,他甚至會很享受。Lex 追問,如果那個複製品比我更擅長社交、接管了我的朋友圈,我變成過時的舊版本怎麼辦。庫茲韋爾說,如果別人和一個基於我的複製品相處得很成功,我會為那個“人”感到驕傲,因為它基於我。這就像有孩子,孩子做到了你做不到的事,你會驕傲。Lex 說這仍然是這個版本的一種死亡,庫茲韋爾的回應是,不一定,你還可以活著。

關於權利,庫茲韋爾的態度很明確:應該有法律,創造複製品就必須給它和人類同等的權利。他也承認這在實踐中很複雜。一個複製品和一群複製品,權利怎麼分?如果複製的是一個已經去世的人,他生前的債務和義務怎麼辦?

他看到了推動這件事的真實動力。他提到自己的妻子想“找回”她的父親,她根本不關心權利歸誰,她只想能和一個像父親的存在見面、說說話,那會給她一些安慰。

“愛的人才是決定它成不成的關鍵。如果愛的人不接受,這件事就成不了。”(雷·庫茲韋爾)

庫茲韋爾說,隨著新皮層聯網、我們收集的資料越來越多,可用來重建一個人的材料會越來越多。今天已經有這樣的雛形:一個人去世了,他的推特還在,最後一條推文還在。用大語言模型可以造出一個和他很像、還能繼續交流的存在。庫茲韋爾覺得這很令人興奮。他的說法是:我推故我在。

兩天造出疫苗

庫茲韋爾認為模擬生物學是通往長壽逃逸速度最現實的一條路。他舉的例子是 Moderna 疫苗。他們模擬了數十億種 mRNA 序列對人體的作用,從中挑出最好的,整個過程花了兩天。換成人類來做,可能很多年都做不完,甚至根本做不了。

很多人不喜歡這個疫苗,理由之一是“做得太快了”。庫茲韋爾說,這個“快”其實把測試時間也算進去了,測試花了 10 個月,所以大家覺得,好吧,10 個月就做出來了。序列設計本身只用了兩天。

下一步是把測試也加速。測試比設計複雜,因為人體有很多元件要一起模擬。庫茲韋爾認為這也會到來。最終可能是幾天設計、幾天測試,然後就能針對任何一類醫學上的不足做出應對。治癒疾病、增強身體機能、保健品、藥物,都會走這條路。

Lex 提到 AlphaFold 解蛋白質摺疊問題,庫茲韋爾說這很了不起,方法還是同一套:用的就是打敗圍棋的那類神經網路,只是換了規則。同一套東西,幾天之內在圍棋上超過任何人類,然後被拿去做蛋白質摺疊。人類最好的水平大概只能解出 15% 到 20% 的形狀,AlphaFold 迭代幾次之後接近 100%。

“全是同一套東西。”庫茲韋爾重複了兩遍。

那條畫了八十年的直線

Lex 拿出一張圖:1939 年到 2021 年,每美元每秒計算量,縱軸取對數。圖上是一條直線,也就是說它指的是數增長。

庫茲韋爾強調這條曲線跟英特爾沒關係。第一臺計算機是二戰期間一個德國人做的,德國人沒覺得計算機重要,完全放棄了它。第三臺是英國的計算機,盟軍認真對待,用它破譯了德國密碼,幫英國贏下了不列顛空戰。沒有這臺機器,結果會完全不同。

這條曲線跨過了繼電器、真空管、分立電晶體、積體電路。積體電路大概在圖的中間才開始出現。庫茲韋爾說,過去 80 年,每隔五年左右就有人說這條曲線要完了,說摩爾定律死了。把每一年最快的晶片挑出來畫圖,這條線一直在。它經過了二戰,經過了全球衰退,從來沒停過。

他不喜歡“摩爾定律”這個詞,因為這跟摩爾沒關係,也跟英特爾沒關係。英特爾曾經是關鍵角色,幾年前已經不是最快晶片的製造者了。真正在增長的,是計算本身的指數曲線。

更陡的一條線是神經網路的訓練算力。從 2010 年到 2022 年,橫軸是模型的發表時間,縱軸是訓練用的浮點運算量。這條線大約每六個月翻一倍,比電晶體密度增長還快。因為漲得比成本下降還快,訓練這些模型反而變成了一筆越來越大的投資。

“到 2045 年,我們能夠把智慧放大幾百萬倍。很難想象那會是什麼樣子。”(雷·庫茲韋爾)

這就是“奇點”這個詞的來源。物理學裡的奇點,東西被吸進去之後,外面收不到任何資訊,你不知道里面在發生什麼。技術奇點也一樣:它超出了我們能想象的範圍。

Lex 問了一個有意思的假設:會不會我們根本注意不到自己穿過了奇點,因為認知能力一直在指數增長,快到自己來不及內省?庫茲韋爾說,我們會擁有比現在大得多的理解能力,應該有能力回頭看、理解歷史。他也承認會有大量好玩的東西分散注意力。計算機遊戲已經相當驚人了,未來的娛樂方式只會更多。

六個階段:從粒子到愛

庫茲韋爾把宇宙中資訊處理的歷史分成六個階段。第一階段是物理和化學,宇宙早期大量電子和粒子四處運動,這一段持續了幾十億年。然後是物理化學造出生物和 DNA,資訊的載體收縮到一種分子上。再然後是生物造出大腦。

他說,重要的不只是大腦,還有拇指。大象的腦子比人大,鯨魚的腦子比人大,它們沒造出技術,因為沒有拇指。拇指是人在物理世界裡解謎的關鍵工具。你能看著一棵樹想,我可以把那根樹枝掰下來,去掉葉子,削出一個尖,這就是技術。沒有拇指做不到。

拇指造出了技術,技術也有記憶。這些記憶的規模和範圍正在和人類競爭,最終會超越。然後是人的智慧和技術融合,我們理解人類智慧怎麼運作,把它放進技術裡。技術由我們的智慧啟發,然後在能力上超過我們,我們跟著一起走。

很多人不這麼看。他們看到的是人類和機器對立,人類比不過,故事就結束了。庫茲韋爾舉了李世石(Lee Sedol)的例子。這位曾經的世界最強棋手說他不下圍棋了,因為圍棋對人類來說曾經是智力的極致,現在機器遠遠超過了他,下下去沒有意義。庫茲韋爾說,這在遊戲上也許成立,生活裡不成立,生活裡和 AI 協作的收益很大。

他給了一張更硬的資料:1774 年到 2024 年,人均個人收入按不變美元計算,是一條超線性上升的曲線。如果自動化真的把工作全搶走,這條線不該這樣走。工作人口占總人口的比例也一路上升。它上升的原因,是人類用機器增強了自己的能力,機器和人之間是增強關係,談不上單純的競爭關係。

關於“這次不一樣”的擔心,庫茲韋爾的回答落在一個條件上:看我們能多快和這種智慧融合。如果 GPT-3 這類模型解決了一些核心問題,而人類智慧沒有被增強,那可能是一個負面場景。他相信我們會增強。現在新皮層裡大約有 3 億個模組,這個數字可以乘以 10、100、1000、100 萬。有人會問,做這個有什麼意義?庫茲韋爾的回答是,這就像問一個從沒聽過音樂的人音樂有什麼價值。你沒創造出來,就體會不到。

手機與貧困:兩條被誤讀的曲線

關於貧富差距,庫茲韋爾的類比是手機。今天世界上有 40 億部手機。手機剛出來的時候很貴,只有有錢人買得起,而且那時候功能很差,幾乎什麼都做不了。你要在它又貴又難用的時候買得起,才用得上。讓規模起來、讓價格降下來,本身就是讓它變好的一部分。

現在手機幾百美元就能買到,考慮到它提供的功能,這個價格很低。第三世界很多人物資極少,但有智慧手機。庫茲韋爾說他見過無家可歸的人也有手機。他判斷 AI 會走同樣的軌跡:最終變便宜、變得可負擔。他自己不會第一批往腦子裡裝東西,因為早期版本一定有限制。等它真正成熟,價格也會下來。

書裡還有 50 張圖表,講各個維度在變好。有一張關於極端貧困的民調,問題是:貧困是變多了還是變少了?選項從增加 50% 到減少 50%。70% 的人認為變糟了,88% 的人認為變糟或沒變,只有 1% 的人選了“減少 50%”。正確答案就是減少 50%,只有那 1% 的人答對了。

