Physical AI is more than robots, says the Nvidia veteran now investing in it

Amulya Vishwanath, who spent seven years leading product marketing for NVIDIA’s robotics platforms, says robotics is currently in its “Lego era,” with the basic building blocks like actuators, robotic hands, software, and safety standards still being rebuilt. This view runs counter to those who believe that robotics, powered by a general foundation model, is about to have its “ChatGPT moment” — that day when the shockingly capable chatbot was launched in late 2022. (General Intuition CEO Pim de Witte told Equity earlier this year that a single general foundation model would make much of today’s specialized robotics work redundant, and be that moment.) On this episode of TechCrunch’s Equity podcast, Dominic-Madori Davis caught up with Vishwanath to discuss where she’s writing first checks as the founder and managing partner of Techable VC. They also talked about what she’s learned as one of the first women executives to spin out of Nvidia and launch her own early-stage firm investing in physical AI across robotics, materials science, and life sciences. Listen to the full episode to hear more about: Why Vishwanath defines physical AI as more than robots: “a molecule, a material, a medicine,” or a machine on a factory line. What she means by “conscious automation.” Why the best opportunities solve big problems like family-run factories that can't find workers to surgeons facing burnout. Why she wants founders to see their VC as their moat, and how years at NVIDIA built the network she now uses for due diligence and customer introductions. Where she thinks the U. S. and China each have the edge, and why humanoids should be good for more than dancing. Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You can also follow Equity on X and Threads, at @EquityPod. Chapters: 00:00 Intro 01:03 Amulya’s path from Intel to Nvidia, and why she left 04:39 What physical AI meant in 2018 vs. now 06:12 Beyond dancing robots: industrial and surgical use cases 09:31 What “conscious automation” means 12:12 Cutting through the hype: the “Lego era” of robotics 16:43 Why your VC should be your moat 20:30 Biggest bottlenecks for physical AI founders 22:30 U. S. vs. China in physical AI 25:43 Are humanoids just for entertainment? 28:10 The most promising near-term areas 29:22 Outro Learn more about your ad choices. Visit megaphone.fm/adchoices

• 0:00Speaker 00

  Hello and welcome back to Equity, TechCrunch's flagship podcast about the business of startups. I'm Dominic Midori Davis and this is the episode where we bring on industry experts to help us explore a trend in the tech world and dive deep. In the past few weeks, news broke that robotic startup Field AI is reportedly eyeing a $700 million raise at a $10 billion valuation, while a German robotic startup hit a unicorn valuation earlier this month. The money pouring into physical AI is getting enormous, but before any of these massive rounds, someone has to write the very first check. Today's guest is making her bets much earlier and she's been in this space longer than most. Back in 2018, years before anyone was even calling it physical AI, she was marketing Nvidia's first robotic software.

• 0:44Speaker 00

  Today, we're joined by Amulya Vishwanath, founder and managing partner of Techable VC, an early-stage firm investing in physical AI and frontier scientists. Amulya, welcome to the show.

• 0:54Speaker 01

  Thank you, Dom. And on that note, I'm curious, do you prefer Dominic or Dom?

• 0:59Speaker 00

  Oh, either is fine. You can call me Dom. It's like shorter.

• 1:03Speaker 01

  Awesome.

• 1:03Speaker 00

  Something that's actually quite interesting is that you were at Nvidia in 2018, which doesn't seem like that long ago, but I guess in AI years actually is kind of like a long time ago. And well, my first question, of course, is like, what made you leave? Like, what did you see that was happening at Nvidia that made you say, wait, I should probably break out and do my own thing? And start backing like the next generation of this?

• 1:28Speaker 01

  So I've been studying deep neural networks for about 16 years now. And my engineering background has been in electrical engineering and I also ended up doing an MBA. But really, over the years, I've noticed that the semiconductor industry has evolved quite a bit from just being known as semiconductors to computing. And my very early career, I started out as a signal processing engineer designing radar systems, and then went on to joining Altera, which got acquired by Intel. So I ended up leading technical product marketing for a lot of the signal processing products. And this was back in 2016 and very early stage of thinking about AI deep learning. So I also was fortunate to launch Open Vino Toolkit for FPGAs,

• 2:13Speaker 01

  which was Altera's strategy in the overall portfolio by Intel. And from there on, Nvidia came calling in 2018 and it was one of the best opportunities that would have showed up in my career, I would say. And since 2018, I've been fortunate to lead product marketing efforts for some of the most foundational and core products, including all of the libraries, pre-trained models that we brought in mainstream. And back in the day, it was more research-focused. And now you see that people are no longer talking about models, they're talking about core applications that can really enable newer trillion-dollar markets.

