硅谷101大会探讨机器人商业落地 专用设备造血能力超人形机器

硅谷101大会探讨机器人商业落地 专用设备造血能力超人形机器 人形机器人正面临高昂硬件研发成本与大规模部署维护困难的现实鸿沟，在实现全身体系可靠性与通过责任险审批前，具备高投资回报率的专用机器人仍是企业级市场的主流。 圆桌论坛围绕机器人的实用价值与市场炒作展开了深度交锋。Anand指出专用机器人在企业级市场拥有更清晰的投资回报率，并通过设立8亿美元基金利用低息贷款解决创业公司的现金流瓶颈；前特斯拉工程师Evan分享了Musk对Optimus人形机器人的执着，并展示了通过线控腱驱技术实现的300美元高自由度低成本开源机械手。Jan则阐述了大型语言模型在控制机器人方面的潜力，同时指出大规模部署中面临的维护、数据隐私、责任保险以及居家噪音等现实硬件与商业化壁垒。 机器人行业面临公众对人形机器人的高度炒作与企业级专用解决方案实际营收之间的巨大反差；对于B2B企业客户而言，专用机器人在长周期连续任务中成本更低、可靠性更高且ROI更明确。 (0:00) 大语言模型将物理世界交互视为连续文本来生成动作，展现出操控机器人的强大潜力，为通用人形机器人的发展带来了全新路径。 (3:30) 为突破硬件成本瓶颈，TetherIA展示了仅售300美元的高自由度线驱动机械手，并与多方共同倡导模块化开源软件架构以降低调试门槛与扩张成本。 (8:00) 在现实世界中，机器人规模化部署的最大瓶颈并非软硬件研发，而是日常运营维护与设备正常运行时间；频繁的硬件故障使得驻地技术维护成为刚需。 (13:30) 尽管规模化量产有望让人形机器人硬件成本降至2万至3万美元，但缺乏责任保险支持、数据安全合规以及高昂的硬件研发资金缺口仍是进入家庭与主流市场的关键阻碍。 (15:30)

在硅谷101举办的Alignment 2025机器人论坛上，从业者与投资人围绕人形机器人的热潮展开反思，指出真正的商业化突破不在于概念炒作，而取决于能否平衡技术、成本与可靠性这一“不可能三角”，并解决线下维保与资本断层的现实挑战。 商业变现分歧：专用设备与人形构型 (0:00) 机器人行业目前分化为追逐风险投资热潮的人形方案与聚焦企业真实付费的专用设备两大阵营。具有大规模落地经验的Anand指出，B2B企业客户看重清晰的投资回报率，单一工业场景任务往往需设备运转超24小时，专用机器人不论在成本还是效率上均显著优于试图使用吸尘器的人形机器人。他以福特造汽车而非机械马为例，认为为特定任务优化形态才是满足企业预算的关键。 与此相对，前特斯拉Optimus团队成员Evan与Open Mind创始人Jan则认为通用人形拥有更广阔的长期市场。Jan提出全球三分之一的经济体量（约30万亿美元）依托手工劳动，其中约三分之一依赖人手操作。随着大语言模型能够将物理世界理解为上下文并生成动作，通用形态的具身智能已具备实现可能，促使团队致力于在通用场景下推动人形构型落地。 硬件落地门槛：低成本灵巧手与构型设计 (8:00) 机械手是人机协同与复杂作业的核心瓶颈。Evan展示了成本仅约300美元（具体为314美元）的开源灵巧手方案，其采用绳索肌腱驱动架构而非连杆或直驱结构，以在极低制造成本下模拟人手在现实交互中的自适应与柔顺性。在指状结构设计上，Evan阐述三指足以应对依靠三脚架支撑的抓取放置，但操作工具（如扣动吸尘器扳机）至少需要四根手指以确保抓握稳定。 在硬件降本预测上，Evan认可马斯克对Optimus最终售价降至2万至3万美元的预期，认为工业规模化量产终将把成本压缩至基本物料清单（BOM）水平。此外他预测，得益于行业资源的集中投入，机械手硬件将在2至3年内走向高度成熟，但涉及全身协同的双足行走系统达到高可靠性仍需更长时间的技术积累。 开源架构与真实环境中的部署阻力 (9:59) 软件层面，Jan提倡类似乐高积木的模块化开源操作系统，认为这比调试大型端到端黑盒模型更具可扩展性。开源架构不仅便于家庭用户与开发者审计数据流动，还能协助国际硬件厂商通过使用本地开源软件与合规服务器，跨越医疗、学校及安防等敏感领域的审查。 然而，机器人进入真实环境仍面临繁重的非技术阻碍。实际入户生活暴露出24小时散热风扇噪音、木地板重步声等生活干扰；在商业与养老场景中，企业必须应对保险合规（如慕尼黑再保险推出的AI Sure产品）、数据安全准入，甚至是记忆照护中心老人因情感依附在机器人表面留下口红等意料之外的清洁维护需求。 运营现实：维保难题与硬件服务化资金缺口 (13:30) 针对规模化部署，Anand根据在全美48个州与沃尔玛、苹果、英伟达等合作伙伴部署约3.5万台机器人的经验指出，行业最大的瓶颈并非软硬件研发，而是极其高频的机械故障与日常维保。由于硬件成本高昂而替代的任务往往属于低时薪工作，企业必须通过大量培训退伍军人组建现场技术团队，才能维持设备正常运行时间并跑通财务模型。 在资本结构上，传统机器人公司在完成A轮后常因昂贵研发与生产投入而倒在B轮门槛前。面对客户青睐每月约1000美元的机器人即服务（RaaS）订阅模式、拒绝支付5万美元高额预付款的现状，初创企业面临严峻的现金流断裂压力。为此，Anand通过联合18家银行成立8亿美元基金，为终端客户合同提供3%至4%的低息承销资金，替代硅谷银行高达18%的风险债，以此帮助硬件企业跨越制造与铺货阶段的资金鸿沟。 该讨论总结了机器人走向规模化所受制于的技术、成本与可靠性“不可能三角”。尽管具身大模型与低成本硬件正在降低准入门槛，但长期的商业存续最终仍受制于严苛的现场维保、责任保险以及重资产运营下的低成本资本供给。

[0:00] Anand: because I make money. [0:00] Anand: You can either get revenue from customers by solving problems or raise millions from VCs by chasing hype. [1:40] Evan: We are building humanoid, but we are human [3:30] Jan: most large language models speak fluent robotics. [6:00] Anand: far out compete any vacuuming humanoid or humanoid trying to vacuum with a Dyson. [13:30] Anand: Robots break down all the bloody time, [15:30] Jan: they'll laugh. [19:59] nurses: wipe lipstick off the head of the humanoid [22:15] customers: 1,000 a month [22:15] Anand: 3%, 4% compared to what Silicon Valley Bank gives it at 18% [24:59] Jan: clunk clunk clunk [24:59] Jan: look into the brain of thinking machines [24:59] Jan: open source software brewed with love in San Francisco

[0:00] All right. Welcome to the afternoon session of Alignment 2025. And I hope you guys had a great lunch. And welcome to the robotics panel. I'm your host, Jing Wu, and I just introduced our three amazing guests over here. The fun story I said I was going to tell is, you know, Anand was here last year. And after he came here, this year his company actually had an $800 million fund used for robotics startup financing. So I guess my point is I really hope our event can be a lucky charm. So I hope all our panelists can also raise more money after coming to our event. So we saw a really amazing demo, man. I think part of what Chen introduced is we have different ideas in this panel. So Anand, let's actually start with you. You're going to be our X factor here because it is an amazing demo. But honestly, I can't remember when's the last time that a robot demo does not have folding laundry or picking fruits. So I guess in an environment so hyped up about humanoid robots how can you still stay so poised and motivated to work on cleaning robots That because I make money Okay That the punchline I have large enterprises a crap ton of money to solve real problems And you can in my opinion you fall