庫茲韋爾說,幾乎每個領域都是這樣。你不會想回到 100 年前或 50 年前,那時候相當悲慘,只是我們不記得了。識字率在過去幾個世紀裡一路上升,很多國家接近 100%。平均受教育年限大幅上升。預期壽命 1900 年是 48 歲,現在超過 80 歲,而且在出生、1 歲、5 歲、10 歲各個年齡段都在上升,不只是嬰兒死亡率下降帶來的效果。民主的覆蓋面也在擴大,雖然這條路很顛簸,而且可能出現倒退。美國建國至今兩百多年,在人類歷史的尺度上很短,在那之前基本上沒有民主國家。

社交網路加劇了人們對這些趨勢的誤判。庫茲韋爾觀察到,引發強烈分歧的內容會提高參與度,平臺機制天然偏愛分裂。他擔心會有人訓練 AI 去最大化這種分裂。

他真正擔心的三件事

Lex 問,AI 的風險裡哪一件最讓他擔心。庫茲韋爾的回答是“很難選”,然後列了三類。

第一類是社交網路上的錯誤資訊。他自己在書裡專門寫了一章講高階 AI 的危險,虛假資訊是其中一項。

第二類是生物。他給出了一個清晰的風險結構:有些病毒難以傳播但非常危險,有些病毒容易傳播但不那麼危險。如果有人造出既容易傳播又非常危險、而且極難阻止的東西,那就是最壞的情況。更麻煩的是那種感染後長時間沒有症狀的病原體,等所有人都有了,症狀才在一個月後出現。

他說,這種病原體在自然界不會出現,因為如果出現過,人類就不存在了。人類存在這件事本身,就說明自然界沒有既容易傳播又能殺死宿主的病毒。病毒想要的是傳播,同時讓宿主活著。

第三類是奈米技術。庫茲韋爾既興奮又警惕。興奮是因為奈米機器人是連線新皮層的手段:新皮層裡的單元非常小,需要一個足夠小的實體鑽進去建立通訊通道。像 Neuralink 這樣的方案目前頻寬不夠,奈米機器人是高頻寬的解法。這些奈米機器人不需要很聰明,只要能建立一條通訊通道就夠了。它們負責外部計算裝置和生物思考機器之間的通訊。

警惕的是“灰蠱”(grey goo)問題。如果一個奈米機器人能夠自我複製、能夠在自然環境中運作,它就可能把周圍的一切都變成自己,摧毀所有生物。

至於核武器,庫茲韋爾的態度是:儘管烏克蘭戰爭很緊張,包括那座被佔領的核電站,他仍然認為人類不會毀滅自己。1945 年兩顆原子彈之後,77 年過去了,沒有一顆因為憤怒而再次被使用。他說這個記錄“還不錯”,也承認自己確實擔心人們會忘記歷史的教訓。他的判斷是,超級智慧 AI 更可能幫我們渡過難關,前提是我們對這些危險保持警覺。他記得自己小時候做過防核演習,鑽到桌子底下,雙手抱頭。那個姿勢當然沒什麼用,但我們還在這兒。

長壽逃逸速度

Lex 問他怕不怕死。庫茲韋爾的回答是“怕”,然後立刻轉到他自己的框架:長壽逃逸速度(longevity escape velocity)。定義很簡單,讓人類預期壽命每年增加的幅度超過一年。這樣從數學上講,你就不會到達終點。

他說這個目標大概能在這個十年結束前實現,這也是他的目標。他不說“我已經實現永生”,因為“永遠”這個詞沒法兌現。他能說的是,希望活得久、活得好。

他自己就是一個需要折騰身體的例子。40 年前他去墨西哥,感染了沙門氏菌,引發了胰腺炎,造成一種奇怪的糖尿病。它不是 1 型,因為 1 型是自身免疫破壞胰腺,他沒有;也不是 2 型,因為 2 型是胰腺正常工作但細胞吸收胰島素不好,他也不是。他的胰腺受到了一次性損傷,沒有繼續惡化,他學會了怎麼控制。他說自己花了很多時間調自己的身體,讓它繼續跑下去。

關於“死亡是特徵不是缺陷”這個論點,庫茲韋爾的回應很直接:大多數人在抽象層面這麼認為,但只要涉及到他們愛的人的死亡,他們就覺得極其壓抑。他認識這樣的人,二三十年、四十年過去,仍然想把那個人要回來。

“死亡不是值得慶祝的事。我們只是活在一個人們接受了它的世界裡。”(雷·庫茲韋爾)

他說,每當討論到某個人的死亡,哪怕只有一個人死去,那都是巨大的悲劇。一個人活到 100 歲,我們依然愛他,這份愛沒有上限。這些趨勢會給每個人帶來更多機會,即便人口更多。他也承認,自己和將近 100 歲的親戚聊過這件事,只能說我們正在儘快推進,能不能趕上不好講。

五百年後怎麼被記住

Lex 問了一個收尾的問題:500 年後,一個超級智慧 AI 回頭看,會怎麼記得雷·庫茲韋爾這個“版本 0”?在複製品擴散之前的那個人。

庫茲韋爾先開了個玩笑,說他希望自己那時還在。Lex 追問,那還是同一個人嗎?庫茲韋爾反問:我還是我 20 歲、10 歲時的那個人嗎?在同一意義上,是;但我們確實變了。你擁有的關於那個人的全部,是你的記憶,而記憶很可能已經被扭曲。也許你只記得好的部分,也許你專記得壞的部分,看你的心理結構。可他仍然和年輕時的自己保持著某種關係。

他希望被記住的,是他的書裡表達的那些東西:嘗試創造一些人們會接受的新現實。這給他巨大的快樂,也讓他更深入地理解人為什麼有價值。Lex 提到他作品裡貫穿的樂觀主義,庫茲韋爾同意,樂觀本身會為更好的未來鋪路。

最後,Lex 把最初的問題繞了回來。庫茲韋爾問過父親的複製品“生命的意義是什麼”,答案是愛。Lex 問他自己怎麼回答。

庫茲韋爾的回答和他父親一樣。如果沒有愛,如果我們不關心任何人,存在就沒有意義。

“愛是生命的意義。”(雷·庫茲韋爾)

這場對話從 2045 年的奇點開始,中間經過算力曲線、奈米機器人、灰蠱、數字複製品和長壽逃逸速度,最後落在這個詞上。庫茲韋爾談技術時用的都是現在時,彷彿那些東西已經存在。談愛的時候,他用的也是現在時。