• 2:51Speaker 00

  And so was this some of the stuff, because like, because what made you, what was the decision? Or what was the moment that made you want to leave and kind of launch and do your own thing?

• 3:00Speaker 01

  Yeah, I always had an entrepreneurial spirit and it was a matter of time. And I'd already seen and built a lot of the community that is now building and developing in superintelligence or artificial intelligence, as you can think of. But really, it was a point where I realized that I've taken on some tremendous challenges in my career since the beginning. My first capstone project was actually working on neural networks that can do image processing. So since then, I've seen AI really get out of the R and D phase to becoming mainstream. And as a result, I realized that if I've seen and built a lot of these things and I've supported a lot of the corporations and startups from a very long time,

• 3:45Speaker 01

  I think it's time for me to be my own Jensen and really go off and support the ecosystem from ground up. And the combination of building the ecosystem, working with a lot of the engineers and researchers from ground up, and to even launching one-of-a-kind, first-of-a-kind products, including Nvidia's Isaac Robotics platform, all the way to leading, expanding emerging ecosystems while Nvidia was going to get much bigger and expand its footprint into emerging markets. I think these are some tremendous opportunities that I never imagined I would get in this lifetime as a professional in the computing industry. And I've been fortunate to be in the front row and leading a lot of these efforts.

• 4:27Speaker 01

  And now I take all of that experience and the learnings that I've seen and absorbed from leaders like Jensen, Ian Buck, Deep Putala at Nvidia, and now I started Techable Ventures.

• 4:39Speaker 00

  What is physical AI to you? Like, what was physical AI back in 2018? And what is it now? Because it seems like it's everywhere right now.

• 4:46Speaker 01

  Yeah, so back in the day, it was essentially robotics, right? And if you think about it at a company as big as Nvidia, if you go back and look at any of the keynote slides from Nvidia's conferences, specifically GTC and so on, robotics and autonomous vehicles have always been a part of their bigger vision. And a lot of it back then was centered around data centers. But that said, you know, things have changed since then. And my definition of physical AI is not necessarily using it as a synonym for robotics. It's more than that. We're thinking about, you know, how materials are reinvented with AI. We're thinking about how robotics is now becoming more and more mainstream.

• 5:29Speaker 01

  Back in the day, it was more pre-programmed robots that could do specific things for specific applications. So now we can think much bigger and broader in terms of the robotics vision by itself. So it's not confined to robotics. It's more than robotics. It goes on to material science. It goes on to even life sciences, for that matter. And that's why I built Techable Ventures, because this culminates these three key pillars, where you can think of, you know, physical AI as anything that has been on the digital front now comes into the existence as a physical form. It could be a molecule, it could be a material, it could be a medicine, or it could be a robot that's in your house or running across a factory line.

• 6:12Speaker 00

  Yeah, it's actually quite interesting because I feel like there's been so much. I feel like you talk to like a regular person and they think about the dancing robots. And I just covered, I think Vogue World brought out dancing robots for like the finale of whatever they were doing in Milan. And it was funny because, you know, I was talking to kind of a, I guess she's like a consultant or a PR person in the industry. And she was like, this doesn't even like capture what's happening in the industry in terms of like how physical AI is intersecting with all these different industries. And I was like, that's so fascinating to think of just what's happening and what's bubbling underneath all the surface. Because I mean, I don't know, regular people might think of like the dancing robots.

• 6:52Speaker 00

  But it seems like there's just so much happening. I mean, what are some of the most interesting things that you're seeing right now?

• 6:58Speaker 01

  Yeah, absolutely. And, you know, part of robotics being so mainstream is essentially looking at the cool and cute things, as you can think of, right? Those fuzzy robots, the dancing robots and so on. But then also, there's a lot of mainstream robotics coming into play in terms of factory lines, healthcare, and really where there is a need for conscious automation. And some of the investments that I've already made through Techable Ventures has been in industrial robotics. Because what's happening is that a lot of the SMB factories, people are deciding to shut them off because there is a lack of labor interest in general, because people have moved on to newer jobs.