into two camps You can either get revenue from customers by solving problems or raise millions from VCs by chasing hype. Yeah, that's cool. So if real application or task specific robots can make money, so I'm not sure if we mean human or robots cannot make money down the road, right? And that's a sharp perspective. I guess, Evan, you just did the demo. How is it like working with Elon at Tesla Optimus? Because your background, you are from the Optimus team. How is it like working with him, and how did that experience influence you to do your own startup as well? Yeah, absolutely. I think Elon is definitely a great and one-of-kind entrepreneur. and he's also has this deep tech-driven mindset and he is a true believer of first principle. So we, from day to day, basically as Optimus, since it's his main focus these days, we had a kind of weekly meeting with him to go through the updates and his directions Overall he always tell us to always trying to get a human form factor even though it going to be a long pass and challenging experience to get there But he truly believes like once the technology there, eventually human will get there. And also the market will be enormous. And yeah, that's and we sometimes even it was him at like 11pm. So he comes to the office to review the robot at 11 p.m. Everybody stays. So he's a really hardcore startup founder, I would say. Wow, that's amazing. Does that mean your company also works until 11 p.m.? We are building humanoid, but we are human. That's a perfect answer. If you guys are hiring, then I'm sure the folks will be happier to know you're not 996 or whatever. But, yeah, coming to you, Jan, I know, well, speaking of hype, right, And I read somewhere that Open Minds actually, your company Open Mind, they put Asimov's Law and the robot identity actually on blockchain. So if those words coming together is not hype I don know what is But I actually I know you saw the real deal though because you were already a professor at Stanford So I was wondering what do you see in humanoids now that actually make you so excited to come out and start your own company when you already have so much prestige and resource at Stanford already? Well, there's a lot to unpack in your question. But what's exciting to me as someone who loves robots is that the longstanding problem in robotics, which is to have a clear line of sight to, quote unquote, universally capable humanoids, is now there. And that's because most large language models speak fluent robotics. So this old perspective on how to build software for robots, which is either sort of deterministic task focused or end to end AI. Now we have another set of tools that allow us to rapidly repurpose robots for a diverse array of tasks in hospitals, homes, schools, workplaces. And that's the really exciting part is that large language models, many of them speak fluent robotics already. [4:59] What do you mean by speak fluent robotics? Do you mean like they have good connection with the code API or do you mean humans can use language to command the robots better? Well, one way to think about this is that large language models are very good at completing stories. If I give a large language model the first chapter of a book, I can ask it to write the next 11 chapters. And if I represent the world as a contiguous block of text, I can then ask a large language model to continue the story. If I then connect the large language model to a physical shell that allows it to move, explore, interact, bark, ask, show emotion, then all of a sudden I have this object in front of me that is much more interactive and much more engaging and can also learn in ways that really hasn't been true before for robotics. I see. That's a good point. So the interaction side of things. Anand is there anything any quick comment back or anything quick to add after you hear from two folks that are you know both slightly bullish on humanoids Maybe do we need like both task specific robots and humanoids in the long term Depends on what part of the sector or industry you going after is what I would argue. If you're going after B2B enterprises where people have enough money, task-specific is far better because just that single task alone will take more than 24 hours for a single robot to complete. And then I don't need