特別節目·中文精讀

科林·安格爾:iRobot

Colin Angle: iRobot

iRobot 創始人回顧掃地機器人從實驗室走進家庭的過程,以及消費級機器人的商業邏輯。

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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

在美國,銷量第一的吸塵器是 Roomba。

把戴森、胡佛、所有那些需要人推著在屋裡走來走去的機器全算進去,排在第一的是一臺自己會走的圓盤。科林·安格爾(Colin Angle)說這句話的時候自己也覺得好笑:「這真的很瘋狂、很怪。」他創立的 iRobot 成立於 1990 年,到今天 29 年,賣出了 2500 萬臺消費級機器人,進入了大約 10% 的美國家庭。一家機器人公司活了 29 年,這件事本身就稀有。做機器人的公司大多活不下來,活下來的大多也停在 demo 和幾十臺的規模裡。iRobot 活在了幾百萬臺、幾千萬臺裡,活在了真人家的地毯、寵物毛和沙發腿之間。

三定律管不住一臺掃地機,可一臺好的掃地機恰好符合三定律

阿西莫夫 1942 年的短篇《環舞》(Runaround,收錄在《我,機器人》裡)提出了機器人三定律:不傷害人類、服從命令、保護自己。iRobot 這個名字和 Roomba 這個名字都從這本書裡來。所以問題很自然:Roomba 遵守三定律嗎?

科林的回答很實在。三定律要求機器人對世界、對自己行為的後果、對「自我」有極其深刻的理解,這個門檻在未來幾十年內都不會有實際意義。但 Roomba 確實符合三定律:它被設計成幫助人而非傷害人,被設計成本質安全的,被設計成能用很久。它做到這一點,靠的純粹是做一個好產品,跟 AI 或者機器人的「意圖」沒有關係。他說得很清楚,符合三定律,只是恰好和做一個好的機器人產品落在同一條路上。

這個回答裡藏著一種工程師的誠實。很多人談機器人倫理,從原則往下推,推出一堆無法驗證的條款。科林反過來,從一個能在千百萬家庭裡跑起來的物理產品往上推,發現倫理要求落到產品設計上的時候,其實就是安全性、可靠性、壽命這些特別樸素的東西。

我們需要機器人,因為人類的平均年齡在快速上升,而年輕到、矯健到能照顧這些老人的那部分人口,數量是不夠的。(科林·安格爾)

這句話分量最重。他把未來分成兩種:一種是自主生活能力和社會生活水平真的往下掉,另一種是人們對自己的生活有更多掌控,能把時間花在自己選擇的事情上。機器人站在中間,是分水嶺。今天它只是讓你的生活稍微乾淨一點、稍微輕鬆一點,把時間軸往後拉,它決定了你老了以後還能不能一個人住在自己家裡。

從排爆機器人到客廳,一家公司活下來的方式

iRobot 最早做的東西和家務沒關係。它給美國軍方做排爆機器人,那臺叫 PackBot 的機器被扔進過阿富汗和伊拉克的山洞裡,去處理人不想靠近的包裹。它也在「9·11」之後進過世貿中心的廢墟,鑽進人爬不進去的縫隙裡找東西。那一段歷史讓公司活了下來,也讓工程團隊練出了一身本事:機器人得能摔、能翻、能在訊號沒了的時候自己想辦法。

科林在訪談裡沒有展開這段,但這條路徑很值得琢磨。一家機器人公司從高價值、低產量、客戶極少數但要求極苛刻的市場起步,拿到現金流,練出可靠性,然後再把這些能力攤薄到消費級產品上。從幾十臺到幾百萬臺,中間隔著的不是技術躍遷,是成本結構的一次徹底重構。這個順序反過來做基本不可能:先做消費級、指望以後升級到專業級,錢燒完了都等不到那天。

而真正讓他下決心轉向家庭的,是一件特別樸素的事。他說早年間總有人問他,你什麼時候能把我的地板掃了。

我腦子裡有一堆特別好的想法,但好像所有人都想讓地板乾淨一點。所以也許我們該先做這個。(科林·安格爾)

先把地板掃了,掙到做下一件事的權利。這個順序聽起來平凡,實際上是絕大多數機器人公司搞反的地方。

技術不等於生意,那些倒在黎明前的公司

訪談裡主持人列了一串名字:Anki、Jibo、Mayfield Robotics 的 Kuri、Rethink Robotics。這些公司背後都是極聰明的人,做的機器人也上過各種封面,然後在很近的幾年裡相繼關門。

科林的解釋不帶任何安慰成分:技術本身不等於一門生意。

當年我是個造機器人的高科技創業者,直到我變成一個吸塵器推銷員,我們才取得了成功。(科林·安格爾)

