中文精读由 AI 基于原始访谈改写,仅供学习参考。
在美国,销量第一的吸尘器是 Roomba。
把戴森、胡佛、所有那些需要人推着在屋里走来走去的机器全算进去,排在第一的是一台自己会走的圆盘。科林·安格尔(Colin Angle)说这句话的时候自己也觉得好笑:「这真的很疯狂、很怪。」他创立的 iRobot 成立于 1990 年,到今天 29 年,卖出了 2500 万台消费级机器人,进入了大约 10% 的美国家庭。一家机器人公司活了 29 年,这件事本身就稀有。做机器人的公司大多活不下来,活下来的大多也停在 demo 和几十台的规模里。iRobot 活在了几百万台、几千万台里,活在了真人家的地毯、宠物毛和沙发腿之间。
三定律管不住一台扫地机,可一台好的扫地机恰好符合三定律
阿西莫夫 1942 年的短篇《环舞》(Runaround,收录在《我,机器人》里)提出了机器人三定律:不伤害人类、服从命令、保护自己。iRobot 这个名字和 Roomba 这个名字都从这本书里来。所以问题很自然:Roomba 遵守三定律吗?
科林的回答很实在。三定律要求机器人对世界、对自己行为的后果、对「自我」有极其深刻的理解,这个门槛在未来几十年内都不会有实际意义。但 Roomba 确实符合三定律:它被设计成帮助人而非伤害人,被设计成本质安全的,被设计成能用很久。它做到这一点,靠的纯粹是做一个好产品,跟 AI 或者机器人的「意图」没有关系。他说得很清楚,符合三定律,只是恰好和做一个好的机器人产品落在同一条路上。
这个回答里藏着一种工程师的诚实。很多人谈机器人伦理,从原则往下推,推出一堆无法验证的条款。科林反过来,从一个能在千百万家庭里跑起来的物理产品往上推,发现伦理要求落到产品设计上的时候,其实就是安全性、可靠性、寿命这些特别朴素的东西。
我们需要机器人,因为人类的平均年龄在快速上升,而年轻到、矫健到能照顾这些老人的那部分人口,数量是不够的。(科林·安格尔)
这句话分量最重。他把未来分成两种:一种是自主生活能力和社会生活水平真的往下掉,另一种是人们对自己的生活有更多掌控,能把时间花在自己选择的事情上。机器人站在中间,是分水岭。今天它只是让你的生活稍微干净一点、稍微轻松一点,把时间轴往后拉,它决定了你老了以后还能不能一个人住在自己家里。
从排爆机器人到客厅,一家公司活下来的方式
iRobot 最早做的东西和家务没关系。它给美国军方做排爆机器人,那台叫 PackBot 的机器被扔进过阿富汗和伊拉克的山洞里,去处理人不想靠近的包裹。它也在「9·11」之后进过世贸中心的废墟,钻进人爬不进去的缝隙里找东西。那一段历史让公司活了下来,也让工程团队练出了一身本事:机器人得能摔、能翻、能在信号没了的时候自己想办法。
科林在访谈里没有展开这段,但这条路径很值得琢磨。一家机器人公司从高价值、低产量、客户极少数但要求极苛刻的市场起步,拿到现金流,练出可靠性,然后再把这些能力摊薄到消费级产品上。从几十台到几百万台,中间隔着的不是技术跃迁,是成本结构的一次彻底重构。这个顺序反过来做基本不可能:先做消费级、指望以后升级到专业级,钱烧完了都等不到那天。
而真正让他下决心转向家庭的,是一件特别朴素的事。他说早年间总有人问他,你什么时候能把我的地板扫了。
我脑子里有一堆特别好的想法,但好像所有人都想让地板干净一点。所以也许我们该先做这个。(科林·安格尔)
先把地板扫了,挣到做下一件事的权利。这个顺序听起来平凡,实际上是绝大多数机器人公司搞反的地方。