• 7:41Speaker 01

  And in this AI-first era, what is happening is that the choice of younger generation in terms of what they want to do versus the choice of, you know, like the boomers, so to speak, in terms of what they want to pursue, or even retiring for that matter, has really left with this huge gap. And a lot of these family-run businesses are now struggling or figuring out, you know, how do we address those gaps? So that's one area. The second thing, and this is an interesting one, and you know, I've been researching a lot about it and also ended up making an investment in one of my portfolio companies called Andromeda Surgical, is that surgeons face one of the highest burnout rates. Because what happens is that when you're assembling complex surgical teams,

• 8:24Speaker 01

  especially, you know, with the right expertise for complex cases, it takes time to, you know, attend to patient care. It takes months before a patient gets attention from the surgeon and their special unit for especially complicated, you know, cases related to cancer and so on. And as a result, you know, it's important to bring this conscious automation where, you know, it can be as simple as an autopilot for a surgeon. So that, you know, instead of doing 10 cases and, and interesting fact is that in the first minute, you can tell if the surgery is going to be a success or not, which becomes again, really critical, right? You want to deliver, you know, the most precision care,

• 9:08Speaker 01

  but at the same time, you want to make sure that you have specialists who are caring for a patient without having to, you know, like really see a miserable state of a patient, for instance. So with that said, you know, I think, you know, including a co-pilot for surgical use cases might be a very interesting space. And this is something that I've been pretty excited about.

• 9:31Speaker 00

  Well, actually, I just, I want to go back to one thing. What is conscious automation?

• 9:35Speaker 01

  A lot of the hype has been around, you know, everything is getting automated, right? And that is, that should not be the case. And again, like I said, you know, there are huge gaps in terms of the labor market. There are huge gaps in terms of, you know, areas where you need to deliver care in a critical and a careful timeline. And also, there's a lot of aging population and it's hard to address, you know, the needs that any of these categories need by just bringing in human labor. That said, you know, automation helps bring in these specific robots or autopilots. Again, it could be a software agent or a physical AI agent, like a robot,

• 10:17Speaker 01

  that can simplify and really add productivity and augment an existing use case. So it could be in healthcare, it could be in material sciences, it could be moving materials from one place to another, or it could be, you know, attending to a patient, or I just... Had to go visit my mom and the fact that, you know, she has her own struggles as she's aging makes me think that, okay, there are so many promising use cases for robotics to help and enable the, you know, aging population in general.

• 10:49Speaker 00

  No, that's actually quite interesting. It feels a little bit like a hot take, too. I feel like you're talking, like you talk to investors and they're like, everything needs to be agentic, everything needs to be AI right now. But it really is like the idea of finding like the meaningful things to automate, not just like spray automation, just like finding what's important.

• 11:07Speaker 01

  Yeah, absolutely. And again, you know, like I said, there's so much happening and there's such a huge gap in the market as well that needs to be addressed. And which is why I take the approach of, you know, having automation, but in a more conscious sense. And everything is tied to a dollar amount. Everything is tied to looking at, you know, can it be economical and can it be scalable? And which is why it's super important to fund these early-stage companies that are thinking and reinventing how robotics has been seen. And at the foundational level, there is a meta-science reset that's happening. And the reason why I say this is that the way research is being done is now being reset.

• 11:51Speaker 01

  The way researchers are doing research, the process of it is also changing. And with that said, the type of companies that are coming together, everyone has now become an engineer, right? If you think about it, English has become a programming language, which enables anyone to build anything and really question the status quo right now. And that's a fascinating time to be in.

• 12:12Speaker 00

  And as an investor during this time period, I'm actually quite curious to know how, because you have so much experience in this space. And there's obviously generalist VCs who also just want to get in on the hype. And so how do you kind of use the experience that you've had in this space to kind of cut through all of the hype or the founders who are just, I don't know, saying, I'm just gonna build a robot that's like, that can do dishes or something? Like, how do you use your perspective to really cut through things and also have a competitive edge against the other VCs in the industry?

• 12:44Speaker 01

  Yeah, absolutely. I think we've jumped from talking about perception AI to generative AI, agentic AI, and then right into physical AI. And a lot of companies and experts have been talking about the chat GPT moment for robotics. But I also want to say that apart from all of the exciting things happening in the chat GPT for robotics era, there's actually-

• 13:07Speaker 00

  Has it happened yet?

• 13:08Speaker 01

  We've been talking about it. There's been quite a bit of progress. But that said, there's a Lego era that's happening for robotics. And what do I mean by it? There are a lot of foundational software and building blocks for robotics that are being rethought right now as we speak. And it's super important in order for innovation to scale. I think it's important for these foundational building blocks for robotics, whether it's actuators, whether it's, you know, type of robots and, you know, anything and everything beyond humanoid robotics, and also what type of applications, which are the newer markets that will be disruptive, but also which are the existing unsexy markets that can see conscious automation as well, right?