他把話說得很直。必須找到一個足夠強的需求,讓機器人交付的價值明顯高於它的成本。這個「明顯」很重要。拿尺子量一量覺得差不多、屏住呼吸也許能成,這種程度不夠,價值要清清楚楚地超過成本。很多機器人產品就卡在這個「差不多」上,投資人和創業者一起屏住呼吸,屏了三五年,氣就沒了。

娛樂型產品更難。他說玩具行業裡,85% 的玩具不管本身多好,都活不到第二個銷售季。就算你做的東西很棒,命中率也不到兩成。社交陪伴機器人、家庭情感機器人這些方向,本質上是在做「除了每週都要做又不想做的家務之外」的事情,那個「魔法般的使用者體驗」到底是什麼,行業還沒想明白。於是最聰明的人做出了最有趣的機器人,使用者價值卻始終模糊,商業上的賬永遠算不清。

他還提到和莊臣(Johnson Wax)合作時學到的方法:進到人家裡,就坐在那兒看人怎麼生活,找出那些他們不喜歡、但做得足夠頻繁、以至於構成負擔的事。有些負擔普遍到人們自己都意識不到它可以被拿掉,得靠外人進去盯著看才能發現。他說,事後回看這些洞察似乎理所當然,當時拿到它們比看起來難得多。

順著這個邏輯往下問,能變成機器人生意的場景有多少?科林的答案是幾乎沒有,我們才剛上路。這個「幾乎」不是悲觀,是清醒。人類家裡需要被自動化的活兒有幾百種,其中同時滿足三個條件的可能只有個位數:幹得比人好、價格比人便宜、買的人自己知道這是個負擔。Roomba 命中了掃地的交集,剩下的空白需要一個個去試。

成本是可以稱出來的

Roomba 要是賣 50 萬美元,就沒人買。幾十年前的機器人成本大致就是這個量級,因為成本主要花在製造它所需的時間上。早期 iRobot 的機器人是鋁做的,科林自己在機加工車間守著銑床,一件一件把零件削出來。

然後他進了玩具行業,看見了一件改變他世界觀的事:當產量足夠大,一臺 Roomba 的成本不再是把銑零件的小時數加起來,改成稱它的重量。

注塑成型把這件事變得徹底。一個任意複雜的塑膠件,成本基本等於那個件裡塑膠的重量。加上今天的三維 CAD 工具,你可以設計一個形狀極其複雜的結構,然後它落地時的價格由材料克數決定。他說這「令人解放」,因為關於製造成本的整個思考方式變了。

這一條值得所有做硬體的人反覆琢磨。機器人在消費市場能不能成,很大程度上由一件和演算法無關的事決定:你能不能把產品塞進一條成熟工業體系的成本函式里。進得去,成本隨規模下降,產品有第二次、第三次迭代的機會;進不去,每臺都是手工品,賣一臺虧一臺,永遠等不到降價的那天。

科林在別的場合提過一個說法,機器人創業真正的門檻不是把東西做出來,是把東西做便宜。做出來靠天才,做便宜靠對製造業的理解,兩種能力經常不長在同一個人身上,這也是很多技術型機器人公司最後死於成本表的原因。

為什麼科林賭視覺,不賭鐳射

感測器是另一個成本函式。很長一段時間裡,科林在琢磨怎麼複製人的皮膚,因為皮膚是極好的感測器。後來他放棄了這條路,轉而問另一個問題:機器人做真實工作要面對的那些麻煩,有多少能用一顆便宜攝像頭加一臺效能過剩的計算機解決?

答案越來越多。摩爾定律還在工作,手機產業每年把更好的處理器、更好的影象感測器推到消費級價格。他說大概兩年前,機器視覺處理器終於便宜到可以裝進消費級機器人裡。他一直在等這個時刻。

所以 iRobot 刻意繞開了鐳射雷達導航,花了好幾年研究純視覺的導航方案。理由很樸素:技術趨勢擺在那兒,你看得見它往哪走,就不該在過渡方案上壓重注。他給出的公式是注塑塑膠加攝像頭,再加一顆能跑機器學習和視覺物體識別的處理器。便宜、夠用、可量產,三樣湊齊,剩下的就是時間。

家裡比馬路更難看清,可撞到你的腳很好笑

自動駕駛行業正在為鐳射雷達和純視覺吵得不可開交。馬斯克(Elon Musk)說過鐳射雷達是柺杖,長期看攝像頭就夠了。

科林的說法是,家庭和馬路在視覺複雜度上朝著相反的兩個方向走。

我的環境其實比汽車行駛的環境難得多。我們沒有道路,我們有 T 恤、有臺階、有近乎無限種花紋、顏色和地面材質。(科林·安格爾)

