Humanoid Robots Are Getting Real Jobs

Summary

WSJ Tech News Briefing: Humanoid Robots Are Getting Real Jobs

Release Date: March 4, 2025 | Host: Charlotte Gartenberg | Producer: The Wall Street Journal

---

Introduction

In the March 4th episode of the WSJ Tech News Briefing, host Charlotte Gartenberg delves into two pivotal advancements in the tech world: the innovative use of underutilized graphics processing units (GPUs) by startups to democratize artificial intelligence (AI) development, and the burgeoning role of humanoid robots in various industries. This summary encapsulates the key discussions, insights, and expert analyses presented in the episode.

---

GPUs in AI: Startups Challenging Tech Giants

Democratizing AI with Underused GPUs

The episode opens with a compelling question: Could your gaming PC help train artificial intelligence models? Charlotte Gartenberg introduces the idea that a cohort of startups is exploring the potential of connecting virtual networks of GPUs to rival the extensive AI data centers dominated by industry behemoths like OpenAI, Meta, and Tesla.

Insights from Tech Reporter Deepa Sitharaman

Deepa Sitharaman, the tech reporter, elaborates on this disruptive approach. She explains that these startups aim to leverage GPUs that are often underused in sectors like gaming and cryptocurrency mining. According to Sitharaman:

“Right now they are tiny companies that just started last year, but they have this broader, bigger vision of finding a way to fight against the man is sort of how they view the big tech companies.” ([02:03])

These startups contend that major players are monopolizing GPU resources, making it prohibitively expensive for smaller entities to train large-scale AI models. By utilizing GPUs that are otherwise idle, these companies aim to lower the barriers to entry in AI development.

Potential and Risks

While the concept holds promise, Sitharaman acknowledges significant risks:

“There is absolutely zero guarantee that something like this will actually function in the real world.” ([02:53])

Other concerns include ensuring privacy and security within a distributed GPU system. The decentralized nature of this approach raises questions about data protection and the feasibility of maintaining robust security measures.

Notable Advantages

Despite the challenges, the potential benefits are substantial. Unused GPU capacity represents a missed revenue opportunity for companies, and tapping into this resource could enable more players to innovate in the AI space. As Sitharaman notes:

“Lowering the barrier to entry to building AI tools seems fairly meaningful. And that is something that really could change the way we think about AI systems currently and the way that we engage with the technology overall.” ([04:08])

---

Humanoid Robots in Real Jobs

From Science Fiction to Reality

Transitioning from AI infrastructure, the episode shifts focus to the tangible advancements in humanoid robotics. Humanoid robots, once relegated to the realms of Star Wars and The Jetsons, are now being integrated into everyday roles, particularly in materials handling within warehouses and manufacturing facilities.

Expert Analysis by Christopher Mims

Tech columnist Christopher Mims provides a comprehensive overview of the current landscape of humanoid robotics. He identifies leading companies poised to sustain their presence in the industry:

1. Apptronic – Based in Austin, Texas, Apptronic focuses on producing affordable humanoid robot bodies, making them more viable for widespread use.
2. Agility Robotics – Pioneers in deploying humanoid robots in production environments, notably at Spanx's warehouse in Atlanta, Georgia.
3. Tesla’s Optimus – Backed by significant investment, Tesla is developing an AI-powered humanoid robot aimed at comprehensive task automation.
4. Boston Dynamics – Renowned for their advanced robotics, Boston Dynamics continues to innovate with humanoid models, despite limited disclosed customer testing.

“The effective hourly wage of their robots... they say they're saving companies money.” ([10:06])

Expanding Roles Beyond Logistics

Mims highlights that while current applications are primarily in logistics, the future holds broader possibilities:

“Eventually these robots are going to be flexible enough that they will probably show up in the service industry... one of the goals is to make them part of elder care.” ([07:57])

Potential roles include assisting in elder care by helping individuals with mobility, personal care tasks, and daily activities, addressing labor shortages in this critical sector.