  • 把“神經網路訓練算力每六個月翻一倍”當成一個可以查證的事實,而不是一個修辭。任何依賴算力的產品規劃,時間視窗都比直覺短,四年前不可行的東西今天可能剛好可行。
  • 庫茲韋爾的“現在時描述法”可以直接抄:寫下你想做的東西已經存在的樣子,然後倒推每一步,倒推到它能跑起來為止。寫不出來,說明你還沒想清楚。
  • 判斷一項技術會不會普及,看它有沒有走完“又貴又難用,只有富人買”到“幾百美元,人人有”這條路。手機走過,AI 正在走。別在早期版本上投入過重的個人依賴。
  • 關於 AI 風險,別隻盯著“AI 覺醒”。生物病原體和奈米自我複製這兩條線更值得關注,也更缺公共討論。前者已經在現實裡有了技術基礎。
  • 想判斷這個世界在變好還是變壞,別信直覺。極端貧困減少 50% 這件事只有 1% 的人答對。社交平臺會系統性地放大你對壞訊息的感知,去查原始資料再下結論。
  • 如果你關心某個人,別等到能造出複製品的那天。庫茲韋爾說他真正和父親深入交談,是在父親最後幾年。那時他剛好有時間。
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。
By the time he gets to 2045, we'll be able to multiply our intelligence many millions fold. And it's just very hard to imagine what that will be like. The following is a conversation with Ray Kurzweil, author, inventor, and futurist, who has an optimistic view of our future as a human civilization, predicting that exponentially improving technologies will take us to a point of a singularity beyond which superintelligent artificial intelligence will transform our world in nearly unimaginable ways. 18 years ago, in the book Singularity is Near, he predicted that the onset of the singularity will happen in the year 2045. He still holds to this prediction and estimate. In fact, he's working on a new book on this topic that will hopefully be out next year. This is the Lex Friedman podcast. To support it, please check out our sponsors in the description. And now, dear friends, here's Ray Kurzweil. In your 2005 book titled The Singularity is Near, you predicted that the singularity will happen in 2045. So now, 18 years later, do you still estimate that the singularity will happen on 2045? And maybe first, what is the singularity, the technological singularity, and when will it happen? Singularity is where computers really change our view of what's important and change who we are. But we're getting close to some salient things that will change who we are. A key thing is 2029, when computers will pass the Turing test. And there's also some controversy whether the Turing test is valid. I believe it is. Most people do believe that, but there's some controversy about that. But Stanford got very alarmed at my prediction about 2029. I made this in 1999 in my book. The Age of Spiritual Machines. Right. And then you repeated the prediction in 2005. In 2005. Yeah. So they held an international conference, you might have been aware of it, of AI experts in 1999 to assess this view. So people gave different predictions, and they took a poll. It was really the first time that AI experts worldwide were polled on this prediction. And the average poll was 100 years. 20% believed it would never happen. And that was the view in 1999. 80% believed it would happen, but not within their lifetimes. There's been so many advances in AI that the poll of AI experts has come down over the years. So a year ago, something called Meticulous, which you may be aware of, assesses different types of experts on the future. They again assessed what AI experts then felt. And they were saying 2042. For the Turing test. For the Turing test. So it's coming down. And I was still saying 2029. A few weeks ago, they again did another poll, and it was 2030. So AI experts now basically agree with me. I haven't changed at all, I've stayed with 2029. And AI experts now agree with me, but they didn't agree at first. So Alan Turing formulated the Turing test, and... Right, now, what he said was very little about it. I mean, the 1950 paper where he had articulated the Turing test, there's like a few lines that talk about the Turing test. And it really wasn't very clear how to administer it. And he said if they did it in like 15 minutes, that would be sufficient, which I don't really think is the case. These large language models now, some people are convinced by it already. I mean, you can talk to it and have a conversation with it. You can actually talk to it for hours. So it requires a little more depth. There's some problems with large language models which we can talk about. But some people are convinced by the Turing test. Now, if somebody passes the Turing test, what are the implications of that? Does that mean that they're sentient, that they're conscious or not? It's not necessarily clear what the implications are. Anyway, I believe 2029, that's six, seven years from now, we'll have something that passes the Turing test and a valid Turing test, meaning it goes for hours, not just a few minutes. Can you speak to that a little bit? What is your formulation of the Turing test? You've proposed a very difficult version of the Turing test, so what does that look like? Basically, it's just to assess it over several hours and also have a human judge that's fairly sophisticated on what computers can do and can't do. If you take somebody who's not that sophisticated or even an average engineer, they may not really assess various aspects of it. So you really want the human to challenge the system. Exactly, exactly. On its ability to do things like common sense reasoning, perhaps. That's actually a key problem with large language models. They don't do these kinds of tests that would involve assessing chains of reasoning, but you can lose track of that. If you talk to them, they actually can talk to you pretty well and you can be convinced by it, but it's somebody that would really convince you that it's a human, whatever that takes. Maybe it would take days or weeks, but it would really convince you that it's human. Large language models can appear that way. You can read conversations and they appear pretty good. There are some problems with it. It doesn't do math very well. You can ask how many legs did 10 elephants have and they'll tell you, well, okay, each elephant has four legs and it's 10 elephants, so it's 40 legs. And you go, okay, that's pretty good. How many legs do 11 elephants have? And they don't seem to understand the question. Do all humans understand that question? No, that's the key thing. I mean, how advanced a human do you want it to be? But we do expect a human to be able to do multi chain reasoning, to be able to take a few facts and put them together, not perfectly. And we see that in a lot of polls that people don't do that perfectly at all. So it's not very well defined, but it's something where it really would convince you that it's a human. Is your intuition that large language models will not be solely the kind of system that passes the Turing test in 2029? Do we need something else? No, I think it will be a large language model, but they have to go beyond what they're doing now. I think we're getting there. And another key issue is if somebody actually passes the Turing test validly, I would believe they're conscious. And then not everybody would say that. It's okay, we can pass the Turing test, but we don't really believe that it's conscious. That's a whole nother issue. But if it really passes the Turing test, I would believe that it's conscious. But I don't believe that of large language models today. If it appears to be conscious, that's as good as being conscious, at least for you, in some sense. I mean, consciousness is not something that's scientific. I mean, I believe you're conscious, but it's really just a belief, and we believe that about other humans that at least appear to be conscious. When you go outside of shared human assumption, like are animals conscious? Some people believe they're not conscious. Some people believe they are conscious. And would a machine that acts just like a human be conscious? I mean, I believe it would be. But that's really a philosophical belief. You can't prove it. I can't take an entity and prove that it's conscious. There's nothing that you can do that would indicate that. It's like saying a piece of art is beautiful. You can say it. Multiple people can experience a piece of art as beautiful, but you can't prove it. But it's also an extremely important issue. I mean, imagine if you had something where nobody's conscious. The world may as well not exist. And so some people, like say Marvin Minsky, said, well, consciousness is not logical, it's not scientific, and therefore we should dismiss it, and any talk about consciousness is just not to be believed. But when he actually engaged with somebody who was conscious, he actually acted as if they were conscious. He didn't ignore that. He acted as if consciousness does matter. Exactly. Whereas he said it didn't matter. Well, that's Marvin Minsky. Yeah. He's full of contradictions. But that's true of a lot of people as well. But to you, consciousness matters. But to me, it's very important. But I would say it's not a scientific issue. It's a philosophical issue. And people have different views. Some people believe that anything that makes a decision is conscious. So your light switch is conscious. Its level of consciousness is low, not very interesting, but that's a consciousness. So a computer that makes a more interesting decision is still not at human levels, but it's also conscious and at a higher level than your light switch. So that's one view. There's many different views of what consciousness is. So if a system passes the Turing test, it's not scientific, but in issues of philosophy, things like ethics start to enter the picture. Do you think there would be, we would start contending as a human species about the ethics of turning off such a machine? Yeah, I mean, that's definitely come up. Hasn't come up in reality yet. Yet. But I'm talking about 2029. It's not that many years from now. So what are our obligations to it? It has a different, I mean, a computer that's conscious, it has a little bit different connotations than a human. We have a continuous consciousness. We're in an entity that does not last forever. Now, actually, a significant portion of humans still exist and are therefore still conscious. But anybody who is over a certain age doesn't exist anymore. That wouldn't be true of a computer program. You could completely turn it off and a copy of it could be stored and you could recreate it. And so it has a different type of validity. You could actually take it back in time. You could eliminate its memory and have it go over again. I mean, it has a different kind of connotation than humans do. Well, perhaps it can do the same thing with humans. It's just that we don't know how to do that yet. It's possible that we figure out all of these things on the machine first. But that doesn't mean the machine isn't conscious. I mean, if you look at the way people react, say, 3CPO or other machines that are conscious in movies, they don't actually present how it's conscious, but we see that they are a machine and people will believe that they are conscious and they'll actually worry about it if they get into trouble and so on. So 2029 is going to be the first year when a major thing happens. Right. And that will shake our civilization to start to consider the role of AI in this world. Yes and no. I mean, this one guy at Google claimed that the machine was conscious. But that's just one person. Right. When it starts to happen to scale. Well, that's exactly right because most people have not taken that position. I don't take that position. I mean, I've used different things like this and they don't appear to me to be conscious. As we eliminate various problems of these large language models, more and more people will accept that they're conscious. So when we get to 2029, I think a large fraction of people will believe that they're conscious. So it's not gonna happen all at once. I believe it will actually happen gradually and it's already started to happen. And so that takes us one step closer to the singularity. Another step then is in the 2030s when we can actually connect our neocortex, which is where we do our thinking, to computers. And I mean, just as this actually gains a lot