a general purpose robot that's overbuilt. An analogy I like to make is if Henry Ford was asked, okay, how are you going to design a far better transportation system? He's not going to take a horse or a human being and make that into a system. No, he's going to take a car. Cars are far better at transporting goods from A to B. My vacuuming robot will far out compete any vacuuming humanoid or humanoid trying to vacuum with a Dyson. So this building alone, if I had to vacuum this entire space, I'd need about four or five different vacuuming robots to to be able to take care of that. It's far cheaper, far more reliable, far easier to be able to get that done than to have a single humanoid trying to do, or a team of humanoids trying to do the same thing. So it all boils down to what are we going after. And in enterprises, tasks are meaningful enough, large enough that an application specific gets you to your ROI far more reliably Yeah that a perfect point And I believe you because some of Ana clients actually include some really big names that we know Big tech companies like Apple or these companies in the Valley are your clients, so definitely. So it seems like the key is how do we roll out robots to its proper applications? What are the roadblocks to the mass adoption of robots? So I guess on the mechanical side, coming to you, Evan, So kind of, you know, your hand is really amazing because we might not know it only cost $300. And it squeezes in the features and the degrees of freedoms of hands that usually cost thousands of dollars. So I wonder how you guys are able to make it. Are there any recent breakthrough? And what still makes it so hard for you guys to, you know, do some of these complicated tasks? Sure, absolutely. So I think coming to robotic hand design, especially human form factor, it's not only about, you know, like we just need to get this joint to move this many degree of freedom. It's more about understanding the end result, the functionality of a human hand, why it such a form factor and how people are interacting with objects around you So that why we are sticking with this cable tendon driven architecture And I know there are some other different architectures like linkages or direct actuator drives. Those are like you see them move smoothly and nicely, but they are not built to really work like a human hand. So that's kind of very important. That's why we picked this cable-driven architecture. Yeah, that's my two cents from a mechanical design perspective. Yeah, yeah, that's great. So I guess then from the software perspective, because Evan just said, right, we have different software based on different type of hardware. So that's also kind of what companies usually do. If Figure or if NVIDIA, their robots is built in a specific way, They're going to have a specific model for that. But, Jan, you believe in open source and modular software. You believe in different types of hardware might be able to work with the same open source software that you have. So I guess why do you believe the robot operating system needs to be open source? And how does that help solve some of the bottlenecks in software? [9:59] Okay. Well, again, there's loads going on in your question. There's why is open source useful? And of course, the internet runs on open source software and most phones on earth run on open source software. It's called Android. So there's certainly a lot of examples for how open source software powers really important things. The other thing you alluded to is the optimal architecture to use for thinking machines. And as we've already heard, in robotics, it's extremely important to be extremely specific. When people throw around things like robotics or humanoids, it is vital to be specific about the task you're trying to accomplish. For example, if you're building a humanoid sex robot, obviously you're trying to accomplish a very different set of like it's a very different business case and form factor compared to a vacuum cleaner compared to something BMW would like to use to put torx bolts into their engine control units If you think about the global economy something like a third of that is based on manual labor like people doing things It's something like 30 trillion a year is based on humans doing stuff in the physical world. And