技术不等于生意,那些倒在黎明前的公司
访谈里主持人列了一串名字:Anki、Jibo、Mayfield Robotics 的 Kuri、Rethink Robotics。这些公司背后都是极聪明的人,做的机器人也上过各种封面,然后在很近的几年里相继关门。
科林的解释不带任何安慰成分:技术本身不等于一门生意。
当年我是个造机器人的高科技创业者,直到我变成一个吸尘器推销员,我们才取得了成功。(科林·安格尔)
他把话说得很直。必须找到一个足够强的需求,让机器人交付的价值明显高于它的成本。这个「明显」很重要。拿尺子量一量觉得差不多、屏住呼吸也许能成,这种程度不够,价值要清清楚楚地超过成本。很多机器人产品就卡在这个「差不多」上,投资人和创业者一起屏住呼吸,屏了三五年,气就没了。
娱乐型产品更难。他说玩具行业里,85% 的玩具不管本身多好,都活不到第二个销售季。就算你做的东西很棒,命中率也不到两成。社交陪伴机器人、家庭情感机器人这些方向,本质上是在做「除了每周都要做又不想做的家务之外」的事情,那个「魔法般的用户体验」到底是什么,行业还没想明白。于是最聪明的人做出了最有趣的机器人,用户价值却始终模糊,商业上的账永远算不清。
他还提到和庄臣(Johnson Wax)合作时学到的方法:进到人家里,就坐在那儿看人怎么生活,找出那些他们不喜欢、但做得足够频繁、以至于构成负担的事。有些负担普遍到人们自己都意识不到它可以被拿掉,得靠外人进去盯着看才能发现。他说,事后回看这些洞察似乎理所当然,当时拿到它们比看起来难得多。
顺着这个逻辑往下问,能变成机器人生意的场景有多少?科林的答案是几乎没有,我们才刚上路。这个「几乎」不是悲观,是清醒。人类家里需要被自动化的活儿有几百种,其中同时满足三个条件的可能只有个位数:干得比人好、价格比人便宜、买的人自己知道这是个负担。Roomba 命中了扫地的交集,剩下的空白需要一个个去试。
成本是可以称出来的
Roomba 要是卖 50 万美元,就没人买。几十年前的机器人成本大致就是这个量级,因为成本主要花在制造它所需的时间上。早期 iRobot 的机器人是铝做的,科林自己在机加工车间守着铣床,一件一件把零件削出来。
然后他进了玩具行业,看见了一件改变他世界观的事:当产量足够大,一台 Roomba 的成本不再是把铣零件的小时数加起来,改成称它的重量。
注塑成型把这件事变得彻底。一个任意复杂的塑料件,成本基本等于那个件里塑料的重量。加上今天的三维 CAD 工具,你可以设计一个形状极其复杂的结构,然后它落地时的价格由材料克数决定。他说这「令人解放」,因为关于制造成本的整个思考方式变了。
这一条值得所有做硬件的人反复琢磨。机器人在消费市场能不能成,很大程度上由一件和算法无关的事决定:你能不能把产品塞进一条成熟工业体系的成本函数里。进得去,成本随规模下降,产品有第二次、第三次迭代的机会;进不去,每台都是手工品,卖一台亏一台,永远等不到降价的那天。
科林在别的场合提过一个说法,机器人创业真正的门槛不是把东西做出来,是把东西做便宜。做出来靠天才,做便宜靠对制造业的理解,两种能力经常不长在同一个人身上,这也是很多技术型机器人公司最后死于成本表的原因。
为什么科林赌视觉,不赌激光
传感器是另一个成本函数。很长一段时间里,科林在琢磨怎么复制人的皮肤,因为皮肤是极好的传感器。后来他放弃了这条路,转而问另一个问题:机器人做真实工作要面对的那些麻烦,有多少能用一颗便宜摄像头加一台性能过剩的计算机解决?