從視覺角度看,家裡的世界無限可變。馬路至少還有車道線、有交通標誌、有一定的規範性。

安全要求是反過來的。Roomba 不重、不快,撞到你的腳,你的反應是笑。自動駕駛面對的是完全相反的局面:環境相對規範,一次判斷失誤就是人命。所以科林可以毫無保留地說視覺是家庭的未來;對自動駕駛,他相信視覺是終點,但加一個便宜的鐳射雷達作為備份感測器,可能不算最壞的主意。他沒有替別人下結論,只說了兩邊賭注不一樣,思考這個未來有多遠的方式就應該不一樣。

這段話有意思的地方,是把「技術路線之爭」還原成了「約束條件不同」。同一個問題,在不同的物理環境、不同的失敗代價下,最優解本來就不該相同。行業裡很多爭論之所以激烈又無解,是因為雙方在拿各自約束下的答案互相攻擊。

三步走:能用、能看懂家、少一點自主

iRobot 這些年乾的事可以粗暴地分成兩步。第一步,把機器人從實驗室裡能做點事、戰場上能幫士兵幹髒活的狀態,做成能大規模進入家庭、幾個月高強度使用不壞、使用者還喜歡的東西。第二步,讓機器人能感知環境、建圖、定位,把「家」這件事變成一張可以被人類貼上語義標籤的地圖。

然後是第三步,也是科林現在最興奮的部分。他說了一句很反常識的話:他正在努力讓機器人變得「不那麼自主」。

過去三十年他一直在做自主性,做到機器人聰明到不需要人管就能把活幹了。現在的目標是把機器人做成夥伴,一臺自顧自運轉的自動機算不上夥伴。你對它說「我剛剛在廚房冰箱旁邊撒了點麵粉,你能處理一下嗎」,然後正確的事情就發生了。這聽起來是更少的自主,實際上要求更高:它要聽懂你說的話,理解句子的上下文和意圖,把這句話對映到它對家的理解上,再決定做什麼。

這已經是產品了。你現在可以告訴 Roomba 去打掃廚房,它知道廚房在哪,能過去幹這件事。他管這叫 1.0。

再往後是機械臂。他提了一個特別鋒利的問題:如果機器人不知道任何東西在哪,它憑什麼要有手?達塔(Data)有手,羅茜(Rosie)有手,所有科幻裡的機器人都有手,因為有手意味著要在一個環境裡做物理的事。現在機器人開始知道廚房在哪了,接下來會知道冰箱在哪,如果有了手,也許能找到把手、拉開門、給自己拿一瓶啤酒。他說,機器人給你拿啤酒、你坐著看電視,算得上機器人學真正的夢想之一。

這裡有個容易被忽略的因果鏈:機械臂的價值由「機器人對空間的語義理解」決定,機械臂本身的工藝水平起不了決定作用。沒有語義,手就是昂貴的擺設;有了語義,手才突然變得有用。這也解釋了家用機械臂喊了這麼多年一直沒起來的原因:卡住的地方是地圖,手從來不是瓶頸。

隱私這件事,做好人是要吃虧的

機器人要在你家裡到處走、到處看,隱私就是繞不過去的門檻。科林說這對 iRobot 是生死問題,能不能被信任去保護使用者的資料和隱私,直接決定了公司能不能走通它想走的那條路。

他列了幾件已經做的事:公開發布隱私宣言,承諾永遠不出售使用者資料;GDPR 在所有市場執行,法律還沒要求的地區也執行;影象不離開機器人,視覺資料的處理在本地完成,只有經過使用者同意的、關於家的語義資訊才會被上傳;使用者能看到機器人知道什麼,也能要求它忘掉。

他給了一個很具體的選擇權描述。你允許它建一張語義地圖、知道房間在哪,你就可以說「去打掃廚房」;你不想,就別建圖,它照樣會盡力打掃你的家,只是做不到那句話。如果你哪天想讓它忘掉「這是你的廚房」,你可以確信它會照做。

然後是最誠實、也最刺人的一段。他說今天人們對隱私的態度是:出了洩露事件非常憤怒,然後走進商店買最便宜的東西,完全不管那個產品有沒有遵守任何隱私標準。

如果我在 Roomba 的包裝上印上那些隱私承諾,我會賣得比什麼都不印更少。(科林·安格爾)

這句話的資訊量比任何行業報告都大。在當下的市場結構裡,隱私保護是一項負資產,做好人的公司要為此付出銷量代價。所以他認為贏得信任只是必要條件,遠遠不夠。真正需要的是建立一套普通人能看懂、能信任、能在買東西時直接用上的隱私分級標準。他打了個比方,就像肉的等級標準那樣。