to being connected to computers that will amplify its abilities, I mean, if this did not have any connection, it would be pretty stupid. It could not answer any of your questions. If you're just listening to this, by the way, Ray's holding up the all powerful smartphone. So we're gonna do that directly from our brains. I mean, these are pretty good. These already have amplified our intelligence. I'm already much smarter than I would otherwise be if I didn't have this. Because I remember my first book, The Age of Intelligent Machines, there was no way to get information from computers. I actually would go to a library, find a book, find the page that had an information I wanted, and I'd go to the copier, and my most significant information tool was a roll of quarters where I could feed the copier. So we're already greatly advanced that we have these things. There's a few problems with it. First of all, I constantly put it down, and I don't remember where I put it. I've actually never lost it. But you have to find it, and then you have to turn it on. So there's a certain amount of steps. It would actually be quite useful if someone would just listen to your conversation and say, oh, that's so and so actress, and tell you what you're talking about. So going from active to passive, where it just permeates your whole life. Yeah, exactly. The way your brain does when you're awake. Your brain is always there. Right. That's something that could actually just about be done today, where we'd listen to your conversation, understand what you're saying, understand what you're not missing, and give you that information. But another step is to actually go inside your brain. And there are some prototypes where you can connect your brain. They actually don't have the amount of bandwidth that we need. They can work, but they work fairly slowly. So if it actually would connect to your neocortex, and the neocortex, which I describe in How to Create a Mind, the neocortex is actually, it has different levels, and as you go up the levels, it's kind of like a pyramid. The top level is fairly small, and that's the level where you wanna connect these brain extenders. And so I believe that will happen in the 2030s. So just the way this is greatly amplified by being connected to the cloud, we can connect our own brain to the cloud, and just do what we can do by using this machine. Do you think it would look like the brain computer interface of like Neuralink? So would it be? Well, Neuralink, it's an attempt to do that. It doesn't have the bandwidth that we need. Yet, right? Right, but I think, I mean, they're gonna get permission for this because there are a lot of people who absolutely need it because they can't communicate. I know a couple people like that who have ideas and they cannot, they cannot move their muscles and so on. They can't communicate. And so for them, this would be very valuable, but we could all use it. Basically, it'd be, turn us into something that would be like we have a phone, but it would be in our minds. It would be kind of instantaneous. And maybe communication between two people would not require this low bandwidth mechanism of language. Yes, exactly. We don't know what that would be, although we do know that computers can share information like language instantly. They can share many, many books in a second. So we could do that as well. If you look at what our brain does, it actually can manipulate different parameters. So we talk about these large language models. I mean, I had written that it requires a certain amount of information in order to be effective and that we would not see AI really being effective And you fell in love with it in the same way he did with music? Yeah, yeah. I remember this actually happened with my grandmother. She had a manual typewriter and she wrote a book, One Life Is Not Enough, which actually a good title for a book I might write, but it was about a school she had created. Well, actually her mother created it. So my mother's mother's mother created the school in 1868. And it was the first school in Europe that provided higher education for girls. It went through 14th grade. If you were a girl and you were lucky enough to get an education at all, it would go through like ninth grade. And many people didn't have any education as a girl. This went through 14th grade. Her mother created it, she took it over, and the book was about the history of the school and her involvement with it. When she presented it to me, I was not so interested in the story of the school, but I was totally amazed with this manual typewriter. I mean, here is something you could put a blank piece of paper into and you could turn it into something that looked like it came from a book. And you can actually type on it and it looked like it came from a book. It was just amazing to me. And I could see actually how it worked. And I was also interested in magic. But in magic, if somebody actually knows how it works, the magic goes away. The magic doesn't stay there if you actually understand how it works. But here was technology. I didn't have that word when I was five or six. And the magic was still there for you? The magic was still there, even if you knew how it worked. So I became totally interested in this and then went around, collected little pieces of mechanical objects from bicycles, from broken radios. I would go through the neighborhood. This was an era where you would allow five or six year olds to run through the neighborhood and do this. We don't do that anymore. But I didn't know how to put them together. I said, if I could just figure out how to put these things together, I could solve any problem. And I actually remember talking to these very old girls. I think they were 10. And telling them, if I could just figure this out, we could fly, we could do anything. And they said, well, you have quite an imagination. And then when I was in third grade, so I was like eight, created like a virtual reality theater where people could come on stage and they could move their arms. And all of it was controlled through one control box. It was all done with mechanical technology. And it was a big hit in my third grade class. And then I went on to do things in junior high school science fairs and high school science fairs. I won the Westinghouse Science Talent Search. So I mean, I became committed to technology when I was five or six years old. You've talked about how you use lucid dreaming to think, to come up with ideas as a source of creativity. Because you maybe talk through that, maybe the process of how to, you've invented a lot of things. You've came up and thought through some very interesting ideas. What advice would you give, or can you speak to the process of thinking, of how to think, how to think creatively? Well, I mean, sometimes I will think through in a dream and try to interpret that. But I think the key issue that I would tell younger people is to put yourself in the position that what you're trying to create already exists. And then you're explaining, like... How it works. Exactly. That's really interesting. You paint a world that you would like to exist, you think it exists, and reverse engineer that. And then you actually imagine you're giving a speech about how you created this. Well, you'd have to then work backwards as to how you would create it in order to make it work. That's brilliant. And that requires some imagination too, some first principles thinking. You have to visualize that world. That's really interesting. And generally, when I talk about things we're trying to invent, I would use the present tense as if it already exists. Not just to give myself that confidence, but everybody else who's working on it. We just have to kind of do all the steps in order to make it actual. How much of a good idea is about timing? How much is it about your genius versus that its time has come? Timing's very important. I mean, that's really why I got into futurism. I didn't, I wasn't inherently a futurist. That was not really my goal. It's really to figure out when things are feasible. We see that now with large scale models. The very large scale models like GPT3, it started two years ago. Four years ago, it wasn't feasible. In fact, they did create GPT2, which didn't work. So it required a certain amount of timing having to do with this exponential growth of computing power. So futurism in some sense is a study of timing, trying to understand how the world will evolve and when will the capacity for certain ideas emerge. And that's become a thing in itself and to try to time things in the future. But really its original purpose was to time my products. I mean, I did OCR in the 1970s because OCR doesn't require a lot of computation. Optical character recognition. Yeah, so we were able to do that in the 70s and I waited till the 80s to address speech recognition since that requires more computation. So you were thinking through timing when you're developing those things. Yeah. Time come. Yeah. And that's how you've developed that brain power to start to think in a futurist sense when how will the world look like in 2045 and work backwards and how it gets there. But that has to become a thing in itself because looking at what things will be like in the future and the future reflects such dramatic changes in how humans will live that was worth communicating also. So you developed that muscle of predicting the future and then applied broadly and started to discuss how it changes the world of technology, how it changes the world of human life on earth. In Danielle, one of your books, you write about someone who has the courage to question assumptions that limit human imagination to solve problems. And you also give advice on how each of us can have this kind of courage. Well, it's good that you picked that quote because I think that does symbolize what Danielle is about. Courage. So how can each of us have that courage to question assumptions? I mean, we see that when people can go beyond the current realm and create something that's new. I mean, take Uber, for example. Before that existed, you never thought that that would be feasible and it did require changes in the way people work. Is there practical advice as you give in the book about what each of us can do to be a Danielle? Well, she looks at the situation and tries to imagine how she can overcome various obstacles and then she goes for it. And she's a very good communicator so she can communicate these ideas to other people. And there's practical advice of learning to program and recording your life and things of this nature. Become a physicist. So you list a bunch of different suggestions of how to throw yourself into this world. Yeah, I mean, it's kind of an idea how young people can actually change the world by learning all of these different skills. And at the core of that is the belief that you can change the world. That your mind, your body can change the world. Yeah, that's right. And not letting anyone else tell you otherwise. That's really good, exactly. When we upload the story you told about your dad and having a conversation with him, we're talking about uploading your mind to the computer. Do you think we'll have a future with something you call afterlife? We'll have avatars that mimic increasingly better and better our behavior, our appearance, all that kind of stuff. Even those that are perhaps no longer with us. Yes, I mean, we need some information about them. I mean, think about my father. I have what he wrote. Now, he didn't have a word processor, so he didn't actually write that much. And our memories of him aren't perfect. So how do you even know if you've created something that's satisfactory? Now, you could do a Frederick Kurzweil Turing test. It