答案越来越多。摩尔定律还在工作,手机产业每年把更好的处理器、更好的图像传感器推到消费级价格。他说大概两年前,机器视觉处理器终于便宜到可以装进消费级机器人里。他一直在等这个时刻。
所以 iRobot 刻意绕开了激光雷达导航,花了好几年研究纯视觉的导航方案。理由很朴素:技术趋势摆在那儿,你看得见它往哪走,就不该在过渡方案上压重注。他给出的公式是注塑塑料加摄像头,再加一颗能跑机器学习和视觉物体识别的处理器。便宜、够用、可量产,三样凑齐,剩下的就是时间。
家里比马路更难看清,可撞到你的脚很好笑
自动驾驶行业正在为激光雷达和纯视觉吵得不可开交。马斯克(Elon Musk)说过激光雷达是拐杖,长期看摄像头就够了。
科林的说法是,家庭和马路在视觉复杂度上朝着相反的两个方向走。
我的环境其实比汽车行驶的环境难得多。我们没有道路,我们有 T 恤、有台阶、有近乎无限种花纹、颜色和地面材质。(科林·安格尔)
从视觉角度看,家里的世界无限可变。马路至少还有车道线、有交通标志、有一定的规范性。
安全要求是反过来的。Roomba 不重、不快,撞到你的脚,你的反应是笑。自动驾驶面对的是完全相反的局面:环境相对规范,一次判断失误就是人命。所以科林可以毫无保留地说视觉是家庭的未来;对自动驾驶,他相信视觉是终点,但加一个便宜的激光雷达作为备份传感器,可能不算最坏的主意。他没有替别人下结论,只说了两边赌注不一样,思考这个未来有多远的方式就应该不一样。
这段话有意思的地方,是把「技术路线之争」还原成了「约束条件不同」。同一个问题,在不同的物理环境、不同的失败代价下,最优解本来就不该相同。行业里很多争论之所以激烈又无解,是因为双方在拿各自约束下的答案互相攻击。
三步走:能用、能看懂家、少一点自主
iRobot 这些年干的事可以粗暴地分成两步。第一步,把机器人从实验室里能做点事、战场上能帮士兵干脏活的状态,做成能大规模进入家庭、几个月高强度使用不坏、用户还喜欢的东西。第二步,让机器人能感知环境、建图、定位,把「家」这件事变成一张可以被人类贴上语义标签的地图。
然后是第三步,也是科林现在最兴奋的部分。他说了一句很反常识的话:他正在努力让机器人变得「不那么自主」。
过去三十年他一直在做自主性,做到机器人聪明到不需要人管就能把活干了。现在的目标是把机器人做成伙伴,一台自顾自运转的自动机算不上伙伴。你对它说「我刚刚在厨房冰箱旁边撒了点面粉,你能处理一下吗」,然后正确的事情就发生了。这听起来是更少的自主,实际上要求更高:它要听懂你说的话,理解句子的上下文和意图,把这句话映射到它对家的理解上,再决定做什么。
这已经是产品了。你现在可以告诉 Roomba 去打扫厨房,它知道厨房在哪,能过去干这件事。他管这叫 1.0。
再往后是机械臂。他提了一个特别锋利的问题:如果机器人不知道任何东西在哪,它凭什么要有手?达塔(Data)有手,罗茜(Rosie)有手,所有科幻里的机器人都有手,因为有手意味着要在一个环境里做物理的事。现在机器人开始知道厨房在哪了,接下来会知道冰箱在哪,如果有了手,也许能找到把手、拉开门、给自己拿一瓶啤酒。他说,机器人给你拿啤酒、你坐着看电视,算得上机器人学真正的梦想之一。
这里有个容易被忽略的因果链:机械臂的价值由「机器人对空间的语义理解」决定,机械臂本身的工艺水平起不了决定作用。没有语义,手就是昂贵的摆设;有了语义,手才突然变得有用。这也解释了家用机械臂喊了这么多年一直没起来的原因:卡住的地方是地图,手从来不是瓶颈。
隐私这件事,做好人是要吃亏的
机器人要在你家里到处走、到处看,隐私就是绕不过去的门槛。科林说这对 iRobot 是生死问题,能不能被信任去保护用户的数据和隐私,直接决定了公司能不能走通它想走的那条路。
他列了几件已经做的事:公开发布隐私宣言,承诺永远不出售用户数据;GDPR 在所有市场执行,法律还没要求的地区也执行;图像不离开机器人,视觉数据的处理在本地完成,只有经过用户同意的、关于家的语义信息才会被上传;用户能看到机器人知道什么,也能要求它忘掉。
他给了一个很具体的选择权描述。你允许它建一张语义地图、知道房间在哪,你就可以说「去打扫厨房」;你不想,就别建图,它照样会尽力打扫你的家,只是做不到那句话。如果你哪天想让它忘掉「这是你的厨房」,你可以确信它会照做。
然后是最诚实、也最刺人的一段。他说今天人们对隐私的态度是:出了泄露事件非常愤怒,然后走进商店买最便宜的东西,完全不管那个产品有没有遵守任何隐私标准。