• 13:54Speaker 01

  So that said, there are a lot of foundational problems that need to be solved for robotics and which is why I see this as a Lego era for robotics. That's the first thing. And then the second thing is that, you know, I've seen how robotics has been reset within companies like Nvidia, right? The strategy has changed by the day and we've seen mainstream adoption now in terms of, again, you know, all the technologies that Nvidia has built, but also the robotic strategy that is really helping. And one of the core pieces about robotics is that, you know, simulation is going to be more and more critical. And one of the products that I did technical product marketing for at Nvidia is called Isaac Lab, but I also led the product marketing efforts for humanoid robotics.

• 14:38Speaker 01

  And you've probably heard about Nvidia's Groot or GR zero zero T, as we would like the world to know it as. So I led a lot of these product marketing efforts, so got to work with fantastic set of founders, researchers internally, externally, and engineers. And I realized that we're just getting started. And in order for this to happen, I think there's, there needs to be more emphasis on open source safety and newer standards that need to be set for robotics in general. And the approach that I'm taking with Techable Ventures is to be a specialist VC firm because I am a product of an engineer and a doctor to begin with. And if you think about the thesis,

• 15:20Speaker 01

  it comes together as, you know, there's one lever which is around robotics, the other one around material science, and the third one around life sciences. So if you look at, you know, how physical AI is evolving, these are the three core levers that are going to see a lot more disruption. And that's our Fund One thesis. And the second thing is that, you know, there are fantastic investors out there and I love collaborating with all of them. And just based on our existing portfolio companies, I have a lot of the lead investors and co-investors reach out to me to get my input about companies that they're evaluating, how do we help our existing portfolio companies and so on? Which again, you know, says that, you know, I've seen and lived this experience in the physical AI market

• 16:04Speaker 01

  and that allows me to bring that unique insight into, not just to the founder community, but also to the investor community. And one of the things that I wanted to do with starting Techable Ventures is to have the founder think that his or her VC is the moat. And that's where I'm headed. And more and more, if you think about it, there is a lot of capital. So if you think about how founders talk about it, there's smart capital and dumb capital. And I want to be at that area where a founder can make a call even before they're, they start building. But at the same time, you know, I am a part of their moat.

• 16:43Speaker 00

  That's really interesting. Like, so what does that, what does that mean? What does that mean exactly?

• 16:47Speaker 01

  Yeah. So like I said, you know, I've been a part of the early journey in terms of AI deep learning becoming more mainstream. So back in the day, during my time at Nvidia, I started out as the founding product marketer to lead a lot of the AI software training, SDKs and models marketing. And that said, you know, I've built this ground-up network of engineers and researchers. And as a result, what has happened is that, you know, doing due diligence for me is much faster. Making introductions for customers or pilots to my founder community is much faster because, number one, I've already worked with a lot of these pilot customers or partners that I can make quick introductions.

• 17:29Speaker 01

  And at the same time, you know, a lot of the founders are people that I've already met or worked at one of the technical conferences in the past. So this just makes it a lot more easier for me to be the strength or the first call for founders and for them to even just validate the idea way in advance, even before that idea turns into a company.

• 17:51Speaker 00

  No, you know what's actually really interesting is I've been talking a lot more to investors who've been saying that, you know, it's not about the money anymore. Like, there's a lot of money out there and it's not necessarily even about talent. And they're saying like, what they've been refocusing a lot of their firms around is helping with like distribution and networking and all these insights. I think that's so interesting that, you know, we've reached a time period in the industry where there's just so much money, right? It's, founders are looking for so much more.

• 18:17Speaker 01

  Absolutely. And you're right in terms of the distribution channel, right? It's not necessarily because you're a VC or an engineer, but it's also because can you help your founders tell the story? Can you help your founders find the best talent and so on? So it all starts or goes back to distribution channel. And fun fact is that when I started out in 2016 on LinkedIn, I had a little over maybe 50 connections. So every connection that I've earned on these platforms has been because of the work that I've done in this ecosystem. So most of my network are these core researchers and developers that I've worked with. I've written a lot of the technical blogs about products that have now become mainstream.

