Everyday AI Podcast – An AI and ChatGPT Podcast - EP 485: Humanoids in our world. How it’ll work and what’s next

Episode Date: March 19, 2025

Will we see humanoids in the grocery store soon? 🤖One of the few sectors of AI advancing at the same pace as LLMs is robotics and humanoids. Spoiler alert — NVIDA powers the humanoid movement. So what was announced at NVIDIA GTC?Will we be seeing humanoids out and about anytime soon?Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Thoughts on these stories? Join the conversationUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [e-mail] with Jordan on LinkedInTopics Covered in This Episode:NVIDIA GTC Conference and Embodied AIRole of Humanoids and RoboticsIntroduction to Agility Robotics and DigitsState of Humanoids in Logistics and ManufacturingHumanoids' Capability and Shift OperationsNVIDIA Inception Program and Agility RoboticsNew Announcements at NVIDIA GTCIsaac Lab and Whole Body Motion Control DemoNVIDIA Mega PlatformDifference Between Robots and HumanoidsEvolution in Humanoid SpacesFuture Applications Beyond ManufacturingSafety and Integration of HumanoidsOnboard Safety System DevelopmentImportance and Impact of Humanoids in RoboticsTimestamps:00:00 Exploring Humanoids and Robotics03:22 Rapid Advancement of Humanoid Technology06:46 AI-Powered Robotic Motion Control Advances11:22 Humanoid Robots Transform Warehouses13:27 Humanoids in Manufacturing and Logistics18:04 Developing Cooperative Robot Safety19:25 Humanoids: A Permanent Robotics EvolutionKeywords: NVIDIA GTC, Agility AI, Everyday AI, Humanoids, Robotics, Embodied AI, Agility Robotics, Digits robot, Logistics, Manufacturing, Retail, AI trained stack, NVIDIA Isaac Lab, Mega platform, Whole body motion control, Retail grocery items, Simulation environment, AI advancements, Supervisor safety system, Cooperative safety, GTC announcements, NVIDIA hardware, NVIDIA inception program, Energy storage, Actuation, Sheffler customer, GXO contract, Industrial settings, Warehouse automation, Cognitive function.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

This is the Everyday AI Show, the everyday podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. Meet Firefly AI Assistant, now live and Adobe Firefly, the all-in-one creative AI studio. Just describe what you want to create and the assistant handles the rest, orchestrating multi-step workflows across Photoshop, Premiere Express, and more in one conversational interface. You direct the outcome. The assistant accelerates execution. One thing that's happening here at Nvidia, GTC, there's much more than, you know, large language

models and GPUs. One exciting area of AI, it's humanoid, it's robotics, it's embodied AI, how we can take all of these innovations and make our actual worlds that we live in better, our jobs, hopefully safer and maybe even more enjoyable. So that's one of the things that we're going to be talking about today on everyday AI. What's going on, y'all? My name's Jordan Wilson, and I'm the host of Everyday AI, and this is a daily live stream podcast and free daily newsletter, helping everyday people like you and me, not just keep up with what's happening in the world of AI, because there's a lot, but how we can use it to get ahead to grow our companies and our careers. If that sounds like what

you're trying to do, you're in the right place. And I'm excited for today's conversation, because one thing, you don't have to be scared of humanoids, right? We're going to understand in today's conversation what they actually are and talk about what is the future of humanoids and robotics and how they're going to impact the future of our work. All right, but don't worry if you're on the podcast, maybe I sound a little different, but I'm actually reporting here live at the Nvidia GTC conference or we're extremely lucky to be able to talk to some of the leaders bringing AI in this case to the real world.

So please help me welcoming to our live stream audience, at least. We have Pross Velocopović, who is the CTO of Agility Robotics. Pras, thank you so much for joining the Everyday AI show. Thanks for having me. All right. So before we get into, you know, humanoids and robotics and talking about all this, first, tell us a little bit about what it is that you all do at agility. So at Agility Robotics, we have our humanoid robot digits.

It's a logistics and manufacturing focused robot right now, but it is a humanoid with the ability to move in work in human spaces. And so we can do a lot of tasks like moving around bins and loading, unloading equipment in a form factor that doesn't really require you to modify any of the spaces that you have already. You can use human shelves and human totes and other things like that. And so what we're building out is basically this platform to be able to take our robot out into the human world and be able to do all sorts of work, starting in logistics and manufacturing, but ideally moving into retail and maybe one day the home. Okay. I'm excited to talk about that, even getting humanoids into the home. But I want to rewind a little bit, right? Because even at this conference last year, right, there was a lot of a talk and excitement around humanoids, right? Can you talk a little bit? Bring us to the current day. Where is the space at right now? Not just the amazing work you all are doing in agility, but where?