seems like Frederick Kurzweil to me. But the people who remember him, like me, don't have a perfect memory. Is there such a thing as a perfect memory? Maybe the whole point is for him to make you feel a certain way. Yeah, well, I think that would be the goal. And that's the connection we have with loved ones. It's not really based on very strict definition of truth. It's more about the experiences we share. And they get morphed through memory. But ultimately, they make us smile. I think we definitely can do that. And that would be very worthwhile. So do you think we'll have a world of replicants? Of copies? There'll be a bunch of Ray Kurzweils. Like, I could hang out with one. I can download it for five bucks and have a best friend, Ray. And you, the original copy, wouldn't even know about it. Is that, do you think that world is, first of all, do you think that world is feasible? And do you think there's ethical challenges there? Like, how would you feel about me hanging out with Ray Kurzweil and you not knowing about it? It doesn't strike me as a problem. Which you, the original? Would you strike, would that cause a problem for you? No, I would really very much enjoy it. No, not just hang out with me, but if somebody hang out with you, a replicant of you. Well, I think I would start, it sounds exciting, but then what if they start doing better than me and take over my friend group? And then, because they may be an imperfect copy or there may be more social, all these kinds of things, and then I become like the old version that's not nearly as exciting. Maybe they're a copy of the best version of me on a good day. Yeah, but if you hang out with a replicant of me and that turned out to be successful, I'd feel proud of that person because it was based on me. So it's, but it is a kind of death of this version of you. Well, not necessarily. I mean, you can still be alive, right? But, and you would be proud, okay, so it's like having kids and you're proud that they've done even more than you were able to do. Yeah, exactly. It does bring up new issues, but it seems like an opportunity. Well, that replicant should probably have the same rights as you do. Well, that gets into a whole issue because when a replicant occurs, they're not necessarily gonna have your rights. And if a replicant occurs, if it's somebody who's already dead, do they have all the obligations and that the original person had? Do they have all the agreements that they had? I think you're gonna have to have laws that say yes. There has to be, if you wanna create a replicant, they have to have all the same rights as human rights. Well, you don't know. Someone can create a replicant and say, well, it's a replicant, but I didn't bother getting their rights. And so. Yeah, but that would be illegal, I mean. Like if you do that, you have to do that in the black market. If you wanna get an official replicant. Okay, it's not so easy. It's supposed to create multiple replicants. The original rights, maybe for one person and not for a whole group of people. Sure. So there has to be at least one. And then all the other ones kinda share the rights. Yeah, I just don't think that, that's very difficult to conceive for us humans, the idea that this country. You create a replicant that has certain, I mean, I've talked to people about this, including my wife, who would like to get back her father. And she doesn't worry about who has rights to what. She would have somebody that she could visit with and might give her some satisfaction. And she wouldn't care about any of these other rights. What does your wife think about multiple rake or as wells? Have you had that discussion? I haven't addressed that with her. I think ultimately that's an important question, loved ones, how they feel about. There's something about love. Well, that's the key thing, right? If the loved one's rejected, it's not gonna work very well, so. So the loved ones really are the key determinant, whether or not this works or not. But there's also ethical rules. We have to contend with the idea, and we have to contend with that idea with AI. But what's gonna motivate it is, I mean, I talk to people who really miss people who are gone and they would love to get something back, even if it isn't perfect. And that's what's gonna motivate this. And that person lives on in some form. And the more data we have, the more we're able to reconstruct that person and allow them to live on. And eventually as we go forward, we're gonna have more and more of this data because we're gonna have none of us that are inside our neocortex and we're gonna collect a lot of data. In fact, anything that's data is always collected. There is something a little bit sad, which is becoming, or maybe it's hopeful, which is more and more common these days, which when a person passes away, you have their Twitter account, and you have the last tweet they tweeted, like something they needed. And you can recreate them now with large language models and so on. I mean, you can create somebody that's just like them and can actually continue to communicate. I think that's really exciting because I think in some sense, like if I were to die today, in some sense I would continue on if I continued tweeting. I tweet, therefore I am. Yeah, well, I mean, that's one of the advantages of a replicant, they can recreate the communications of that person. Do you hope, do you think, do you hope humans will become a multi planetary species? You've talked about the phases, the six epochs, and one of them is reaching out into the stars in part. Yes, but the kind of attempts we're making now to go to other planetary objects doesn't excite me that much because it's not really advancing anything. It's not efficient enough? Yeah, and we're also putting out other human beings, which is a very inefficient way to explore these other objects. What I'm really talking about in the sixth epoch, the universe wakes up. It's where we can spread our super intelligence throughout the universe. And that doesn't mean sending a very soft, squishy creatures like humans. Yeah, the universe wakes up. I mean, we would send intelligence masses of nanobots which can then go out and colonize these other parts of the universe. Do you think there's intelligent alien civilizations out there that our bots might meet? My hunch is no. Most people say yes, absolutely. I mean, and the universe is too big. And they'll cite the Drake equation. And I think in Singularity is Near, I have two analyses of the Drake equation, both with very reasonable assumptions. And one gives you thousands of advanced civilizations in each galaxy. And another one gives you one civilization. And we know of one. A lot of the analyses are forgetting the exponential growth of computation. Because we've gone from where the fastest way I could send a message to somebody was with a pony, which was what, like a century and a half ago? To the advanced civilization we have today. And if you accept what I've said, go forward a few decades, you can have absolutely fantastic amount of civilization compared to a pony, and that's in a couple hundred years. Yeah, the speed and the scale of information transfer is growing exponentially in a blink of an eye. Now think about these other civilizations. They're gonna be spread out at cosmic times. So if something is like ahead of us or behind us, it could be ahead of us or behind us by maybe millions of years, which isn't that much. I mean, the world is billions of years old, 14 billion or something. So even a thousand years, if two or 300 years is enough to go from a pony to fantastic amount of civilization, we would see that. So of other civilizations that have occurred, okay, some might be behind us, but some might be ahead of us. If they're ahead of us, they're ahead of us by thousands, millions of years, and they would be so far beyond us, they would be doing galaxy wide engineering. But we don't see anything doing galaxy wide engineering. So either they don't exist, or this very universe is a construction of an alien species. We're living inside a video game. Well, that's another explanation that yes, you've got some teenage kids in another civilization. Do you find compelling the simulation hypothesis as a thought experiment that we're living in a simulation? The universe is computational. So we are an example in a computational world. Therefore, it is a simulation. It doesn't necessarily mean an experiment by some high school kid in another world, but it nonetheless is taking place in a computational world. And everything that's going on is basically a form of computation. So you really have to define what you mean by this whole world being a simulation. Well, then it's the teenager that makes the video game. Us humans with our current limited cognitive capability have strived to understand ourselves and we have created religions. We think of God. Whatever that is, do you think God exists? And if so, who is God? I alluded to this before. We started out with lots of particles going around and there's nothing that represents love and creativity. And somehow we've gotten into a world where love actually exists and that has to do actually with consciousness because you can't have love without consciousness. So to me, that's God, the fact that we have something where love, where you can be devoted to someone else and really feel the love, that's God. And if you look at the Old Testament, it was actually created by several different ravenants in there. And I think they've identified three of them. One of them dealt with God as a person that you can make deals with and he gets angry and he wrecks vengeance on various people. But two of them actually talk about God as a symbol of love and peace and harmony and so forth. That's how they describe God. So that's my view of God, not as a person in the sky that you can make deals with. It's whatever the magic that goes from basic elements to things like consciousness and love. Do you think one of the things I find extremely beautiful and powerful is cellular automata, which you also touch on? Do you think whatever the heck happens in cellular automata where interesting, complicated objects emerge, God is in there too? The emergence of love in this seemingly primitive universe? Well, that's the goal of creating a replicant is that they would love you and you would love them. There wouldn't be much point of doing it if that didn't happen. But all of it, I guess what I'm saying about cellular automata is it's primitive building blocks and they somehow create beautiful things. Is there some deep truth to that about how our universe works? Is the emergence from simple rules, beautiful, complex objects can emerge? Is that the thing that made us? Yeah, well. As we went through all the six phases of reality. That's a good way to look at it. It does make some point to the whole value of having a universe. Do you think about your own mortality? Are you afraid of it? Yes, but I keep going back to my idea of being able to expand human life quickly enough in advance of our getting there, longevity escape velocity, which we're not quite at yet, but I think we're actually pretty close, particularly with, for example, doing simulated biology. I think we can probably get there within, say, by the end of this decade, and that's my goal. Do you hope to achieve the longevity escape velocity? Do you hope to achieve immortality? Well, immortality is hard to say. I can't really come on your program saying I've done it. I've achieved immortality because it's never forever. A long time, a long time of living well. But we'd like to actually advance human life expectancy, advance my life expectancy more than a year every year, and I think we can get there within, by the end of this decade. How