Technological Advancements Driving Progress

Several technological factors are enabling the enhanced capabilities of humanoid robots:

• Affordable and Advanced Components: The reduction in costs for parts such as camera systems, joints, and actuators, many of which benefit from advancements in the smartphone industry.
• Improved Actuators and Motors: Enhanced precision and power efficiency are crucial for the practical operation of robots without constant recharging.
• AI Integration: Leveraging AI models similar to those driving conversational agents like ChatGPT to animate and control robot movements.

“People have done a lot of work in terms of making those stronger, more precise later, use less power.” ([08:33])

Challenges and Future Outlook

Despite progress, significant hurdles remain:

“Moving a robot body is 100 a thousand times more complicated than making a chatbot.” ([11:08])

The complexity of real-world environments and the lack of extensive datasets for training robot movements pose substantial challenges. Additionally, translating simulated learning to real-world applications requires overcoming unpredictable variables and safety concerns.

Industry Perspective

Jensen Huang, CEO of Nvidia, envisions a transformative "ChatGPT moment for robotics," underscoring the optimistic yet cautious outlook on the integration of sophisticated AI into humanoid robots.

---

Conclusion

The episode of WSJ Tech News Briefing masterfully navigates the cutting-edge developments in AI infrastructure and humanoid robotics. By highlighting the innovative strategies of startups challenging entrenched tech giants and the progressive strides in humanoid robot applications, Charlotte Gartenberg and her expert guests provide a comprehensive view of the future of technology. As GPUs become more accessible for AI training and humanoid robots transition from warehouses to broader societal roles, the landscape of technology continues to evolve dynamically, promising both opportunities and challenges ahead.

---

For more in-depth discussions and exclusive interviews, listeners are encouraged to tune into the latest episode of the WSJ Bold Names podcast, available on all major podcast platforms.

Transcript

[Advertiser]

Your data is like gold to hackers. They'll sell it to the highest bidder. Are you protected? McAfee helps shield you blocking suspicious texts, malicious emails and fraudulent websites. McAfee Secure VPN lets you browse safely and its AI powered tech scam detector spots threats instantly. You'll also get up to $2 million of award winning antivirus and identity theft protection, all for just $39.99 for your first year. Visit mcafee.com/incancel anytime terms apply.

[Charlotte Gartenberg]

Welcome to Tech News briefing. It's Tuesday, March 4th. I'm Charlotte Gartenberg for the Wall Street Journal. Could your gaming PC help train artificial intelligence models? A handful of startups are looking to stitch together virtual networks of graphics processing units, or GPUs to compete with massive AI data centers. We'll hear how underused GPUs, the advanced computer chips that power AI, might open the door to new AI players. Then Star Wars, C3PO and the Jetsons, Rosie the Robot are still the stuff of science fiction, but humanoid robots might soon be helping us do more everyday tasks. WSJ tech columnist Christopher Mims tells us what the latest humanoid robots are doing and the tech that could bring them into our homes. But first, tech CEOs like Elon Musk, Mark Zuckerberg and Sam Altman think that dominating an AI will come from amassing as many GPUs as possible and networking them together in massive data centers. But what if there's another way? For more on that, we're joined now by our tech reporter Deepa Sitharaman. Deepa, you spoke with some startup founders who believe that underused graphics processing units could bring AI success to companies that are not quite as well resourced as the OpenAI's and metas of the world. Who are some of these people and what are they proposing?

[Advertiser]

Right now they are tiny companies that just started last year, but they have this broader, bigger vision of finding a way to fight against the man is sort of how they view the big tech companies. In their view, there's a lot of resource hoarding. The big OpenAI's of the world, the X AIs of the world like the Elon Musk, Sam Altmans, Mark Zuckerbergs, they're all pulling together and buying up what are already these crazy expensive GPUs, ensuring that they're the ones that can train gigantic models or make models work. And here you have these companies that say it doesn't need to be like that. Having said that, it's a huge risk. There is absolutely zero guarantee that something like this will actually function in the real world.