something like a third of that third involves hands. So obviously, if you're going after something like iPhone assembly, then exquisite hands are critical. So then with respect to your question, what is the right architecture for humanoid robots? There's no simple answer. Again, it depends on what you're trying to do. if you're physically manipulating things, that requires exquisite technology like we saw earlier today with hands, but it also requires amazing compute. The difficulty of making sense of your physical world, deciding what you should do with the hand, and then being able to deal with all those degrees of freedom to accomplish a task is a big compute problem With respect to what a lot of companies are doing right now, which is exploring the possibility of modular Lego block like architectures for humanoid, including intrinsic, including OpenAI's robotics, including NVIDIA Foxconn humanoid, including everyone else who's currently working on software for humanoids. The central idea is that it's much easier to debug smaller pieces of software rather than like fine-tuning some end-to-end AI or something like that. So it's not only us that is thinking about modular architectures. It's many other people in the industry as well. Yeah, yeah, that's a great point. I guess, Evan, coming back to you very quickly because you're working on hands before, you know, right now on robotic hand. We probably saw the demo succeeded one time today, but yesterday, you know, there's like a number of tries. And we were talking about how difficult it is with the tactile sensors or there maybe a lack of force feedback on the hand So what are your thoughts on some of these hardware working with the smaller modular software like Professor Yang mentioned Okay, so I think your question is about some hardware sensing. Yeah, like software working with different types of hardware. Do you guys write specific software for your hardware or do you see it being able to work with other types of software in the future? Absolutely. So with the hand we showed today, It's a total pure open source hand, including the hardware and also software. We are going to rely on industrial and academic people and even hobbyists trying to contribute to this whole thing and to create this ecosystem around the hardware to make it better and better. That's why we just marketed at $314. So it's really easy to enter this dexterous manipulation world without breaking the bank. Yeah, that's a good point. Adan, I guess come to you. You've seen robot deploying in the real world. What do you feel like is the bottleneck to the mass adoption of robots? Is it on the hardware side or on the software side, or maybe it's something else? So between us and our partners, we have [14:59] about 35,000 robots deployed in the real world. Clients include Walmart, Amazon, Apple, NVIDIA, Meta, Hilton, Marriott, MGM, et cetera. The challenges that we see, the biggest challenge today that we are actually overcoming is not building the robot, it's not the software, it's not even the hardware. It's the fact that robots break down all the bloody time. Question for you, Evan. How often do your robotic arms break down? So yeah, I would imagine once we really deployed it, that's quite a big issue at this moment. So in the 48 states we are deployed in today, pick any state, I will tell you a city right now, I have a broken robot. And that is my biggest headache, is uptime, being able to make sure my robots are operating. To that end, we are hiring thousands of veterans to go out and train them and be a robot technician. But that is the real-world challenges that need to be overcome. Along with that, there's the entire finance aspect to this. Like, how do you actually get the capital to be able to do all of these systems? Robots aren't cheap. Hardware is not cheap. And then a lot of the tasks people go after, such as laundry folding, is this is minimum wage tasks. Most parts of the country we are still at per hour So how do you make the math work on that front Yeah absolutely So you talk about business model and reliability and that actually are two more talking points that we're going to get into. I guess in terms of business model, Evan, Elon last year said the Optimus robot will cost only around $20,000 to $30,000. Do you feel like