AI Roundup: Anthropic, OpenClaw, layoffs, and more

0:00On pioneers of AI, we often talk about the responsibility that comes with building powerful technology. AI isn't just one thing. It's a force reshaping medicine, education, science, and the stories we tell on screen. And for that future to work, it needs infrastructure that's built thoughtfully and deliberately. As the essential cloud for AI, core weave empowers pioneers at leading AI labs and enterprises with a purpose-built cloud made specifically to train and run the world's most advanced models. They help accelerate the breakthroughs that matter at scale. The big ideas, the moonshots, the futures we haven't imagined yet. Ready for anything? Ready for AI. To learn more about how core weave powers the world's best AI, go to coreweave.com slash ready for anything. One reason the Department of War wanted to take this action in the way that it did is specifically to intimidate other companies into compliance.

1:05I think it really wanted to send a message here like you either get on board with doing things the way we want, or the consequences are going to be very severe. Are companies really cutting jobs because of the productivity gains of AI? In some cases, companies are saying that these cuts are due to AI. When actually, you know, they're using that as an excuse to cover up for poor business decisions. A lot of these Gulf countries have big ambitions to be AI hubs. How does this instability threaten or reshape these ambitions? Iran did launch some drone attacks and missile attacks against data centers in the UAE and in Bahrain. It was really the first time that we saw deliberate targeting of data centers. Jeremy Khan is the AI editor at Fortune and my co-chair at Fortune's brainstorm AI conference. He is my go-to person to unpack what is happening in the AI space beyond the headlines. And there's a lot happening right now. There's a standoff between Anthropic and the Pentagon, the rise of AI agents. And of course, the instability in the Middle East and how that could reshape the AI industry.

2:11Even for someone like me who's in the AI space day in and day out, it feels like a lot. But it's so hard to keep up. There's a lot of uncertainty. I don't know, just a lot of confusion. So let's try to make sense of it all. I'm Rana Elkhayubi and this is Pioneers of AI, a podcast taking you behind the scenes of the AI revolution. Hi Jeremy, it's so good to see you again. Thank you for joining us again on Pioneers of AI. Oh Rana, it's great to see you and thank you for having me back again. Alright, so let's dig into it. Let's start with Anthropic. This all kind of started to unfold over the last few weeks. It's definitely still important, Rana. And it is an ongoing situation because Anthropic has now sued the Department of War to try to overturn this decision to label them a supply chain risk.

3:11They have filed for an injunction actually to stop the ruling from going into effect. So Anthropic filed two lawsuits actually, one in California and one in the DC area. And there have been some hearings, initial hearings in both of those cases. And we will see how, you know, what happens there. A lot of legal experts, you know, I've talked to you think Anthropic has a very good case. Whether they will get injunction is sort of another matter. I want to kind of rewind a little bit. So this has been brewing for many months. Really since the US government has been working more closely with the big kind of AI companies. But it really escalated when Anthropic demanded that the Department of War not use their technology for domestic surveillance or for fully autonomous weapons. Which then the Trump administration deemed Anthropic to be a supply chain risk. Which I guess this is the first time in US history that an American company is deemed a supply chain risk. Why is this such a big deal? Yeah, so this is really an unprecedented decision by the US government.

4:15The supply chain risk designation was actually developed in order to prevent foreign suppliers that might pose a sabotage risk from entering the supply chain of defense products. A lot of legal experts say it's really inappropriate for the Department of War to have used the supply chain risk destination essentially in a retaliatory way. They were quite happy to buy in Anthropic technology other than these two red lines. And it was really a contract dispute that went awry. They couldn't reach contract terms that they could agree on. So a lot of people said, okay, fine, you cancel the contract. But to go further and try to label them a supply chain risk. Which means that any defense department contractor cannot use Anthropics Claude models in the fulfillment of a Department of Defense contract. A lot of people feel like that's going too far. And actually the Department of War, the Secretary of War Pete Hegseth had tried to interpret this supply chain risk ruling even broader than that. He tweeted out on X that the designation meant that anybody who had a defense department contract

5:19had to cease all commercial relationships within Anthropic. Which legal experts say there's just no basis for that in the statute. Even if the supply chain risk designation holds, it should apply only to the work that companies do in fulfilling defense department contracts. It should not mean that they have to sever all commercial relationships within Anthropic and not use Anthropics models for any purpose. Yeah, because that would also mean like for example, major providers like AWS or Google Cloud, for example, both use Claude, right? Technically they would have to stop that. Yes, not only do, does AWS and Google have this close relationship with Anthropics? Close relationship with Anthropics, they're also investors in Anthropic. Some people said if you really take the Hegseth interpretation, they'd have to divest from those investments. It really would be, as some people said, if you take that very broad interpretation and existential threat to Anthropic, it probably would be the end of them as a company. You know, I'm personally really fascinated by this because as you know,