如果我在 Roomba 的包装上印上那些隐私承诺,我会卖得比什么都不印更少。(科林·安格尔)
这句话的信息量比任何行业报告都大。在当下的市场结构里,隐私保护是一项负资产,做好人的公司要为此付出销量代价。所以他认为赢得信任只是必要条件,远远不够。真正需要的是建立一套普通人能看懂、能信任、能在买东西时直接用上的隐私分级标准。他打了个比方,就像肉的等级标准那样。
有了标准,买家才有一个可以拿来比价的维度,好公司才会因为好行为被奖励,整个行业才会往前走。现在的局面是,每个公司都在自己的新闻稿里说自己重视隐私,消费者无从分辨,最后干脆不看这个维度。而消费者之所以不看,一部分原因在于 AI 和数据收集对大多数人还是黑箱,看不见的东西没法比较。标准做出来,讨论才有可能开始,人们才能问一句,谁在遵守,谁没有。
机器人越聪明,会越有情绪
关于「Roomba 会不会有一天拥有人类级别的智能」,科林的答案很干脆:在他有生之年不会。
他紧接着说,一台没有人级别智能的机器人,也完全可以和你进行一场有意义的对话。对话的对象是谁,决定了这场对话有没有价值。如果对话是为了哄机器人开心、让它感觉良好,那在机器人身上装个按钮,一按它就笑,效果一样。如果对话是为了你自己,你想知道今天宠物过得怎么样,想知道怎么让家里更省电,想知道去爬珠峰前该了解什么,那就完全可行,而且很有价值。他举了独居老人的例子:机器人可以很有效地帮人减少孤独感,填补那些本来可以用来了解世界的有趣空隙。
他还说了一个自己的理论:机器人越聪明,会越有情绪。
你没法只靠纯逻辑活下去。我们遇到的处境里,只有极小一部分是能靠逻辑合理解决的。(科林·安格尔)
他的论证是,情绪在信息不完整的情况下帮人做出合理决定。社交场合信息不完整,竞争和危险场合也信息不完整,情绪之所以存在,是因为它有用。当机器人进入同样的处境,纯逻辑不够用,情绪就成了必需品。
这个观点和主流想象正好相反。人们通常把情绪当成智能的对立面,觉得越理性越高级,越接近机器越纯粹。科林从工程角度给出的判断是:情绪是一种在不确定条件下的高效启发式,是进化给出的近似解,任何要在真实世界里做决定的智能体,最终都得有类似的东西。
访谈最后,主持人问他愿意和哪个科幻里的机器人待一天。他选了《星际迷航》里的达塔,因为达塔很聪明,见过很多事,而且关于情绪和机器人,达塔会有很多话说。主持人追问,如果能问达塔一个问题,并且得到深刻诚实的回答,会问什么。他的答案让整场对话落地:「皮卡德(Picard)船长到底是什么样的人?」
一个造了 29 年扫地机器人的人,最后想问一个虚构机器人的,是关于另一个人的事。这大概就是他对机器人这件事的真实态度:机器人不用变成人,机器人能做的只是让人与人之间的东西变得更多一点。
值得带走的几条
- 如果你在做硬件产品,先把成本函数想清楚。问自己一句:量产之后,我的产品定价由零件重量和标准工艺决定,还是由人工装配的小时数决定?只有前者能随规模下降,也只有前者能让你活到第二次迭代。
- 判断一个机器人方向是否成立,技术有多酷没什么用,要看那个需求是否「明显」大于成本。勉强打平不算,需要屏住呼吸才能算平的生意,五年内会断气。
- 找需求的方法可以很笨:进到真实场景里坐着看,看人怎么生活,找出那些频繁到成为负担、普遍到自己都察觉不到的事。这类洞察事后看着理所当然,事前极难拿到,值得花时间。
- 传感器路线别赌过渡方案。看技术趋势往哪走,问「三年后这个部件会便宜到什么程度」,据此设计今天的架构,别挑当下最好用的那个。
- 如果你的产品涉及用户数据,别指望靠宣传隐私赢得市场。当下隐私是负资产,印在包装上会掉销量。现实的做法是把处理放在本地、把控制权交给用户、只上传必要的最小语义信息,等行业标准出现时你已经合规。
- 做自主系统的人可以想一想:用户真正想要的是他一句话,正确的事就发生了。把「听懂意图」当成核心能力来建,比一味提高自动化等级更有价值。
- 评估机器人公司的护城河,看它对空间的语义理解有多深,别被机械结构的复杂度唬住。手不值钱,知道东西在哪才值钱。
文稿来自公开 Kaggle 数据集(rajneesh231/lex-fridman-podcast-transcript),为早期自动转录存档,可能存在识别错误。
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.