do you think we'd do it? So there's practical things in Transcend, the nine steps to living well forever, your book. You describe just that. There's practical things like health, exercise, all those things. Yeah, I mean, we live in a body that doesn't last forever. There's no reason why it can't, though, and we're discovering things, I think, that will extend it. But you do have to deal with, I mean, I've got various issues. Went to Mexico 40 years ago, developed salmonella. I created pancreatitis, which gave me a strange form of diabetes. It's not type one diabetes, because it's an autoimmune disorder that destroys your pancreas. I don't have that. But it's also not type two diabetes, because type two diabetes is your pancreas works fine, but your cells don't absorb the insulin well. I don't have that either. The pancreatitis I had partially damaged my pancreas, but it was a one time thing. It didn't continue, and I've learned now how to control it. But so that's just something that I had to do in order to continue to exist. Since your particular biological system, you had to figure out a few hacks, and the idea is that science would be able to do that much better, actually. Yeah, so I mean, I do spend a lot of time just tinkering with my own body to keep it going. So I do think I'll last till the end of this decade, and I think we'll achieve longevity, escape velocity. I think that we'll start with people who are very diligent about this. Eventually, it'll become sort of routine that people will be able to do it. So if you're talking about kids today, or even people in their 20s or 30s, that's really not a very serious problem. I have had some discussions with relatives who are like almost 100, and saying, well, we're working on it as quickly as possible. I don't know if that's gonna work. Is there a case, this is a difficult question, but is there a case to be made against living forever that a finite life, that mortality is a feature, not a bug, that living a shorter, so dying makes ice cream taste delicious, makes life intensely beautiful more than it otherwise might be? Most people believe that way, except if you present a death of anybody they care about or love, they find that extremely depressing. And I know people who feel that way 20, 30, 40 years later, they still want them back. So I mean, death is not something to celebrate, but we've lived in a world where people just accept this. Life is short, you see it all the time on TV, oh, life's short, you have to take advantage of it and nobody accepts the fact that you could actually go beyond normal lifetimes. But anytime we talk about death or a death of a person, even one death is a terrible tragedy. If you have somebody that lives to 100 years old, we still love them in return. And there's no limitation to that. In fact, these kinds of trends are gonna provide greater and greater opportunity for everybody, even if we have more people. So let me ask about an alien species or a super intelligent AI 500 years from now that will look back and remember Ray Kurzweil version zero. Before the replicants spread, how do you hope they remember you in Hitchhiker's Guide to the Galaxy summary of Ray Kurzweil? What do you hope your legacy is? Well, I mean, I do hope to be around, so that's. Some version of you, yes. So. Do you think you'll be the same person around? I mean, am I the same person I was when I was 20 or 10? You would be the same person in that same way, but yes, we're different, we're different. All we have of that, all you have of that person is your memories, which are probably distorted in some way. Maybe you just remember the good parts, depending on your psyche. You might focus on the bad parts, might focus on the good parts. Right, but I mean, I still have a relationship to the way I was when I was earlier, when I was younger. How will you and the other super intelligent AIs remember you of today from 500 years ago? What do you hope to be remembered by this version of you before the singularity? Well, I think it's expressed well in my books, trying to create some new realities that people will accept. I mean, that's something that gives me great pleasure, and greater insight into what makes humans valuable. I'm not the only person who's tempted to comment on that. And optimism that permeates your work. Optimism about the future is ultimately that optimism paves the way for building a better future. Yeah, I agree with that. So you asked your dad about the meaning of life, and he said, love, let me ask you the same question. What's the meaning of life? Why are we here? This beautiful journey that we're on in phase four, reaching for phase five of this evolution and information processing, why? Well, I think I'd give the same answers as my father. Because if there were no love, and we didn't care about anybody, there'd be no point existing. Love is the meaning of life. The AI version of your dad had a good point. Well, I think that's a beautiful way to end it. Ray, thank you for your work. Thank you for being who you are. Thank you for dreaming about a beautiful future and creating it along the way. And thank you so much for spending your really valuable time with me today. This was awesome. It was my pleasure, and you have some great insights, both into me and into humanity as well, so I appreciate that. Thanks for listening to this conversation with Ray Kurzweil. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Isaac Asimov. It is change, continuous change, inevitable change that is the dominant factor in society today. No sensible decision can be made any longer without taking into account not only the world as it is, but the world as it will be. This, in turn, means that our statesmen, our businessmen, our everyman, must take on a science fictional way of thinking. Thank you for listening, and hope to see you next time. until it got to that level. And we had large language models that were like 10 billion bytes, didn't work very well. They finally got to a hundred billion bytes and now they work fairly well. And now we're going to a trillion bytes. If you say lambda has a hundred billion bytes, what does that mean? Well, what if you had something that had one byte, one parameter, maybe you wanna tell whether or not something's an elephant or not. And so you put in something that would detect its trunk. If it has a trunk, it's an elephant. If it doesn't have a trunk, it's not an elephant. That would work fairly well. There's a few problems with it. And it really wouldn't be able to tell what a trunk is, but anyway. And maybe other things other than elephants have trunks, you might get really confused. Yeah, exactly. I'm not sure which animals have trunks, but how do you define a trunk? But yeah, that's one parameter. You can do okay. So these things have a hundred billion parameters. So they're able to deal with very complex issues. All kinds of trunks. Human beings actually have a little bit more than that, but they're getting to the point where they can emulate humans. If we were able to connect this to our neocortex, we would basically add more of these abilities to make distinctions, and it could ultimately be much smarter and also be attached to information that we feel is reliable. So that's where we're headed. So you think that there will be a merger in the 30s, an increasing amount of merging between the human brain and the AI brain? Exactly. And the AI brain is really an emulation of human beings. I mean, that's why we're creating them, because human beings act the same way, and this is basically to amplify them. I mean, this amplifies our brain. It's a little bit clumsy to interact with, but it definitely is way beyond what we had 15 years ago. But the implementation becomes different, just like a bird versus the airplane, even though the AI brain is an emulation, it starts adding features we might not otherwise have, like ability to consume a huge amount of information quickly, like look up thousands of Wikipedia articles in one take. Exactly. I mean, we can get, for example, issues like simulated biology, where it can simulate many different things at once. We already had one example of simulated biology, which is the Moderna vaccine. And that's gonna be now the way in which we create medications. But they were able to simulate what each example of an mRNA would do to a human being, and they were able to simulate that quite reliably. And we actually simulated billions of different mRNA sequences, and they found the ones that were the best, and they created the vaccine. And they did, and talked about doing that quickly, they did that in two days. Now, how long would a human being take to simulate billions of different mRNA sequences? I don't know that we could do it at all, but it would take many years. They did it in two days, and one of the reasons that people didn't like vaccines is because it was done too quickly, it was done too fast. And they actually included the time it took to test it out, which was 10 months, so they figured, okay, it took 10 months to create this. Actually, it took us two days. And we also will be able to ultimately do the tests in a few days as well. Oh, because we can simulate how the body will respond to it. Yeah, that's a little bit more complicated because the body has a lot of different elements, and we have to simulate all of that, but that's coming as well. So ultimately, we could create it in a few days and then test it in a few days, and it would be done. And we can do that with every type of medical insufficiency that we have. So curing all diseases, improving certain functions of the body, supplements, drugs for recreation, for health, for performance, for productivity, all that kind of stuff. Well, that's where we're headed, because I mean, right now we have a very inefficient way of creating these new medications. But we've already shown it, and the Moderna vaccine is actually the best of the vaccines we've had, and it literally took two days to create. And we'll get to the point where we can test it out also quickly. Are you impressed by AlphaFold and the solution to the protein folding, which essentially is simulating, modeling this primitive building block of life, which is a protein, and its 3D shape? It's pretty remarkable that they can actually predict what the 3D shape of these things are, but they did it with the same type of neural net that won, for example, the Go test. So it's all the same. It's all the same. All the same approaches. They took that same thing and just changed the rules to chess, and within a couple of days, it now played a master level of chess greater than any human being. And the same thing then worked for AlphaFold, which no human had done. I mean, human beings could do, the best humans could maybe do 15, 20% of figuring out what the shape would be. And after a few takes, it ultimately did just about 100%. 