• 18:59Speaker 01

  And at the same time, you know, I've had one of the unique opportunities where I've gotten to work with Jensen directly in third month of my time at Nvidia. So, you know, it gives me this unique perspective, but also, you know, to your earlier point about, you know, working at company, at a company like Nvidia, it's like working at a company that is, you know, running at light years right now. And it's been a fascinating journey to not only support founders while I was in the ecosystem, but I continue to exist in that ecosystem. And now I get to be an investor and help them do their fundraises or help with their product positioning, even thinking about their partnership strategy, for instance.

• 19:41Speaker 01

  So all of these components become critical. And in order for them to get the best talent, position their product, and at the same time, you know, work with the right set of investors is going to be crucial. And all of these are so much more important and capitalists do, but, you know, distribution and strategy behind it, which is why I say that your VC should be your moat. And I hope that founders can think through that very seriously because capital takes you to a certain distance. But beyond that, you want someone who's lived the problem. You want someone who can help you find the best talent, help retain them. At the same time, you know, can help you tell the product story, can help you identify the right partners to scale and go from there.

• 20:25Speaker 01

  And all of these things are things that are done. And I'm excited to bring it back to support the founder community.

• 20:30Speaker 00

  And when it comes to your founders who are building in this space, what are some of the biggest bottlenecks that they're running into? And I'm thinking in terms of like, is it manufacturing? Are there regulatory problems? Is it finding compute and energy? Like, what are some of the biggest problems that they're facing right now when it comes to building and scaling?

• 20:48Speaker 01

  I would say it's a combination of all of these, right? And that's fantastic. These are the problems that are needed in order for us to really build a scalable set of programs and ways to enable the entrepreneurship community. And as a result, you can already see that there's so much happening within the US ecosystem. We're seeing companies that are building actuators. We're seeing companies that are building variety of robotic hands, for example. We're starting to see companies that are reimagining how materials come into play with, you know, the semiconductor shortage that we're talking about. We're seeing robots being built, general purpose and special purpose robots, that are now going to be, you know, US-made.

• 21:28Speaker 01

  So that said, I think it's important to have supply chain within this ecosystem. And at the same time, I think the challenges are one thing, but then, you know, having the right talent, retaining that talent is also going to be very critical. And now is a time where you're seeing a lot of the talent going into some of the bigger corporations. But that said, you know, I see two polarized ways. One is where you're seeing a lot of talent going into some of these bigger corporations, like the Anthropics and OpenAI and then Nvidia's of the world. And then you're also seeing a lot of people leaving these existing corporations to solve the foundational problems across different domains and industries and build something on their own. Same thing is happening with the university ecosystem as well.

• 22:12Speaker 01

  A lot of people are getting into building, and this is such an exciting time. So I'm sure, you know, this is a pretty strong ecosystem. We've done this during the internet era. We've done this a long, long time ago with the industrial revolution. I think it's just a matter of time before things fall in place. And which is why I say it's the Lego era for robotics.

• 22:30Speaker 00

  But I feel like when it comes to manufacturing, you can't, you like, you can't not mention China. And so where is the US actually winning when it comes to a lot of physical AI production? Versus what do you think China is winning on right now? And how do you see the two ecosystems playing off of each other?

• 22:49Speaker 01

  Yeah, remember during my time at Nvidia, I did extensive research about, you know, where is a lot of work or publications coming from for some of these key areas, including robotics? And we definitely saw a lot more happening in China in comparison to other countries. But that said, in the US, there's been a strong talent pipeline. And we want to make sure that, you know, like, we offer them the right set of programs to support if they want to become an entrepreneur and also have, you know, channels for them to get into some of these bigger corporations. I think talent has and is being a moat for US in general. China has always had this position where, you know, they've been manufacturing experts for a very long time.

• 23:34Speaker 01

  But that said, I think the fact that we're bringing in superintelligence by itself, and there's so much emphasis within the country, you could say already that there's so much happening. You're probably seeing a lot of it when you see it in the news or when you hear it from one of your friends or colleagues. But that said, there's so much more that needs to get done within this ecosystem. At the same time, it is going to be a race. But at the same time, it is going to take a while. I think the way superintelligence has been evolving, I'm pretty sure will be able to accelerate a lot of those development and discovery to development timelines in general.

• 24:17Speaker 01

  There's going to be a global ecosystem, so it doesn't have to necessarily be centric around one country, right? In order for us to have a lot of these materials or life sciences development or, you know, robot development, a lot of these big corporations have presence beyond US as well. So it's important to think about this as a global ecosystem building towards, you know, what I see as, you know, like, the newer civilization or the more, more conscious civilization. That's kind of how the thesis that I built out. You know, there's so much happening, so much happening in the US, happening in China, and in general, within the ecosystem. Founders are pretty excited.