There's the humanoid's kind of progress at because it seems like it's always changing. It's hard to keep up with. What are they capable of? Are they actually out there doing jobs today? Like, where are we at? Yeah. So it's been moving really quickly. You're definitely right about that.

In the past year, what we've seen is this convergence of technologies, both in the hardware, in things like energy storage and actuation and in the software with all of the advancements in AI, has really enabled a lot of technology. to come together to make the humanoid platforms that you see in a lot of videos and things like that today. And we're right at the cusp of this kind of explosion of the capabilities of these platforms being able to make it out into the world. And so where we are right right now, I think, is that there's a lot of humanoids that are emerging in the market. And there's a few that are making the transition to being able to do true useful work out there. So we're one of them.

We have customers right now. Our robots can work in full shift operation in facilities, and they do, where they're working full eight-hour days. So we're just starting to see that happening in the market where there's actually this ability for a humanoid robot to come into something like a logistics or warehousing or manufacturing facility and do a job, a useful job. And usually the types of jobs that really it would be great for humans to never have to do moving around heavy objects, you know, crouching really low, loading and unloading things.

These types of repetitive tasks that, you know, really we have humans doing it mostly because they're inconvenient to automate, not because there's such, you know, valued, loved jobs by the people doing them. All right. So I have to have a follow up on that right away. Why are the human only working eight hours? Why aren't they working around the clock, right? So great question. They absolutely can work longer than that. It's just we happen to be. in some facilities right now that that's when the rest of the system is working because there are humans upstream and downstream of us. But the robots themselves, you're absolutely right. We can run two or three shifts with the same robots. They don't care. They can run continuously.

But we are limited, or not limited, I'd say we have to be matched up to what the process around us is doing, which is sometimes robots on either side of us doing other types of tasks and sometimes humans upstream or downstream that are doing other tasks that are related to the overall flow. So I do want to get into what's new at GTC, but first, I want to talk a little bit about your involvement in the Inception program, a lot of great and promising startups. But can you just talk a little bit about what your experience has been like in the Invidia Inception program? Yeah, so it's been a really great connector for us. Invidia in general has been a really great partner for agility and helping it out in a lot of different ways because we both use Nvidia hardware. We use some of their software, and we're really aligned with their product teams in terms of figuring out what to do next and how to focus some of the new technology that's coming out.

And so the inception program has been a great connection point for that in being able to get us training, get us access to some resources that we can use to help accelerate our adoption of Nvidia technologies and really just get us connected and supported in using the pieces that Nvidia has for us. So speaking of NVIDIA technologies, a lot of new announcements this week at GTC. Let's talk about what's new and what are you excited about for agility. Yeah, so we're showing off a demo here at DTC where we're using NVIDIA-Isaac-Lab-trained policies to do whole-body motion control of our robot. So basically, between last year's announcement and this year, we've actually adopted a lot of that technology and gotten it working and now have a control stack that's going to be picking and placing retail grocery items using a fully AI-trained stack that went directly from

Nvidia's simulation environment to the real robot with no other data, which is really an exciting step for us. We're particularly proud of that, and we're continuing to build out this sort of Isaac Lab ecosystem for ourselves. We're also working on Nvidia Mega, which is a platform that Nvidia announced, I think back at CES, which is intended to basically support this distributed workload and simulation of, for example, multiple robots working at something larger, like a facility scale. So we have a customer, Sheffler, that we've been working with, that we're essentially building out the pieces for them to be able to develop out larger scale simulations of things like their entire facility, where they might be using technology.

digit robots and parts of their flows. And so we're building up the pieces to be able to do that. So mega overall is sort of lifting up another level in the robotic space into not just thinking about how do you train and run an individual robot, but how do you train and run fleets of robots across a facility? And so it's a pretty new tool and we're excited to see where that leads. Yeah. And let's get even more elementary here.

Is there a difference between a robot in a humanoid? Is it the same thing? Is it just as the capabilities and the technology gets better, we just refer to them as humanoids, as they take on more tasks that maybe are, demand more cognitive function? Like, is there a difference between a robot and a humanoid? Yeah, so great question.