有了標準,買家才有一個可以拿來比價的維度,好公司才會因為好行為被獎勵,整個行業才會往前走。現在的局面是,每個公司都在自己的新聞稿裡說自己重視隱私,消費者無從分辨,最後乾脆不看這個維度。而消費者之所以不看,一部分原因在於 AI 和資料收集對大多數人還是黑箱,看不見的東西沒法比較。標準做出來,討論才有可能開始,人們才能問一句,誰在遵守,誰沒有。

機器人越聰明,會越有情緒

關於「Roomba 會不會有一天擁有人類級別的智慧」,科林的答案很乾脆:在他有生之年不會。

他緊接著說,一臺沒有人級別智慧的機器人,也完全可以和你進行一場有意義的對話。對話的物件是誰,決定了這場對話有沒有價值。如果對話是為了哄機器人開心、讓它感覺良好,那在機器人身上裝個按鈕,一按它就笑,效果一樣。如果對話是為了你自己,你想知道今天寵物過得怎麼樣,想知道怎麼讓家裡更省電,想知道去爬珠峰前該瞭解什麼,那就完全可行,而且很有價值。他舉了獨居老人的例子:機器人可以很有效地幫人減少孤獨感,填補那些本來可以用來了解世界的有趣空隙。

他還說了一個自己的理論:機器人越聰明,會越有情緒。

你沒法只靠純邏輯活下去。我們遇到的處境裡,只有極小一部分是能靠邏輯合理解決的。(科林·安格爾)

他的論證是,情緒在資訊不完整的情況下幫人做出合理決定。社交場合資訊不完整,競爭和危險場合也資訊不完整,情緒之所以存在,是因為它有用。當機器人進入同樣的處境,純邏輯不夠用,情緒就成了必需品。

這個觀點和主流想象正好相反。人們通常把情緒當成智慧的對立面,覺得越理性越高階,越接近機器越純粹。科林從工程角度給出的判斷是:情緒是一種在不確定條件下的高效啟發式,是進化給出的近似解,任何要在真實世界裡做決定的智慧體,最終都得有類似的東西。

訪談最後,主持人問他願意和哪個科幻裡的機器人待一天。他選了《星際迷航》裡的達塔,因為達塔很聰明,見過很多事,而且關於情緒和機器人,達塔會有很多話說。主持人追問,如果能問達塔一個問題,並且得到深刻誠實的回答,會問什麼。他的答案讓整場對話落地:「皮卡德(Picard)船長到底是什麼樣的人?」

一個造了 29 年掃地機器人的人,最後想問一個虛構機器人的,是關於另一個人的事。這大概就是他對機器人這件事的真實態度:機器人不用變成人,機器人能做的只是讓人與人之間的東西變得更多一點。