• 24:58Speaker 01

  We already see a lot of founders building or thinking about building. We see a lot of enthusiasm, even in the bigger corporations. Back in the day, they were slow to move and would think twice or thrice before working with startups. Are now taking bets on startups and building this three-way, four-way ecosystems with university entities, the startup themselves, a bigger corporation, and a cross-domain entity. It could be like an Nvidia, a university, a startup, and an Eli Lilly, for example. So we're, again, you know, seeing a lot of these resets. And which is why I say we are going through this Lego era. And it's a fascinating time to see robotics, life sciences, and material sciences being relooked at.

• 25:43Speaker 00

  That is so interesting. I think I was talking to someone very recently about it. I was like, we see coming out of China right now, like, a lot of the dancing robots. And like, I think the robotic Olympics was over there, right? They had something. And I was like, no, there's definitely something else happening. Like, this is, you know, they're, they're funny to see. I think, what is it? I don't know, the dancing robots are just so funny. I have no idea. But I was talking to some academics, and they were like, with humanoids, they were like, I think the best use case for them right now is entertainment. And I thought that was really interesting from an academic point of view, because I was like, that can't just be the only thing humanoids are good for. But maybe, but maybe, but they can't be. I don't know.

• 26:22Speaker 01

  Well, I could say this much, that I've seen non-humanoid robots also dance. In fact, back in 2018, I did see this artist Enterprise put together a robot powered by Nvidia Jetson, which was just, you know, like, going around the dance floor, you know, with different movements, and was not a humanoid. Sure, you can see some entertaining use cases. But that said, humanoid robots in general are a fascinating form factor, because we as humans are used to seeing this form factor. And that's nice, because a lot of these existing spaces, buildings and outdoors, are designed primarily for us. But that said, there's more beyond this form factor. And there's, there are more use cases beyond just thinking about, you know, entertainment

• 27:07Speaker 01

  or for the fact that, you know, it's going to be running through factory lines and so on. You know, you can see Optimus, you can see Neuro Robotics, you can see Unitree, you know, releasing fantastic features with their robots or at least show them as demos. But there's a lot more form factors that we will start seeing. And one of the things, and this is something I want to test it out, and I'm sure probably there are companies that are thinking about it, is that imagine if you wanted to start a business, you know, 10, 15, 20 years from now, and you could maybe commission a set of robots from another entity and specialize these robots to either, you know, do all the lawn cleaning

• 27:51Speaker 01

  or maybe, you know, move products from point A to point B within the factory line. So I think that there's going to be a combination of conscious automation. But that said, also conscious entrepreneurship that will involve robots working alongside with us to start new businesses.

• 28:10Speaker 00

  I guess like, my final question is kind of like, what do you see as the most successful near-term area when it comes to physical AI?

• 28:17Speaker 01

  Well, the definition of near-term could be shifting based on who you ask this question to, right? And also, the definition of physical AI has been shifting. And like I said earlier, you know, physical AI is more than just robotics. I'm really excited about, you know, where things will lead in terms of solving the foundational problems with robotics by itself, right? Having a more easy-to-use deterministic and safe set of products that can enable the ecosystem to build for different industries, whether it's regulated or otherwise too. So that's one area that I'm excited about. Safety standards are going to be more and more important

• 28:57Speaker 01

  in terms of, you know, how you think about robotics within houses versus outdoor robotics and so on. And the third thing that I'm excited about is healthcare. I think in general, there's so much that we could be doing in that space. And which is why the culmination of conscious robotics, material sciences, and life sciences put together is going to be one new disruptive space that I'm investing in.

• 29:22Speaker 00

  And we're just about out of time, but where can our listeners connect with you and find your work?

• 29:27Speaker 01

  Yeah, so you can find more information on techable.vc website. And you can always email me, [email protected].

• 29:36Speaker 00

  Thank you so much again for joining us on the show. This has been a really fun conversation. I'm now looking out for the chat GPT of physical AI. So I'd like to have my eyes and ears open. And for our listeners, you can find me at Dominic Madori on Instagram. Please follow me on Instagram so I can get more followers. And Equity at EquityPod on X. Thank you again. Talk to you next time.

• 30:02Speaker 00

  Equity is hosted by TechCrunch senior reporters and produced by Teresa Locan Solo with editing by Cal. Subscribe on YouTube or wherever you get your podcasts and find out what's next at techcrunch.com/events. Thanks so much for listening, and we'll talk to you next time.