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Embracing Humanoids and Robotics: A New Frontier for Business Efficiency
Pioneering the Era of Humanoid Robotics
In the dynamic world of artificial intelligence, humanoids and robotics are setting the stage for a transformative shift across various industries. Recently showcased at the NVIDIA GTC, the integration of humanoids into conventional workspaces signals a leap in technological innovation. For business leaders, this means reconsidering traditional operational models to embrace these advancements as a path to increased efficiency and safety.
Revolutionizing Logistics and Manufacturing
Humanoids like Agility Robotics’ Digits are designed to operate seamlessly within human environments. With capabilities to move and work in spaces built for human activity, these robots can handle tasks such as moving bins and loading equipment without significant modifications to existing infrastructure. This enables logistics, warehousing, and manufacturing sectors to leverage humanoids for tasks that are repetitive and physically demanding, effectively reallocating human resources to more strategic functions.
Current Innovations and Real-World Applications
The past year has witnessed a significant convergence of technologies, enhancing the capabilities of humanoid robots. Many are now operating in facilities, capable of working full shifts alongside human counterparts. And that's just the beginning. With humanoids already functional in logistics environments, the potential for expansion into retail and data sectors is palpable. These developments raise intriguing possibilities for businesses to reduce human exposure to monotonous tasks, thus maximizing workforce productivity.
Unpacking the Mechanics: AI in Motion
Recent announcements from NVIDIA reveal the deployment of advanced technologies, such as the Isaac Lab policies, which enable these robots to perform whole-body motion control—a leap forward in AI implementation. This innovation allows humanoids to operate from a simulation environment directly to real-world tasks without additional input. The implication for businesses is clear: the more complex the AI, the broader the scope of operations these humanoids can undertake, paving the way for more intelligent, versatile, and efficient operational systems.
Addressing the Safety and Integration Concerns
Safety remains a prime concern for integrating humanoids into business workflows. Currently, humanoid robots operate with parallel safety systems, using environmental sensors to ensure safe interactions with humans and objects. This dual-system approach ensures that business leaders can trust humanoids to function without causing disruptions or hazards. As technology advances, onboard safety measures are set to evolve, allowing for more integrated and autonomous cooperative safety systems.
Business Applications Beyond Manufacturing
While manufacturing and logistics embrace humanoids, other sectors stand on the cusp of integration. Opportunities abound in retail for activities like shelf restocking and material handling in hospitals, offering significant efficiency overhauls. The strategic deployment of humanoids is not about replacing jobs but enhancing service delivery, customer experience, and operational efficiency.
Looking Ahead: The Future of Work with Humanoids
As capabilities expand and safety concerns are addressed, humanoids will become mainstays in business environments. For decision-makers contemplating the leap into robotics, now is the time to observe these trends closely. The evolution of these technologies is rapid, and early adoption could equate to competitive advantages in efficiency, safety, and innovation. Watch closely as humanoids move from niche environments to become a ubiquitous component of the everyday business landscape.
By integrating advanced AI-driven humanoids into strategic areas of operation, businesses not only streamline operations but also set the stage for continuous innovation in the future of work.
Topics Covered in This Episode
NVIDIA GTC Conference and Embodied AI
Role of Humanoids and Robotics
Introduction to Agility Robotics and Digits
State of Humanoids in Logistics and Manufacturing
Humanoids' Capability and Shift Operations
NVIDIA Inception Program and Agility Robotics
New Announcements at NVIDIA GTC
Isaac Lab and Whole Body Motion Control Demo
NVIDIA Mega Platform
Difference Between Robots and Humanoids
Evolution in Humanoid Spaces
Future Applications Beyond Manufacturing
Safety and Integration of Humanoids
Onboard Safety System Development
Importance and Impact of Humanoids in Robotics
Podcast Transcript
Jordan Wilson [00:00:17]:
One thing that's happening here at NVIDIA GTC, there's much more than, you know, large language models and and GPUs. One exciting area of AI, it's humanoids, 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 gonna be talking about today on Everyday AI. What's going on y'all? My name is Jordan Wilson, and I'm the host of Everyday AI. And this is a daily livestream, 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 gonna understand in today's conversation what they actually are and talk about what is the future of of humanoids and robotics and how they're gonna impact the future of our work.