值得帶走的幾條

  • 如果你在做硬體產品,先把成本函式想清楚。問自己一句:量產之後,我的產品定價由零件重量和標準工藝決定,還是由人工裝配的小時數決定?只有前者能隨規模下降,也只有前者能讓你活到第二次迭代。
  • 判斷一個機器人方向是否成立,技術有多酷沒什麼用,要看那個需求是否「明顯」大於成本。勉強打平不算,需要屏住呼吸才能算平的生意,五年內會斷氣。
  • 找需求的方法可以很笨:進到真實場景裡坐著看,看人怎麼生活,找出那些頻繁到成為負擔、普遍到自己都察覺不到的事。這類洞察事後看著理所當然,事前極難拿到,值得花時間。
  • 感測器路線別賭過渡方案。看技術趨勢往哪走,問「三年後這個部件會便宜到什麼程度」,據此設計今天的架構,別挑當下最好用的那個。
  • 如果你的產品涉及使用者資料,別指望靠宣傳隱私贏得市場。當下隱私是負資產,印在包裝上會掉銷量。現實的做法是把處理放在本地、把控制權交給使用者、只上傳必要的最小語義資訊,等行業標準出現時你已經合規。
  • 做自主系統的人可以想一想:使用者真正想要的是他一句話,正確的事就發生了。把「聽懂意圖」當成核心能力來建,比一味提高自動化等級更有價值。
  • 評估機器人公司的護城河,看它對空間的語義理解有多深,別被機械結構的複雜度唬住。手不值錢,知道東西在哪才值錢。
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 Colin Angle. He's the CEO and co founder of iRobot, a robotics company that for 29 years has been creating robots that operate successfully in the real world. Not as a demo or on a scale of dozens, but on a scale of thousands and millions. As of this year, iRobot has sold more than 25 million robots to consumers, including the Roomba vacuum cleaning robot, the Bravo floor mopping robot, and soon the Terra lawn mowing robot. 29 million robots successfully operating autonomously in real people's homes, to me is an incredible accomplishment of science, engineering, logistics, and all kinds of general entrepreneurial innovation. Most robotics companies fail. iRobot has survived and succeeded for 29 years. I spent all day at iRobot, including a long tour and conversation with Colin about the history of iRobot, and then sat down for this podcast conversation that would have been much longer if I didn't spend all day learning about and playing with the various robots and the company's history. I'll release the video of the tour separately. Colin, iRobot, its founding team, its current team, and its mission has been and continues to be an inspiration to me and thousands of engineers who are working hard to create AI systems that help real people. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on iTunes, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F R I D M A N. And now, here's my conversation with Colin Angle. In his 1942 short story, Runaround, from his iRobot collection, Asimov proposed the three laws of robotics in order, don't harm humans, obey orders, protect yourself. So two questions. First, does the Roomba follow these three laws? And also, more seriously, what role do you hope to see robots take in modern society and in the future world? So the three laws are very thought provoking and require such a profound understanding of the world a robot lives in, the ramifications of its action and its own sense of self that it's not a relevant bar, at least it won't be a relevant bar for decades to come. And so if Roomba follows the three laws, and I believe it does, it is designed to help humans, not hurt them, it's designed to be inherently safe, and we designed it to last a long time. It's not through any AI or intent on the robot's part. It's because following the three laws is aligned with being a good robot product. So I guess it does, but not by explicit design. So then the bigger picture, what role do you hope to see robotics, robots take in what's currently mostly a world of humans? We need robots to help us continue to improve our standard of living. We need robots because the average age of humanity is increasing very quickly, and simply the number of people young enough and spry enough to care for the elder growing demographic is inadequate. And so what is the role of robots? Today, the role is to make our lives a little easier, a little cleaner, maybe a little healthier. But in time, robots are going to be the difference between real gut wrenching declines in our ability to live independently and maintain our standard of living, and a future that is the bright one where we have more control over our lives, can spend more of our time focused on activities we choose. And I'm so honored and excited to be playing a role in that journey. So you've given me a tour. It showed me some of the long histories, now 29 years that iRobot has been at it, creating some incredible robots. You showed me Pacbot. You showed me a bunch of other stuff that led up to Roomba, that led to Braava and Terra. So let's skip that incredible history in the interest of time, cause we already talked about it. I'll show this incredible footage. You mentioned elderly and robotics in society. I think the home is a fascinating place for robots to be. So where do you see robots in the home? Currently, I would say, once again, probably most homes in the world don't have a robot. So how do you see that changing? What do you think is the big initial value add that robots can do? So iRobot has sort of, over the years, narrowed in on the home, the consumer's home, as the place where we want to innovate and deliver tools that will help a home be a more automatically maintained place, a healthier place, a safer place, and perhaps even a more efficient place to be. And today, we vacuum, we mop, soon we'll be mowing your lawn. But where things are going is, when do we get to the point where the home, not just the robots that live in your home, but the home itself becomes part of a system that maintains itself and plays an active role in caring for and helping the people live in that home. And I see everything that we're doing as steps along the path toward that future. So what are the steps? So if we can summarize some of the history of Roomba, you've mentioned, and maybe you can elaborate on it, but you mentioned that the early days were really taking a robot from something that works either in the lab or something that works in the field that helps soldiers do the difficult work they do to actually be in the hands of consumers and tens of thousands, hundreds of thousands of robots that don't break down over how much people love them over months of very extensive use. So that was the big first step. And then the second big step was the ability to sense the environment, to build a map, to localize, to be able to build a picture of the home that the human can then attach labels to in terms of giving some semantic knowledge to the robot about its environment. Okay, so that's like a huge, two big, huge steps. Maybe you can comment on them, but also what is the next step of making a robot part of the home? Sure, so the goal is to make a home that takes care of itself, takes care of the people in the home, and gives the user an experience of just living their life and the home is somehow doing the right thing, turning on and off lights when you leave, cleaning up the environment. And we went from robots that were great in the lab, but were both too expensive and not sufficiently capable to ever do an acceptable job of anything other than being a toy or a curio in your home to something that was both affordable and sufficiently effective