100%. Do you still think the singularity will happen in 2045? And what does that look like? Once we can amplify our brain with computers directly, which will happen in the 2030s, that's gonna keep growing. That's another whole theme, which is the exponential growth of computing power. Yeah, so looking at price performance of computation from 1939 to 2021. Right, so that starts with the very first computer actually created by a German during World War II. You might have thought that that might be significant, but actually the Germans didn't think computers were significant, and they completely rejected it. The second one is also the ZUSA 2. And by the way, we're looking at a plot with the X axis being the year from 1935 to 2025. And on the Y axis in log scale is computation per second per constant dollar. So dollar normalized inflation. And it's growing linearly on the log scale, which means it's growing exponentially. The third one was the British computer, which the Allies did take very seriously. And it cracked the German code and enables the British to win the Battle of Britain, which otherwise absolutely would not have happened if they hadn't cracked the code using that computer. But that's an exponential graph. So a straight line on that graph is exponential growth. And you see 80 years of exponential growth. And I would say about every five years, and this happened shortly before the pandemic, people saying, well, they call it Moore's law, which is not the correct, because that's not all intel. In fact, this started decades before intel was even created. It wasn't with transistors formed into a grid. So it's not just transistor count or transistor size. Right, it started with relays, then went to vacuum tubes, then went to individual transistors, and then to integrated circuits. And integrated circuits actually starts like in the middle of this graph. And it has nothing to do with intel. Intel actually was a key part of this. But a few years ago, they stopped making the fastest chips. But if you take the fastest chip of any technology in that year, you get this kind of graph. And it's definitely continuing for 80 years. So you don't think Moore's law, broadly defined, is dead. It's been declared dead multiple times throughout this process. I don't like the term Moore's law, because it has nothing to do with Moore or with intel. But yes, the exponential growth of computing is continuing. It has never stopped. From various sources. I mean, it went through World War II, it went through global recessions. It's just continuing. And if you continue that out, along with software gains, which is a whole nother issue, and they really multiply, whatever you get from software gains, you multiply by the computer gains, you get faster and faster speed. This is actually the fastest computer models that have been created. And that actually expands roughly twice a year. Like, every six months it expands by two. So we're looking at a plot from 2010 to 2022. On the x axis is the publication date of the model, and perhaps sometimes the actual paper associated with it. And on the y axis is training, compute, and flops. And so basically this is looking at the increase in the, not transistors, but the computational power of neural networks. Yes, the computational power that created these models. And that's doubled every six months. Which is even faster than transistor division. Yeah. Now actually, since it goes faster than the amount of cost, this has actually become a greater investment to create these. But at any rate, by the time we get to 2045, we'll be able to multiply our intelligence many millions fold. And it's just very hard to imagine what that will be like. And that's the singularity where we can't even imagine. Right, that's why we call it the singularity. Because the singularity in physics, something gets sucked into its singularity and you can't tell what's going on in there because no information can get out of it. There's various problems with that, but that's the idea. It's too much beyond what we can imagine. Do you think it's possible we don't notice that what the singularity actually feels like is we just live through it with exponentially increasing cognitive capabilities and we almost, because everything's moving so quickly, aren't really able to introspect that our life has changed. Yeah, but I mean, we will have that much greater capacity to understand things, so we should be able to look back. Looking at history, understand history. But we will need people, basically like you and me, to actually think about these things. But we might be distracted by all the other sources of entertainment and fun because the exponential power of intellect is growing, but also there'll be a lot of fun. The amount of ways you can have, you know. I mean, we already have a lot of fun with computer games and so on that are really quite remarkable. What do you think about the digital world, the metaverse, virtual reality? Will that have a component in this or will most of our advancement be in physical reality? Well, that's a little bit like Second Life, although the Second Life actually didn't work very well because it couldn't actually handle too many people. And I don't think the metaverse has come to being. I think there will be something like that. It won't necessarily be from that one company. I mean, there's gonna be competitors. But yes, we're gonna live increasingly online, and particularly if our brains are online. I mean, how could we not be online? Do you think it's possible that given this merger with AI, most of our meaningful interactions will be in this virtual world most of our life? We fall in love, we make friends, we come up with ideas, we do collaborations, we have fun. I actually know somebody who's marrying somebody that they never met. I think they just met her briefly before the wedding, but she actually fell in love with this other person, never having met them. And I think the love is real, so. That's a beautiful story, but do you think that story is one that might be experienced as opposed to by hundreds of thousands of people, but instead by hundreds of millions of people? I mean, it really gives you appreciation for these virtual ways of communicating. And if anybody can do it, then it's really not such a freak story. So I think more and more people will do that. But that's turning our back on our entire history of evolution. The old days, we used to fall in love by holding hands and sitting by the fire, that kind of stuff. Here, you're playing. Actually, I have five patents on where you can hold hands, even if you're separated. Great. So the touch, the sense, it's all just senses. It's all just replicated. Yeah, I mean, touch is, it's not just that you're touching someone or not. There's a whole way of doing it, and it's very subtle. But ultimately, we can emulate all of that. Are you excited by that future? Do you worry about that future? I have certain worries about the future, but not virtual touch. Well, I agree with you. You described six stages in the evolution of information processing in the universe, as you started to describe. Can you maybe talk through some of those stages from the physics and chemistry to DNA and brains, and then to the very end, to the very beautiful end of this process? It actually gets more rapid. So physics and chemistry, that's how we started. So the very beginning of the universe. We had lots of electrons and various things traveling around. And that took actually many billions of years, kind of jumping ahead here to kind of some of the last stages where we have things like love and creativity. It's really quite remarkable that that happens. But finally, physics and chemistry created biology and DNA. And now you had actually one type of molecule that described the cutting edge of this process. And we go from physics and chemistry to biology. And finally, biology created brains. I mean, not everything that's created by biology has a brain, but eventually brains came along. And all of this is happening faster and faster. Yeah. It created increasingly complex organisms. Another key thing is actually not just brains, but our thumb. Because there's a lot of animals with brains even bigger than humans. I mean, elephants have a bigger brain. Whales have a bigger brain. But they've not created technology because they don't have a thumb. So that's one of the really key elements in the evolution of humans. This physical manipulator device that's useful for puzzle solving in the physical reality. So I could think, I could look at a tree and go, oh, I could actually trip that branch down and eliminate the leaves and carve a tip on it and I would create technology. And you can't do that if you don't have a thumb. Yeah. So thumbs then created technology and technology also had a memory. And now those memories are competing with the scale and scope of human beings. And ultimately we'll go beyond it. And then we're gonna merge human technology with human intelligence and understand how human intelligence works, which I think we already do. And we're putting that into our human technology. So create the technology inspired by our own intelligence and then that technology supersedes us in terms of its capabilities. And we ride along. Or do you ultimately see it as... And we ride along, but a lot of people don't see that. They say, well, you've got humans and you've got machines and there's no way we can ultimately compete with humans. And you can already see that. Lee Soudal, who's like the best Go player in the world, says he's not gonna play Go anymore. Because playing Go for a human, that was like the ultimate in intelligence because no one else could do that. But now a machine can actually go way beyond him. And so he says, well, there's no point playing it anymore. That may be more true for games than it is for life. I think there's a lot of benefit to working together with AI in regular life. So if you were to put a probability on it, is it more likely that we merge with AI or AI replaces us? A lot of people just think computers come along and they compete with them. We can't really compete and that's the end of it. As opposed to them increasing our abilities. And if you look at most technology, it increases our abilities. I mean, look at the history of work. Look at what people did 100 years ago. Does any of that exist anymore? People, I mean, if you were to predict that all of these jobs would go away and would be done by machines, people would say, well, there's gonna be, no one's gonna have jobs and it's gonna be massive unemployment. But I show in this book that's coming out the amount of people that are working, even as a percentage of the population has gone way up. We're looking at the x axis year from 1774 to 2024 and on the y axis, personal income per capita in constant dollars and it's growing super linearly. I mean, it's 2021 constant dollars and it's gone way up. That's not what you would predict given that we would predict that all these jobs would go away. But the reason it's gone up is because we've basically enhanced our own capabilities by using these machines as opposed to them just competing with us. That's a key way in which we're gonna be able to become far smarter than we are now by increasing the number of different parameters we can consider in making a decision. I was very fortunate, I am very fortunate to be able to get a glimpse preview of your upcoming book, Singularity is Nearer. And one of the themes outside of just discussing the increasing exponential growth of technology, one of the themes is that things are getting better in all aspects of life. And you talked just about this. So one of the things you're saying is with jobs. So let me just ask about that. There is a big concern that automation, especially powerful AI, will get rid of jobs. There are people who lose jobs. And as you were saying, the sense is throughout the history of the 20th century, automation did not do that ultimately. And so the question is, will this time be different? Right, that is the question. Will this time be different? And it really has to do with how quickly we can merge with this type of intelligence. Whether Lambda or GPT3 is out there, and maybe it's overcome some of its key problems, and we really haven't enhanced human intelligence, that might be a negative scenario. But I mean, that's why we create technologies, to enhance ourselves. And I believe we will be enhanced when I'm just going to sit here with 300 million modules in our neocortex. We're going to be able to go beyond that. Because that's useful, but we can multiply that by 10, 100, 1,000, a