Jordan Wilson [00:01:28]:
Alright. 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 Congress where 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 livestream audience at least. We have Pras Velakapudi, who is the CTO of Agility Robotics. Pras, thank you so much for joining the Everyday AI Show.
Pras Velagapudi [00:01:53]:
Thanks for having me. Alright. So before we get into, you know, humanoids and 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 and 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 this basis that you have already. You can use human shelves and human totes and 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 data.
Jordan Wilson [00:02:46]:
Okay. I'm, I'm excited to to talk about that even getting, humanoids into the home. But I I want I wanna rewind a little bit. Right? Because, even at this conference, last year, right, there was a lot of talk and excitement around humanoids. Right? Can you talk a little bit? Bring us to to the current day. Where is the space at right now? Not just the the the amazing work you all are doing at agility, but where is the humanoids, you know, kind of, progress at? Because it seems like it's it's always changing. It's hard to keep up with. What are they capable of? Are they actually out there, you know, doing jobs today? Like, where are we at?
Pras Velagapudi [00:03:22]:
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 and 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 of this kind of explosion of the capabilities of these platforms being able to make it out into the world. And so where 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.
Pras Velagapudi [00:04:11]:
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 or warehousing or manufacturing facility and and do a job, a 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 it. No.
Jordan Wilson [00:04:53]:
All right. So I have to have a follow-up on that right away. Why, why are the humanoids only working eight hours? Why aren't
Pras Velagapudi [00:05:00]:
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 about those. 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.
Pras Velagapudi [00:05:24]:
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 wanna get into what's new at GTC, but first,
Jordan Wilson [00:05:42]:
I wanna, talk a little bit about your involvement in the, inception, program. You know, a lot of great and promising startups. But can you just talk a little bit about what your experience has been like, in the NVIDIA inception program?
Pras Velagapudi [00:05:55]:
Yeah. So it's been a really great connector for us. NVIDIA in general has been a 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.
Jordan Wilson [00:06:35]:
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?
Pras Velagapudi [00:06:46]:
Yeah. So we're, showing off a demo here at GTC, 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 and this year, we've actually adopted a lot of that technology and gotten it working and now have a control stack that's gonna 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 exciting step for us. And so 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 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 Digic robots and parts of their flows. And so we're building out 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.
Pras Velagapudi [00:08:20]:
And so it's a a pretty new tool. We're excited to see where that leads.
Jordan Wilson [00:08:24]:
Yeah. And and let's let's get even more elementary here. Is there a difference between a robot and a humanoid? Is it the same thing? Is it just as the the capabilities and the technology, you you know, gets better, we just refer to them as humanoids as they take on, you know, more, tasks that maybe are demand more cognitive function. Like, is there a difference between a a robot and a humanoid? Yeah. So,
Pras Velagapudi [00:08:47]:
great question. And I think probably over the years, this sort of terminology has sort of evolved, right, based on our conception of what robots are capable of. Humanoids are they're 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 humanoids. 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.
Pras Velagapudi [00:09:45]:
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, we, in the demo that we're presenting at 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 is less about oh, it's it's specifically got two arms and two legs and, you know, it's about so and so high.
Pras Velagapudi [00:10:33]:
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.
Jordan Wilson [00:10:58]:
So it seems like, you know, because I was here at, GDC 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 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 or warehouse and and seeing humanoids, or are we still not quite there? Maybe that's what's coming in in 2025.
Pras Velagapudi [00:11:22]:
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 we have a a multiyear contract in place with GXO, for example, where there's humanoids working in 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, 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 and sort of, like, get too close to human not 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.