to drive, be above threshold and drive purchase intent. Now we've disrupted the entire vacuuming industry. The number one selling vacuums, for example, in the US are Roombas, so not robot vacuums, but vacuums, and that's really crazy and weird. We need to pause that. I mean, that's incredible. That's incredible that a robot is the number one selling thing that does something. Yep. Something as essential as vacuuming. Yep. Congratulations. Thank you. It's still kind of fun to say, but just because this was a crazy idea that just started, you know, in a room here, we're like, do you think we can do this? So, hey, let's give it a try. But now the robots are starting to understand their environment. And if you think about the next step, there's two dimensions. I've been working so hard since the beginning of iRobot to make robots are autonomous, that, you know, they're smart enough and understand their task enough, they can just go do it without human involvement. Now what I'm really excited and working on is how do I make them less autonomous? Meaning that the robot is supposed to be your partner, not this automaton that just goes and does what a robot does. And so that if you tell it, hey, I just dropped some flour by the fridge in the kitchen, can you deal with it? Wouldn't it be awesome if the right thing just happened based on that utterance? And to some extent, that's less autonomous because it's actually listening to you, understanding the context and intent of the sentence, mapping it against its understanding of the home it lives in and knowing what to do. And so that's an area of research. It's an area where we're starting to roll out features. You can now tell your robot to clean up the kitchen and it knows what the kitchen is and can do that. And that's sort of 1.0 of where we're going. The other cool thing is that we're starting to know where stuff is. And why is that important? Well, robots are supposed to have arms, right? Data had an arm, Rosie had an arm, Robbie the robot had an arm. I mean, robots are, you know, they are physical things that move around in an environment and they're supposed to like do work. And if you think about it, if a robot doesn't know where anything is, why should it have an arm? But with this new dawn of home understanding that we're starting to go enjoy, I know where the kitchen is. I might in the future know where the refrigerator is. I might, if I had an arm, be able to find the handle, open it and even get myself a beer. Obviously, that's one of the true dreams of robotics is to have robots bringing us a beer while we watch television. But, you know, I think that that new category of tasks where physical manipulation, robot arms, is just a potpourri of new opportunity and excitement. And you see humans as a crucial part of that. So you kind of mentioned that. And I personally find that a really compelling idea. I think full autonomy can only take us so far, especially in the home. So you see humans as helping the robot understand or give deeper meaning to the spatial information. Right. It's a partnership. The robot is supposed to operate according to descriptors that you would use to describe your own home. The robot is supposed to, in lieu of better direction, kind of go about its routine, which ought to be basically right, and lead to a home maintained in a way that it's learned you like, but also be perpetually ready to take direction that would activate a different set of behaviors or actions to meet a current need to the extent it could actually perform that task. So I got to ask you, I think this is a fundamental and a fascinating question, because iRobot has been a successful company and a rare successful robotics company. So Anki, Jibo, Mayfield Robotics with their robot curry, SciFi Works, Rethink Robotics, these are robotics companies that were founded and run by brilliant people. But all, very unfortunately, at least for us roboticists, all went out of business recently. So why do you think they didn't last longer? Why do you think it is so hard to keep a robotics company alive? You know, I say this only partially in jest that back in the day before Roomba, you know, I was a high tech entrepreneur building robots. But it wasn't until I became a vacuum cleaner salesman that we had any success. So, I mean, the point is technology alone doesn't equal a successful business. We need to go and find the compelling need where the robot that we're creating can deliver clearly more value to the end user than it costs. And this is not a marginal thing where you're looking at the scale and you're like, yeah, it's close. Maybe we can hold our breath and make it work. It's clearly more value than the cost of the robot to bring, you know, in the store. And I think that the challenge has been finding those businesses where that's true in a sustainable fashion. You know, when you get into entertainment style things, you could be the cat's meow one year, but 85% of toys, regardless of their merit, fail to make it to their second season. It's just super hard to do so. And so that's just a tough business. And there has been a lot of experimentation around what is the right type of social companion, what is the right robot in the home that is doing something other than tasks people do every week that they'd rather not do. And I'm not sure we've got it all figured out right. And so that you get brilliant roboticists with super interesting robots that ultimately don't quite have that magical user experience and thus that value benefit equation remains ambiguous. So you as somebody who dreams of robots changing the world, what's your estimate? How big is the space of applications that fit the criteria that you just described where you can really demonstrate an obvious significant value over the alternative non robotic solution? Well, I think that we're just about none of the way to achieving the potential of robotics at home. But we have to do it in a really eyes wide open, honest fashion. And so another way to put that is the potential is infinite because we did take a few steps, but you're saying those steps are just very initial steps. So the Roomba is a hugely successful product, but you're saying that's just the very, very beginning. That's just the very, very beginning. It's the foot in the door. And I think I was lucky that in the early days of robotics, people would ask me, when are you going to clean my floor? It was something that I grew up saying, I got all these really good ideas, but everyone seems to want their floor clean. And so maybe we should do that. Yeah, your good ideas. Earn the right to do the next thing after that. So the good ideas have to match with the desire of the people and then the actual cost has to like the business, the financial aspect has to all