that's feasible? And if it is, how can startups like you guys to compete with companies like Tesla because they have so much more manufacturing capacity. Yeah, totally. First of all, with the price point, Elon brought up $20,000, $30,000. I am truly believing that. Once anything getting to mass production, we are basically optimizing all this process. And so the cost down to basic bomb costs and pure material costs. And talking about the cars, cars have such a high mass of material around there, but it's still maybe around $40,000, $50,000. But so the humanoid robot eventually, I totally believe we will get down to $20,000, $30,000. However so talking to how we can compete in this game versus Elon or Tesla I believe as Anana was saying in the future I also believe there will be many different form factors of robots. Elon is trying to build the Optimus, which is one SKU, one human form factor. But a human is not designed to be the most efficient form factor to do all kinds of tasks. So, but the hand, I believe, will have more compatibility to own different tasks. So, it will be different platform, but integrate all kind of hand shape. And as a hand focus company, we're also developing, you know, different skews kind of hand. Even the human hand, we build differently. Like, some people with very elegant hand can do, like, music instrument. hand, and some hands are more like strong and labor-driven hands. So where our robot hand will be. Yeah, maybe one day we'll see the chairs being carried on by robot hands, and with the robot themselves for sure Yan I know you mentioned Android and robotics I guess part of the reason why Android works is because it also integrates closely with the rest of Google ecosystem It drives people to Google ads revenue and all of that But for a startup who does not yet have that type of ecosystem, how do you see open source business models start to work out in robotics? To quickly comment on what we heard earlier, there's some really excellent points we're surfacing. One of them is the reliability, and I totally agree. That's probably the main thing right now is just we expect when we go outside, we expect our Tesla to just work. And most robotics deployments right now, except for things like in the gigafactory or in car factories, have nowhere near the robustness or reliability that one would like. The other thing we're seeing as a practical barrier to deploying humanoids and Quadruped into American households is as simple as liability insurance. Try to go to an insurance company and say, hey man, I'm deploying humanoids into U.S. households on October 15 for healthcare, math, education, and security. I need liability insurance, and they'll laugh. So the good news is that we're not going to be able to do that. [19:59] Munich Ray, as of last week, is offering AI Sure, which is liability insurance for humanoids. And the point of that insurance is that if the humanoid fails to perform a task, Munich Ray will cover liability arising from that. And so I totally agree with Anad. For certain specific use cases, the technology, the hardware is basically good enough. If the software is basically good enough, it's really things like business models. Is this leasing? Is this a subscription service for add-on apps for your humanoid? Is this something that old people's homes purchase for their patients? So who's buying? How much are they paying for it? How are they paying for it? And how are you dealing with things like reliability and insurance? There's one new task for humans that blows my mind, and this is based on deploying humanoid into memory care facilities So that a situation of where the humanoid does not have hands because it not necessary The point of the humanoid is to engage with a human and make them laugh and cry and listen for people who been in memory care facilities for years and have almost no interactions with other humans. And humans in that situation get so attached to the humanoid that the nurses in the evening have to wipe lipstick off the head of the humanoid. And so this is part of the general, like, maintenance of robots deployed into human settings. Yeah, I see. Well, I was looking for different opinions, but I got a lot of agreements between you and Ana, so I guess that's a great point. Ana, you were smiling a