[Charlotte Gartenberg]

What devices use GPUs that might theoretically be stitched together?

[Advertiser]

GPUs were originally built for gaming and there are a lot of gaming rigs out there that have GPUs where somebody isn't gaming 24 hours a day and so it lies idle at least some of the time. Additionally, GPUs were used for things like crypto mining. You can also just utilize those things. There's not like 100% utilization necessarily on these types of GPUs. Plus there's a lot of companies that, for whatever reason they might be dealing with sensitive data. They're deciding to have their GPUs in house so that if they need to use these big AI systems, they can rely on their own GPUs and not go elsewhere. Just from a data protection standpoint, those guys aren't using GPUs 24, seven necessarily either. And that GPU is network and hooked up and online and gobbling up power. That's a revenue opportunity missed.

[Charlotte Gartenberg]

What risks does renting out your GPUs expose your company to or maybe particular individual?

[Advertiser]

It isn't yet clear what the broader risks would look like. Like how do you ensure privacy and security in this kind of distributed system? The people that are trying to build these models and trying to operate within these data centers, a lot of them are risk averse already. Given that they're already taking this big risk by paying for all these GPUs and trying to do these models. The risks of distribution are maybe something that a lot of entrepreneurs may not even want to take on. So there's the privacy issue. How do you protect data? Those are things that people are going to have to work out. You talk to the entrepreneurs, they think all of this can be sorted out in time. Lowering the barrier to entry to building AI tools seems fairly meaningful. And that is something that really could change the way we think about AI systems currently and the way that we engage with the technology overall.

[Charlotte Gartenberg]

That was our tech reporter, Deepa Sitharaman. Coming up. Where's my robot made? Tech has not yet made Rosie the Robot, but humanoid robots are finally getting real jobs. We'll find out where after the break.

[Capella University Ad]

Imagine what's possible when learning doesn't get in the way of life. At Capella University, our game changing Flexpath learning format lets you set your own deadline so you can learn at a time and pace that works for you. It's an education you can tailor to your schedule. That means you don't have to put your life on hold to pursue your professional goals. Instead, enjoy learning your way and earn your degree without missing a beat. A different future is closer than you think with Capella University. Learn more at capella. Edu.

[Charlotte Gartenberg]

Newly powered by AI brains, humanoid robots are becoming increasingly capable. Currently they're mostly used in what's known as materials handling, basically moving things around in warehouses and manufacturing facilities. And while these are generally low stakes tasks, humanoid robots could save money for companies that use them. Here to tell us about the tech powering these bots and what's next for the industry is our tech columnist, Christopher Mims. Can you talk to me about some of the startups and companies and some specific humanoid robots that you've seen lately?

[Christopher Mims]

Okay. This is Christopher Mims. Top humanoid robot companies in order of likelihood that you'll actually hear about them again five years from now. And they will won't just be gone. All right, number one, Apptronic. Apptronic is a Austin, Texas based company. Their focus is on making humanoid robot bodies as affordable as possible. So that's good in terms of making them viable. Agility Robotics. They are the first in the world to really be used in production. In a Spanx warehouse outside of Atlanta, Georgia, they're moving Shapewear Reflex Robotics. They're doing cool stuff with a logistics company called gxo. Picture a robot picking stuff out of bins and putting them in boxes to be shipped to. You can't count out Tesla's optimus robots. There's figure they just got a boatload of money and they claim to be building kind of start to finish an AI powered robot. There's Boston Dynamics. They've been at it forever. They make those terrifying big dog robots that you've seen videos of on the Internet and now they make humanoid robots. And they don't have any tests with customers that they're willing to tell me about yet. But they're good at what they do and they've had more experience at it than anybody.