match together. Yeah, during our partnership back a number of years ago with Johnson Wax, they would explain to me that they would go into homes and just watch how people lived and try to figure out what were they doing that they really didn't really like to do, but they had to do it frequently enough that it was top of mind and understood as a burden. Hey, let's make a product or come up with a solution to make that pain point less challenging. And sometimes we do certain burdens so often as a society that we actually don't even realize, like it's actually hard to see that that burden is something that could be removed. So it does require just going into the home and staring at, wait, how do I actually live life? What are the pain points? Yeah, and getting those insights is a lot harder than it would seem it should be in retrospect. So how hard on that point? I mean, one of the big challenges of robotics is driving the cost down to something that consumers, people would afford. So people would be less likely to buy a Roomba if it cost $500,000, which is probably sort of what a Roomba would cost several decades ago. So how do you drive, which I mentioned is very difficult, how do you drive the cost of a Roomba or a robot down such that people would want to buy it? When I started building robots, the cost of the robot had a lot to do with the amount of time it took to build it. And so that we build our robots out of aluminum, I would go spend my time in the machine shop on the milling machine, cutting out the parts and so forth. And then when we got into the toy industry, I realized that if we were building at scale, I could determine the cost of the Roomba instead of adding up all the hours to mill out the parts, but by weighing it. And that's liberating. You can say, wow, the world has just changed as I think about construction in a different way. The 3D CAD tools that are available to us today, the operating at scale where I can do tooling and injection mold, an arbitrarily complicated part, and the cost is going to be basically the weight of the plastic in that part, is incredibly exciting and liberating and opens up all sorts of opportunities. And for the sensing part of it, where we are today is instead of trying to build skin, which is really hard. For a long time, I spent creating strategies and ideas around how could we duplicate the skin on the human body because it's such an amazing sensor. Instead of going down that path, why don't we focus on vision? And how many of the problems that face a robot trying to do real work could be solved with a cheap camera and a big ass computer? Moore's law continues to work. The cell phone industry, the mobile industry is giving us better and better tools that can run on these embedded computers. And I think we passed an important moment maybe two years ago where you could put machine vision capable processors on robots at consumer price points. And I was waiting for it to happen. We avoided putting lasers on our robots to do navigation and instead spent years researching how to do vision based navigation because you could just see where these technology trends were going. And between injection molded plastic and a camera with a computer capable of running machine learning and visual object recognition, I could build an incredibly affordable, incredibly capable robot. And that's going to be the future. So on that point with a small tangent, but I think an important one, another industry in which I would say the only other industry in which there is automation actually touching people's lives today is autonomous vehicles. What the vision you just described of using computer vision and using cheap camera sensors, there's a debate on that of LIDAR versus computer vision. And the Elon Musk famously said that LIDAR is a crutch that really in the long term, camera only is the right solution, which echoes some of the ideas you're expressing. Of course, the domain in terms of its safety criticality is different. But what do you think about that approach in the autonomous vehicle space? And in general, do you see a connection between the incredible real world challenges you have to solve in the home with Roomba? And I saw a demonstration of some of them, corner cases literally, and autonomous vehicles. So there's absolutely a tremendous overlap between both the problems a robot vacuum and an autonomous vehicle are trying to solve and the tools and the types of sensors that are being applied in the pursuit of the solutions. In my world, my environment is actually much harder than the environment an automobile travels. We don't have roads. We have t shirts. We have steps. We have a near infinite number of patterns and colors and surface textures on the floor. Especially from a visual perspective. So the way the world looks is an infinitely variable. On the other hand, safety is way easier on the inside. My robots, they're not very heavy. They're not very fast. If they bump into your foot, you think it's funny. And autonomous vehicles kind of have the inverse problem. And so that for me saying vision is the future, I can say that without reservation. For autonomous vehicles, I think I believe what Elon's saying about the future is ultimately going to be vision. Maybe if we put a cheap lighter on there as a backup sensor, it might not be the worst idea in the world. So the stakes are much higher. The stakes are much higher. You have to be much more careful thinking through how far away that future is. Right. But I think that the primary environmental understanding sensor is going to be a visual system. Visual system. So on that point, well, let me ask, do you hope there's an iRobot robot in every home in the world one day? I expect there to be at least one iRobot robot in every home. We've sold 25 million robots. So we're in about 10% of US homes, which is a great start. But I think that when we think about the numbers of things that robots can do, today I can vacuum your floor, mop your floor, cut your lawn, or soon we'll be able to cut your lawn. But there are more things that we could do in the home. And I hope that we continue using the techniques I described around exploiting computer vision and low cost manufacturing that we'll be able to create these solutions at affordable price points. So let me ask on that point of a robot in every home, that's my dream as well. I'd love to see that. I think the possibilities there are indeed infinite positive possibilities. But in our current culture, no thanks to science fiction and so on, there's a serious kind of hesitation, anxiety, concern about robots, and also a concern about privacy. And it's a fascinating question to me why that concern is amongst a certain group of people is as intense as it is. So you have to think about