lot before when Jan talked about insurance and all these problems. Do you have anything quick to add there? Yeah, that is what I'd say is the difference between the real world and the academia or the startup world. In the real world, insurance is a big thing. COIs, being able to comply legal. Good luck trying to get a large language model approved for any of these large companies. Good luck trying to get Chinese robots like a unit tree inside where you know there are so many back doors where the privacy is a big aspect. Data security is a massive aspect. How do you get them deployed in large industrial sectors How do you get offices We clean Jamie Dimon personal office with a robot I am paranoid because I was like holy shit that a huge security risk We are in multiple defense sectors. We have robots running around there at SpaceX and at military bases. So how do you get through the security clearance? How do you get through insurance? How do you get through reliability? How do you get through making sure that when the robot breaks down, someone can show up and fix it? That is the real world that needs to be solved far more importantly, and people are spending a lot more time trying to figure those portions out. Yeah, yeah, absolutely. And we're going to cover reliability very quickly. But first, more about your $800 million fund, I guess one thing is how did you even discover that as one of your business model? Where did you find that need? And why can't just robotic startup find customers and funding on their own? That's a great question. Longer story short is getting access. We spoke with 30 plus CEOs of robotic companies who all raised a series A and could never get to a series B. This was generally the wave two of robotic companies. This was the Willow Garage style, Savvy Oak Robotics, etc. Some of the most legendary robotic companies there are. One of the biggest reasons they fail is getting access to capital Capital is expensive Typically there are two ways of getting funding You can go to debt your bank Silicon Valley bank who not incredibly high rates because you are a startup you not profitable Or you can go to VCs. And VCs will take a portion of equity. But that's gated capital. If you don't hit certain benchmarks, they're not going to give you more money. Now, robots are expensive. They're not cheap. They're not easy to build. They require a lot of R&D. And most of my customers don't want to pay up front for $50,000 for a robot. What they would much rather do is $1,000 a month because that's what they're used to paying a human being to doing that particular task. So how do you bridge that particular bridge when if you get an order for 500 robots and that robot costs you, say, $20,000, you'd require $10 million worth of capital to be able to even go out and buy or procure or build so many robots. Who is going to give you that $10 million? The VCs? No, that's too expensive. Equity dollars don't exist for that. And banks, they will eat up your entire margin. So we created this fund with a consortium of 18 different banks to be able to actually underwrite the contract, underwrite the end customer, and do it at what, 3%, 4% compared to what Silicon Valley Bank gives it at 18%. Yeah, that's a good point. It sounds like a lot of effort trying to go in to enable [24:59] us deploying more robots in the real world without worrying too much about the underlying risk, because that's always a work in progress. So speaking of reliability, Anand, you've covered it a lot on the reliability side. I want to ask Evan as well. So, you know, how far away are we from reliable robot hands? And also, one thing extends from reliability is if the robot is reliable, it's safe. We can start to trust them. So Professor Ronnie Brooks actually said in one of his essays earlier this week that if the humanoid hands have tactile feedback, it can really help foster a better human-robot interaction. So just largely, how does robot hand all play into all this? I would say from my two cents, maybe in the next two or three years, we're going to see a lot of maturity on the hardware side, especially on the hand. But for the general whole body, especially the biped, right, that still takes maybe a little longer. Because to get to that level of maturity, you need a whole system