[Charlotte Gartenberg]

You talked about some of the job tasks that they're taking on a lot of logistics stuff in warehouses. What other tasks are you seeing those robots take on?

[Christopher Mims]

Eventually these robots are going to be flexible enough that they will probably show up in the service industry. You could picture them working in the back of the smoothie shop again, doing materials handling mostly in the future, one of the goals is to make them part of elder care. So a lot of elder care is just helping people move around, helping people shift in and out of bed or go to the bathroom or feed themselves. These are all applications where these robots could really help tackle the labor crisis in that industry.

[Charlotte Gartenberg]

What's the tech that's helping current robots do more than before?

[Christopher Mims]

So robots, they're different than other computers in that they have bodies. So one big thing that's helping them is all the parts that make up their bodies are getting cheaper, they're getting more capable. Their camera eyes, that all comes out of the cell phone supply chain. We've gotten really good at making that kind of thing. Their joints, their limbs, their actuators, their motors, their equivalent of our muscles. People have done a lot of work in terms of making those stronger, more precise later, use less power. That's really key because these robots, unless you want them plugged in all the time, they got to run on batteries, and they apparently really chew through batteries pretty quick. Then there are their brains. And there have been a lot of breakthroughs lately in terms of using the same kind of underlying AI that drives things like chat GPT to learn how to animate a robot body. And pretty much all these companies are betting that that innovation's gonna continue at a pretty swift pace in order to make these robots more versatile.

[Charlotte Gartenberg]

You spoke with Ayanna Howard, who's dean at the Ohio State University College of Engineering. She's a former robotics researcher at NASA's Jet Propulsion Lab. She's a startup founder, and here she is on our Bold Names podcast.

[Capella University Ad]

Humanoid robots is the next shiny penny that's out there that tech folks and VCs can invest in those who aren't in the robotics. It seems like the next logical step around artificial intelligence and generative AI is, oh, let's think about generative AI with the physical embodiment.

[Charlotte Gartenberg]

Christopher, how close are we to truly useful humanoid robots that say, think with AI?

[Christopher Mims]

So we have truly useful humanoid robots today that are able to do really basic stuff, just like moving things around inside of warehouses and factories. The challenge, honestly, is how are we going to make them affordable? The companies I talked to claim that the effective hourly wage of their robots, so they don't sell these robots, they rent them out for a wage like a human is, such that from day one, they say they're saving companies money. That doesn't mean that these startups are making money. If you could make one cheap enough, it could have pretty limited utility and you might still want to use it. But if it's really capable, maybe at that point the cost of the robot compares favorably with a human worker who has to take breaks. And gets benefits and labor protections and everything else.

[Charlotte Gartenberg]

How is particularly the AI going to be leveraged to get us where some of these companies are hoping to go?

[Christopher Mims]

It's really unclear. So the CEO of Nvidia, Jensen Huang, has said he thinks we're soon going to have what he called a chatgpt moment for robotics. That's a bold claim, because moving a robot body is 100 a thousand times more complicated than making a chatbot. And when it comes to what makes modern AIs work, it's how much data do you have available to train them? We had an Internet's worth of text to train chatbots on. There does not exist an Internet's worth of instructions for how to move robot limbs. So all these companies are having to come up with their own data. So they got to test the robot in the lab. A lot of the training is done in simulation, and then they have to translate that learning from simulation to the real world. And just the real world is monstrously complicated. And frankly, it's full of fall hazards as well. So that's going to be a problem if you're walking around and you're a robot.

[Charlotte Gartenberg]

That was WSJ tech columnist Christopher Mims. You can hear more about humanoid robots and AI on the latest episode of our Bold Names podcast. Find it wherever you get your podcasts. And that's it for Tech News Briefing. Today's show was produced by Jess Jupiter with supervising producer Kathryn Millsop. I'm Charlotte Gartenberg for the Wall Street Journal. We'll be back this afternoon with TNB Tech Minute. Thanks for listening.