it because it's a serious concern. But I wonder how you address it best. So from a perspective of vision sensors, so robots that move about the home and sense the world, how do you alleviate people's privacy concerns? How do you make sure that they can trust iRobot and the robots that they share their home with? I think that's a great question. And we've really leaned way forward on this because given our vision as to the role the company intends to play in the home, really for us, make or break is can our approach be trusted to protecting the data and the privacy of the people who have our robots? And so we've gone out publicly with a privacy manifesto stating we'll never sell your data. We've adopted GDPR not just where GDPR is required, but globally. We have ensured that images don't leave the robot. So processing data from the visual sensors happens locally on the robot. And only semantic knowledge of the home with the consumer's consent is sent up. We show you what we know and are trying to go use data as an enabler for the performance of the robots with the informed consent and understanding of the people who own those robots. We take it very seriously. And ultimately, we think that by showing a customer that if you let us build a semantic map of your home and know where the rooms are, well, then you can say clean the kitchen. If you don't want the robot to do that, don't make the map. It'll do its best job cleaning your home. But it won't be able to do that. And if you ever want us to forget that we know that it's your kitchen, you can have confidence that we will do that for you. So we're trying to go and be a data 2.0 perspective company where we treat the data that the robots have of the consumer's home as if it were the consumer's data and that they have rights to it. So we think by being the good guys on this front, we can build the trust and thus be entrusted to enable robots to do more things that are thoughtful. You think people's worries will diminish over time? As a society, broadly speaking, do you think you can win over trust not just for the company, but just the comfort that people have with AI in their home enriching their lives in some way? I think we're in an interesting place today where it's less about winning them over and more about finding a way to talk about privacy in a way that more people can understand. I would tell you that today, when there's a privacy breach, people get very upset and then go to the store and buy the cheapest thing, paying no attention to whether or not the products that they're buying honor privacy standards or not. In fact, if I put on the package of my Roomba, the privacy commitments that we have, I would sell less than I would if I did nothing at all. And that needs to change. So it's not a question about earning trust. I think that's necessary but not sufficient. We need to figure out how to have a comfortable set of what is the grade A meat standard applied to privacy that customers can trust and understand and then use in their buying decisions. That will reward companies for good behavior and that will ultimately be how this moves forward. And maybe be part of the conversation between regular people about what it means, what privacy means. If you have some standards, you can say, you can start talking about who's following them, who does not have more. Because most people are actually quite clueless about all aspects of artificial intelligence, the data collection, and so on. It would be nice to change that for people to understand the good that AI can do. And it's not some system that's trying to steal all the most sensitive data. Do you think, do you dream of a Roomba with human level intelligence one day? So you've mentioned a very successful localization and mapping of the environment, being able to do some basic communication to say, go clean the kitchen. Do you see in your maybe more bored moments, once you get the beer, to sit back with that beer and have a chat on a Friday night with a Roomba about how your day went? So to your latter question, absolutely. To your former question as to whether a Roomba can have human level intelligence, not in my lifetime. You can have you. I think you can have a great conversation, a meaningful conversation with a Roomba without it having anything that resembles human level intelligence. And I think that as long as you realize that conversation is not about the robot and making the robot feel good. That conversation is about you learning interesting things that make you feel like the conversation that you had with the robot is a pretty awesome way of learning something. And it could be about what kind of day your pet had. It could be about how can I make my home more energy efficient. It could be about if I'm thinking about climbing Mount Everest, what should I know? And that's a very doable thing. But if I think that that conversation I'm going to have with the robot is I'm going to be rewarded by making the robot happy, well, I could just put a button on the robot that you could push and the robot would smile. And that sort of thing. So I think you need to think about the question in the right way. And robots can be awesomely effective at helping people feel less isolated, learn more about the home that they live in, and fill some of those lonely gaps that we wish we were engaged learning cool stuff about our world. Last question. If you could hang out for a day with a robot from science fiction, movies, books, and safely pick its brain for that day, who would you pick? Data. Data. From Star Trek. I think that A, data is really smart. Data has been through a lot trying to go and save the galaxy. And I'm really interested actually in emotion and robotics. And I think you'd have a lot to say about that. Because I believe actually that emotion plays an incredibly useful role in doing reasonable things in situations where we have imperfect understanding of what's going on. In social situations when there's imperfect information. In social situations, also in competitive or dangerous situations that we have emotion for a reason. And so that ultimately, my theory is that as robots get smarter and smarter, they're actually going to get more emotional. Because you can't actually survive on pure logic. Because only a very tiny fraction of the situations we find ourselves in can be resolved reasonably with logic. And so I think Data would have a lot to say about that. And so I could find out whether he agrees. If you could ask Data one question, you would get a deep, honest answer to what would you ask. What's Captain Picard really like? OK, I think that's the perfect way to end it. Colin, thank you so much for talking today. I really appreciate it. My pleasure.

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