Pras Velagapudi [00:12:24]:
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 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 gonna that inertia is gonna continue into what will be capable of in the real world in, reliable and and industrial settings and manufacturing settings and things like that, to start out and then move from there.
Jordan Wilson [00:12:55]:
Yeah. And and where do we move from there? Right? So whether you wanna talk specifically, you know, agility and and and the type of, you 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, you know, manufacturing, warehouses, that makes sense. But where might we be going next? I mean, I'm I I assuming we're not gonna have humanoids having, like, desk jobs. Right? Traditional desk jobs. But you said they're probably gonna end up in our homes, but but what are what's another, type of work that that humanoids might be very well suited for outside of, you know, manufacturing?
Pras Velagapudi [00:13:27]:
Yeah. So first of all, there's plenty of manufacturing to be done. Logistics of 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 the 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 humanoids 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. Right? And unlike other types of robots that just need to avoid ever touching anything, right, which, you know, a self driving car for the most of its lifetime is mostly concerned with not touching anything. Right? Like, that's its measure of success.
Pras Velagapudi [00:14:35]:
Right? You get in the car and then it gets to the destination while not touching anything else. Right? But with the 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, kind of have to figure out what those rules are gonna 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 can 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.
Pras Velagapudi [00:15:27]:
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 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 follows basically where we have a better idea of not just how to make the humanoids do the work, but also how to safely get them out in the world such that when they're being relied upon to work, you know, 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 mispack something and it's overflowing? Like, will you, like, tip it over? Things like that. All those can be reasoned about and covered.
Jordan Wilson [00:16:21]:
Yeah. So I think even when in a lot of probably our audience, their their day to day right now interactions with AI are using large language models and, you know, fine tuning them on 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, some some apprehension. Right? Because I think with AI, it's like, okay. Well, I'm gonna go in. I'm gonna tell a a chatbot this. You know, I'm gonna initiate something. Where humanoids are essentially you know, they're out there.
Jordan Wilson [00:16:58]:
They're kind of doing their own thing. Right? And that's what they're programmed to do. So, you 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 the the safety of the guardrails of a humanoid? Mhmm.
Pras Velagapudi [00:17:19]:
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, and they sort of operate in parallel. And that's the easiest way to do it, 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, you know, 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.
Pras Velagapudi [00:18:04]:
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 wanna achieve that without requiring any 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 unobtanium, 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 kinda 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 I'm doing gonna cause a hazard or not.
Jordan Wilson [00:19:01]:
So we we we've covered a lot in our short conversation already, but, you know, as as we wrap up, what do you think is the most, important or maybe even most, exciting takeaway for you and and what agility is doing, in announcements here at GTC? What do you think is gonna be, you know, maybe that thing that is going to be most impactful for the everyday person and how they work in the future?
Pras Velagapudi [00:19:25]:
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 it's okay now when I wanna choose out of 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 water line is gonna keep going up at an astonishing rate.
Jordan Wilson [00:20:11]:
Alright. It's 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 gonna be, you know, sharing those in our newsletter. So make sure if you haven't already, please go to youreverydayai.com. Sign up for the free daily newsletter. We're gonna be recapping today's conversation. And, you know, for the podcast audience, you'll be able to see a lot of what process is just talking about, in action. So, thank you so much for taking time out of your day to join the Everyday AI Show.
Jordan Wilson [00:20:39]:
We really appreciate it.
Pras Velagapudi [00:20:40]:
Thanks again.
Jordan Wilson [00:20:40]:
Alright. Thank you so much for tuning in. A lot more exclusive insights talking with some of the brightest minds in AI at NVIDIA GTC. Thank you for tuning in. Hope to see you back tomorrow and every day for more everyday AI. Thanks, y'all.
Midroll [00:20:56]:
And that's a wrap for today's edition of everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit your everyday a I Com and sign up to our daily newsletter so you don't get left behind. Go break some barriers, and we'll
Jordan Wilson [00:21:15]:
see