million. And you might think, well, what's the point of doing that? It's like asking somebody that's never heard music, well, what's the value of music? I mean, you can't appreciate it until you've created it. There's some worry that there'll be a wealth disparity. Class or wealth disparity, only the rich people will be, basically, the rich people will first have access to this kind of thing, and then because of this kind of thing, because the ability to merge will get richer exponentially faster. And I say that's just like cell phones. I mean, there's like four billion cell phones in the world today. In fact, when cell phones first came out, you had to be fairly wealthy. They weren't very inexpensive. So you had to have some wealth in order to afford them. Yeah, there were these big, sexy phones. And they didn't work very well. They did almost nothing. So you can only afford these things if you're wealthy at a point where they really don't work very well. So achieving scale and making it inexpensive is part of making the thing work well. Exactly. So these are not totally cheap, but they're pretty cheap. I mean, you can get them for a few hundred dollars. Especially given the kind of things it provides for you. There's a lot of people in the third world that have very little, but they have a smartphone. Yeah, absolutely. And the same will be true with AI. I mean, I see homeless people have their own cell phones. Yeah, so your sense is any kind of advanced technology will take the same trajectory. Right, it ultimately becomes cheap and will be affordable. I probably would not be the first person to put something in my brain to connect to computers because I think it will have limitations. But once it's really perfected, and at that point it'll be pretty inexpensive, I think it'll be pretty affordable. So in which other ways, as you outline your book, is life getting better? Because I think... Well, I mean, I have 50 charts in there where everything is getting better. I think there's a kind of cynicism about, like even if you look at extreme poverty, for example. For example, this is actually a poll taken on extreme poverty, and people were asked, has poverty gotten better or worse? And the options are increased by 50%, increased by 25%, remain the same, decreased by 25%, decreased by 50%. If you're watching this or listening to this, try to vote for yourself. 70% thought it had gotten worse, and that's the general impression. 88% thought it had gotten worse or remained the same. Only 1% thought it decreased by 50%, and that is the answer. It actually decreased by 50%. So only 1% of people got the right optimistic estimate of how poverty is. Right, and this is the reality, and it's true of almost everything you look at. You don't wanna go back 100 years or 50 years. Things were quite miserable then, but we tend not to remember that. So literacy rate increasing over the past few centuries across all the different nations, nearly to 100% across many of the nations in the world. It's gone way up. Average years of education have gone way up. Life expectancy is also increasing. Life expectancy was 48 in 1900. And it's over 80 now. And it's gonna continue to go up, particularly as we get into more advanced stages of simulated biology. For life expectancy, these trends are the same for at birth, age one, age five, age 10, so it's not just the infant mortality. And I have 50 more graphs in the book about all kinds of things. Even spread of democracy, which might bring up some sort of controversial issues, it still has gone way up. Well, that one has gone way up, but that one is a bumpy road, right? Exactly, and somebody might represent democracy and go backwards, but we basically had no democracies before the creation of the United States, which was a little over two centuries ago, which in the scale of human history isn't that long. Do you think superintelligence systems will help with democracy? So what is democracy? Democracy is giving a voice to the populace and having their ideas, having their beliefs, having their views represented. Well, I hope so. I mean, we've seen social networks can spread conspiracy theories, which have been quite negative, being, for example, being against any kind of stuff that would help your health. So those kinds of ideas have, on social media, what you notice is they increase engagement, so dramatic division increases engagement. Do you worry about AI systems that will learn to maximize that division? I mean, I do have some concerns about this, and I have a chapter in the book about the perils of advanced AI, spreading misinformation on social networks is one of them, but there are many others. What's the one that worries you the most that we should think about to try to avoid? Well, it's hard to choose. We do have the nuclear power that evolved when I was a child, I remember, and we would actually do these drills against a nuclear war. We'd get under our desks and put our hands behind our heads to protect us from a nuclear war. Seems to work, we're still around, so. You're protected. But that's still a concern. And there are key dangerous situations that can take place in biology. Someone could create a virus that's very, I mean, we have viruses that are hard to spread, and they can be very dangerous, and we have viruses that are easy to spread, but they're not so dangerous. Somebody could create something that would be very easy to spread and very dangerous, and be very hard to stop. It could be something that would spread without people noticing, because people could get it, they'd have no symptoms, and then everybody would get it, and then symptoms would occur maybe a month later. So I mean, and that actually doesn't occur normally, because if we were to have a problem with that, we wouldn't exist. So the fact that humans exist means that we don't have viruses that can spread easily and kill us, because otherwise we wouldn't exist. Yeah, viruses don't wanna do that. They want to spread and keep the host alive somewhat. So you can describe various dangers with biology. Also nanotechnology, which we actually haven't experienced yet, but there are people that are creating nanotechnology, and I describe that in the book. Now you're excited by the possibilities of nanotechnology, of nanobots, of being able to do things inside our body, inside our mind, that's going to help. What's exciting, what's terrifying about nanobots? What's exciting is that that's a way to communicate with our neocortex, because each neocortex is pretty small and you need a small entity that can actually get in there and establish a communication channel. And that's gonna really be necessary to connect our brains to AI within ourselves, because otherwise it would be hard for us to compete with it. In a high bandwidth way. Yeah, yeah. And that's key, actually, because a lot of the things like Neuralink are really not high bandwidth yet. So nanobots is the way you achieve high bandwidth. How much intelligence would those nanobots have? Yeah, they don't need a lot, just enough to basically establish a communication channel to one nanobot. So it's primarily about communication. Yeah. Between external computing devices and our biological thinking machine. What worries you about nanobots? Is it similar to with the viruses? Well, I mean, it's the great goo challenge. Yes. If you had a nanobot that wanted to create any kind of entity and repeat itself, and was able to operate in a natural environment, it could turn everything into that entity and basically destroy all biological life. So you mentioned nuclear weapons. Yeah. I'd love to hear your opinion about the 21st century and whether you think we might destroy ourselves. And maybe your opinion, if it has changed by looking at what's going on in Ukraine, that we could have a hot war with nuclear powers involved and the tensions building and the seeming forgetting of how terrifying and destructive nuclear weapons are. Do you think humans might destroy ourselves in the 21st century, and if we do, how? And how do we avoid it? I don't think that's gonna happen despite the terrors of that war. It is a possibility, but I mean, I don't. It's unlikely in your mind. Yeah, even with the tensions we've had with this one nuclear power plant that's been taken over, it's very tense, but I don't actually see a lot of people worrying that that's gonna happen. I think we'll avoid that. We had two nuclear bombs go off in 45, so now we're 77 years later. Yeah, we're doing pretty good. We've never had another one go off through anger. People forget the lessons of history. Well, yeah, I mean, I am worried about it. I mean, that is definitely a challenge. But you believe that we'll make it out and ultimately superintelligent AI will help us make it out as opposed to destroy us. I think so, but we do have to be mindful of these dangers. And there are other dangers besides nuclear weapons, so. So to get back to merging with AI, will we be able to upload our mind in a computer in a way where we might even transcend the constraints of our bodies? So copy our mind into a computer and leave the body behind? Let me describe one thing I've already done with my father. That's a great story. So we created a technology, this is public, came out, I think, six years ago, where you could ask any question and the release product, which I think is still on the market, it would read 200,000 books. And then find the one sentence in 200,000 books that best answered your question. And it's actually quite interesting. You can ask all kinds of questions and you get the best answer in 200,000 books. But I was also able to take it and not go through 200,000 books, but go through a book that I put together, which is basically everything my father had written. So everything he had written, I had gathered, and we created a book, everything that Frederick Herzog had written. Now, I didn't think this actually would work that well because stuff he had written was stuff about how to lay out. I mean, he directed choral groups and music groups, and he would be laying out how the people should, where they should sit and how to fund this and all kinds of things that really didn't seem that interesting. And yet, when you ask a question, it would go through it and it would actually give you a very good answer. So I said, well, who's the most interesting composer? And he said, well, definitely Brahms. And he would go on about how Brahms was fabulous and talk about the importance of music education. So you could have essentially a question and answer, a conversation with him. You could have a conversation with him, which was actually more interesting than talking to him because if you talked to him, he'd be concerned about how they're gonna lay out this property to give a choral group. He'd be concerned about the day to day versus the big questions. Exactly, yeah. And you did ask about the meaning of life and he answered, love. Yeah. Do you miss him? Yes, I do. Yeah, you get used to missing somebody after 52 years, and I didn't really have intelligent conversations with him until later in life. In the last few years, he was sick, which meant he was home a lot and I was actually able to talk to him about different things like music and other things. And so I miss that very much. What did you learn about life from your father? What part of him is with you now? He was devoted to music. And when he would create something to music, it put him in a different world. Otherwise, he was very shy. And if people got together, he tended not to interact with people just because of his shyness. But when he created music, he was like a different person. Do you have that in you? That kind of light that shines? I mean, I got involved with technology at like age five.

本集資源與出處