And I think probably over the years, the sort of terminology has sort of evolved, right, based on our conception of what robots are capable of. Humanoids are, they're a class of robots. They're typically used to refer to robots. that either look a lot like humans in terms of their form factor or can do things in human environments to some extent. Like they can operate in a human home in a human space and do things the way that humans would

do without special accommodations. So I think it's maybe a little bit different from saying that all robots will eventually converge to humanoid. That's probably not going to happen. There's a lot of very effective robots that are good at what they do in other form factors other than humanoid form factors, especially when you're talking about things like transporting objects around or dealing with industrial processes where there's very specialized equipment or needs that robots designed for that function can do very effectively.

Where humanoid robots can really shine is in being human-centric in not having to change their environment in order to do their tasks. A humanoid robot can use the same types of containers that you would carry around. In fact, in the demo that we're presenting a GTC, we're using a shopping basket. We just bought off of the internet from a place that sells shopping baskets. There's no special accommodations, right? We're using a shelf that's just literally a store retail shelf, right? And when we're in our customer facilities, we're putting the robot into flows that were previously ones where human labor was doing the work of lifting and moving stuff around.

And so the power of a humanoid platform, I think, is less about, oh, it's specific. got two arms and two legs and, you know, is about so and so high. It's more that, well, I can move into the same spaces that you do. I can use the same types of items that you do. I can do the same types of tasks that you do so that I can come into your environment without you having to restructure everything, often at great expense, to instrument it, reorganize it, and tool it up specifically for any particular robotic piece of things. So it seems like, you know, I was here at GTC last year and I, you know, remember Jensen coming out and, you know,

talking about Isaac and having all the robots. But, you know, how has the humanoid space kind of evolved even over the past year? I mean, is it very common to walk into a big, you know, logistics or warehouse and seeing humanoids? Are we still not quite there? Maybe that's what's coming in 2020. I would say we're on the path there versus where we were last year.

You can at the very least go into some warehouses and see some humanoids, which is definitely different from even a year or two ago, right? We have a multi-year contract in place with GXO, for example, where there's humano working in a facility in one of their facilities all day, every day. I think adoption is not quite at the level where that's at every warehouse. But now it's definitely been established that this is a thing that's possible, that you can get real value out of doing it. And we're also seeing a great acceleration in the capabilities and the speed at which we're seeing evolution in the platforms that are available. So the performance of the systems is going up, the types of capabilities and flows that we're

able to take on and sort of like get too close to human, not at human performance, because you don't necessarily need that, but enough to be valuable to someone to not have a human doing the same tasks, we're able to cover an increasing amount of that space. So I'd say that for us, we're really seeing this ramp in velocity. I think if you look out into the media space, you're seeing a lot of really cool demos of that functionality in lab environments right now. And I think that's going to, that inertia is going to continue into what will be capable of in the real world, in reliable in industrial settings and manufacturing settings and things like that to start out and then move from there. Yeah. And where do we move from there? Right. So

whether you want to talk specifically, you know, agility and in the type of, you know, companies that you're looking to work with in the future or just more generally about the types of work, but, you know, manufacturing, warehouses, that makes sense. But where might we be going next? I mean, I'm, I assuming we're not going to have humanoids having like desk jobs, right, traditional desk jobs, but you said they're probably going to end up in our homes. But what are, what's another type of work that that humanoids might be very well suited for outside of, you know, manufacturing?

Yeah. So first of all, there's plenty of manufacturing to be done. Logistics and manufacturing alone is, you know, tens of thousands, hundreds of thousands, you know, maybe millions of robots right in that space alone. But going beyond that, you can think about things like working in the back of the store and retail, things like restocking shelves, things like moving material around in hospitals or other types of environments.

And when you think about, okay, why these environments and not other ones, why are we even starting in logistics and manufacturing? There's actually a pretty good reason, which is that those are the environments in which the structure and the training are most amenable to meet humanoid robots where they are in terms of safety. So a humanoid robot, especially one that can do useful work, it's got a lot of capability, but that's also a lot of energy and force that it can use to do things in the world. And unlike other types of robots that just need to avoid ever touching anything, right? which, you know, a self-driving car for most of its lifetime is mostly concerned with not touching anything, right? Like that's its measure of success, right? You get in the car and then it gets to the destination while not touching anything else, right?

But with a humanoid robot, a core part of what it's doing is touching stuff all the time. And that means that we really need to understand, okay, how do we safely impart our forces on the world? Logistics and manufacturing has a long history of using automation. And so it means that there's a good starting point. The rules in some sense are more understood. As we expand out from there, we kind of have to figure out what those rules are going to be in other parts of society. If we were to put a humanoid in the home like today,

well, there's a lot of gray area in terms of exactly how you would ensure that it could be safe and what types of things around it might be reasonable. You know, how does it handle things like pets or children? Is it okay for it to be carrying a hot pot of something, right? Because even if it doesn't cause a problem, like it could spill something, right? All of those are, I think, societal things that will take some time to be figured out, right? Both our comfort levels as a society and also how the technology can advance to be able to provide better guarantees about that stuff. But one place where we can do it right now is in logistics and manufacturing.