improvement. But just by hand itself I totally believe with the whole resource from the whole society focusing on getting this better and better we believe we get there in the next two three years Wow that an optimistic look And I guess, Jan, in terms of reliability, like I said, is trust, is interacting with the robots. You're actually one of the only, maybe the only person I know that lives with robots. I wonder how are Iris and Franchi doing? And yeah, how do you ensure safety and trust when you actually interact with these robots that actually live in your home? Well, I encourage all the engineers and investors and bankers and scientists in this audience to get a robot and try to live with it, because that will immediately expose a long list of things that are irrelevant in the lab, but critical for deploying humanoid or quadruped into households. A great example would be cooling. A lot of the humanoids right now have these big fans going 24 hours. And if you've ever tried to sleep next to a humanoid with a loud cooling fan, it's literally impossible. That irrelevant if you a humanoid in a lab because no one cares about sound levels But the other thing is when the humanoid walks around your house it very loud on wooden floors It goes clunk clunk clunk And so those are little things that become only apparent when you try to live with a humanoid. And with respect to trust, the whole notion of building open source software for humanoid, for me personally, was a no-brainer. I have kids. I want my kids to be able to look into the brain of thinking machines around them and say, aha, I can kind of see what's happening here. I can see how the data are moving. I can see bugs. I can contribute, add, fix. And in retrospect, focusing on open source software for humanoid was not only meaningful for me as a parent, it also makes good business sense for reasons we heard earlier. Imagine you're a quote unquote international manufacturer of humanoids and you're trying to sell into U.S. markets. Like good luck. Imagine like you want to sell your humanoid into a U.S. police department, fire station, elementary school hospital And the first question you get is oh why should we trust the software Where are the data going somewhere I don want it to go And a good solution for that is that if you build good hardware why don you use open source software brewed with love in San Francisco and have the data stay in the U on HIPAA servers And so it turned out that building open source software for many, many different verticals is not only good for like all the parents in this room who care about where the technology is going, but make very good sense nuts and bolts for rev share deals with Chinese robotics companies. Well, Anand, we got like 30 seconds left. Anything quick to add on reliability or the safety trust side of things? I have one question for Evan, actually. Evan, where do you see the need for five fingers versus three? Like what task truly requires five fingers that three fingers cannot do? I kind of asked him the same question yesterday, actually. Yeah, that's actually a great question. I think when you're talking about basically pick and place tasks, right? Three fingers is totally enough for tripod support. However, once you start talking about doing tool operations, like using a vacuum, right? You need at least four fingers I would say. [29:59] Four finger to hold your tool first and then use your index finger to pull the trigger. If you don't have this extra redundancy, your ring finger, only three, you're only picking up your vacuum with two finger now, and then one index finger for pulling the trigger, then that's not stable state. I will argue maybe fifth finger is not that important on the pinky, But four fingers definitely need. Yeah. This is cool. I love how this is turning into a biology and evolution theory class real quick. But yeah, today we covered robotics progress and challenges from the Trinity, the impossible Trinity, which is the technology and the cost and also the reliability side. So yeah, I really appreciate our guest here. And let's give it up for our panelists. Thank you. Thank you. I know. I have an answer for you. So if you have a robot girlfriend, you need the ring finger. How do you propose to the girlfriend without ring finger? That's right.