And then from there to things like commercial applications. So that's why that evolution, I think, is the likely progression is because it followed. is basically where we have a better idea of not just how to make the humanoid to do the work, but also how to safely get them out in the world such that when they're being relied upon to work every day all day, that all those statistical edge cases of like, what if you have a slippery floor one day or what if somebody mishapts something, it's overflowing? Like, will you tip it over or things like that? All those can be reasoned about and covered.

Yeah. So I think even when in a lot of probably our audience, their day-to-day right now interactions with AI are using large language models and, you know, fine-tuning them on their company's data and, you know, bringing in rag pipelines and all of those things. But, you know, when business leaders who are listening now and they're, you know, maybe very curious about how they might be able to integrate, you know, humanoids into their workflows, there's probably a bit of, you know, maybe some apprehension, right? Because I think with AI, it's like, okay, well, I'm going to go in. I'm going to tell a chat bot this. You know, I'm going to initiate something where humanoid are essentially, you know, they're out there. They're kind of doing their own thing, right? And that's what they're programmed to do.

So, you know, how can you, you know, what are you all doing to kind of address the whole safety piece? Because I know that there's, you know, sometimes people, you know, think, oh, you know, this is just Terminator, but it's not. Right. So, like, how do you address the safety and the guardrails of a humanoid? So right now what we do is by having a completely independent supervisory system. So we have our safety system and we have our control system. They sort of operate in parallel. And that's the easiest way to do it.

And so it's a good starting point. But right now we tie that external safety system to whatever the robot's operating within. So that might be a work cell. It might be something like laser curtains or external sensing. We basically pair the robot off with some aspect of its environment that's used to tell how close are humans getting and where could hazards be introduced. Now, where we're going from this

is to take all of that sensing and reasoning about where people are and where we could induce these hazards and bring it onboard the robot. So that's what we're doing over the next year is basically building out an onboard safety system on the robot to be able to get to what we call cooperative safety, which is humans and robots being able to safely be in the same space.

And we want to achieve that without requiring anything special in the environment the way that we do right now. So I think that is kind of how we can get to this kind of safe operation without requiring any sort of unobtainium. Like we require, you know, generalized AGI. It's like, no, no, we just require a very well-designed safety semantic about like how the robot responds to people that's run on a reliable, verifiable system. And then we kind of run it in parallel to the AI models that are making decisions about performance, like how to move quickly, how to grab things. We're sort of running a separate parallel system, which is just reasoning about is the thing undoing going to cause a hazard or not. So we've covered a lot in our short conversation already. But as we wrap up, what do you think is the most important or maybe even most exciting takeaway for you and what agility is doing in announcements here at GTC?

what do you think is going to be, you know, maybe that thing that is going to be most impactful for the everyday person and how they work in the future? I think the biggest thing is that we're seeing that humanoids are a real thing and they're here to stay, right? This is now just a new piece of the puzzle in robotics and automation. It's not some far-off abstract concept or a thing that's in a lab. It's okay, now when I want to choose how to do something in the real world, one of the options is just a humanoid robot. And the performance and the capabilities are only going to get better from where they are today. And they're doing so at this just astonishing pace.

So I think people who are interested, you know, check in, take a look at some of the stuff that we can do, take a look at what the space can offer. And basically, you should keep checking in because I think every six months, every nine months, that waterline is going to keep going up at an astonishing rate. All right. It's extremely exciting to watch and follow this space. and, you know, hey, you know, he mentioned a lot about some of these demos. So we're going to be, you know, sharing those in our newsletter. So make sure if you haven't already, please go to your EverydayAI.com. Sign up for the free daily newsletter.

We're going to be recapping today's conversation. And, you know, for the podcast audience, you'll be able to see a lot of what Praz was just talking about in action. So, Pras, thank you so much for taking time out of your day to join the Everyday AI show. We really appreciate it. Thanks again. All right. Thank you so much for tuning in a lot more exclusive insights.

talking with some of the brightest minds in AI at NvidiaGGC. Thank you for tuning in. Hope to see you back tomorrow and every day for more everyday AI. Thanks y'all. Meet Firefly AI Assistant. Now live in Adobe Firefly, the Allman One Creative AI Studio. Just describe what you want to create in your own words and the assistant handles the rest, orchestrating multi-step workflows across Adobe Creative Cloud apps,

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