6:21when I had my company affectiva, we had very strong, very similar language actually in our terms and conditions when we were licensing our technology. Obviously, this is at a very different scale, but it's perhaps the most prominent example where AI ethics and alignment is coming head-to-head with government use. What do you make of that? Yeah, no, it's fascinating. It's one of the reasons this is such an important issue. It speaks to this wider question about who is going to control advanced AI? And who is going to decide what guardrails should be in place around this technology's use? A lot of AI policy people, I talk to say, you know, we really need Congress to act here. There should be laws around this. It should really be up to democratically elected representatives to make these decisions and set these high-level rules. How do we want AI used in war within the US military? What do we think about the use of AI for potentially the surveillance of US citizens? Those sorts of decisions need to be made really by Congress,

7:22but Congress hasn't acted. As you know, Congress has yet to pass any real federal AI regulation. And in the absence of that, we're falling back on things like a contractual negotiation between one part of the government and anthropic. There's also some questions about what the whole industry does. I mean, it's very interesting in the anthropic case. Another reason that's so important is if you look at the number of amicus briefs that other people have filed in support of anthropic, it includes a number of very prominent AI researchers and computer scientists who work at other AI companies. It also includes Microsoft itself as a corporate entity. They filed an amicus brief supporting anthropic position. So I think it's very interesting. This is a case that's going to have really big ramifications for these big questions about, you know, how do we govern AI? What does it mean for the AI industry, but industry at large, if a company can be penalized for saying no to the government? Yeah, that's a great question. A lot of people feel that the, okay, if you can't reach a contractual agreement,

8:24is it fair that the punishment for that is that the government can essentially try to destroy your business? And a lot of people are saying no, that's very un-American. But it's going to have this chilling effect. I think the one reason the Department of War wanted to take this action in the way that it did is specifically to intimidate other companies into compliance. I think it really wanted to send a message here like, you either get on board with doing things the way we want, or, you know, the consequences are going to be very severe. And this is kind of, we've seen this play out several times with the Trump administration where they've taken very punitive action against people who have disagreed with them on some particular policy decision or who they just perceive, you know, are politically not aligned with them. They have sought to punish those businesses. You saw it with the law firms that they felt had done work for the Biden administration or had opposed them in the past some things. You've seen it with the universities where they've stripped funding from universities that they feel are not complying with the policies that they want.

9:24And in some cases, those actions have been illegal, but they've had this tremendous chilling effect. And that seems to be kind of the playbook that they're using here with the Anthropic case. Okay, so as all of this was unfolding, the Department of War worked out a deal with OpenAI. That has also a lot of confusion around it. So where do we stand with that? Right, so yeah, it was a pretty amazing story, right? Right in the middle of this very public dispute while the negotiations were still ongoing. Yeah. You had OpenAI CEO Sam Alman. First of all, come out and say that he agreed with the red lines that his rival Anthropic was trying to impose that basically OpenAI had the same red lines. And then you have just hours later him announcing, oh, by the way, we're talking to the Department of Defense too. And we have reached a deal. And our deal included, according to Sam Alman and according to the National Security Policy Executives at OpenAI, it included language that was attempting to establish the same red lines,

10:28but with one big exception. So the exception was that OpenAI agreed to contract language that says it's okay for the Department of War to use our technology for, quote, all lawful purposes. And then it tries to define further in the contract, critics have pointed out that there's a lot of loopholes here that the Department of War could step through to essentially do the things that it wants to do and could essentially do a mass surveillance, could essentially use autonomous weapons and still comply with the contract. In particular, on the surveillance issue, what anthropic was most worried about was the idea that you could buy a lot of commercially available data. This is data that's available for sale to anyone. And then you could stitch that together using AI to really create quite an accurate picture of the activities of a lot of specific American individuals. And the question is, is that mass surveillance?

11:30And the government is trying to argue it isn't. And a lot of other people say, well, it feels a lot like mass surveillance. We're going to take a short break, more in a minute. If you've spent any time building AI products or leading technical teams, you know this. Transformation doesn't fail because of ideas. It fails because teams can't move together. Enter Atlassian's teamwork collection. It has planning and JIRA, documentation and confluence, video updates in Loom, and now AI Agents Enrovo, which connects the dots across your work so nothing gets lost. It's one AI-powered teamwork platform designed for how modern teams actually build. Learn more at Atlassian.com slash TeamChanger.

12:31That's A-T-L-A-S-S-I-A-N .com slash TeamChanger. AI has moved from possibility to practice. The question now is, how do today's pioneers build it fast, reliably and at scale? From medical research and education to scientific discovery and cinematic creativity, AI is already changing how we understand the world. As the essential cloud for AI, CoreWeave is a leader of that transformation. Delivering a purpose-built AI cloud designed specifically for today's most complex AI workloads, it allows researchers, developers and creators at leading AI labs and enterprises to focus on impact, not limitations, which is how bold ideas become real breakthroughs. CoreWeave was built for this, ready for anything, ready for AI. To learn more about how CoreWeave powers the world's best AI,

13:32go to coreweave.com slash ready for anything. When it comes to AI, we spend a lot of time talking about what it takes to move models from research into reality. Enter LTX2 from light tricks. It's an open-source audio video foundation model built for synchronized sound and video, native 4K output, expressive motion, and precise multimodal control, all running on consumer GPUs. With over three million downloads on hugging face, LTX2 gives you full model weights, training frameworks, and evaluation tools to build real production workflows. Don't settle for a first draft. Get the complete creative engine to reach your ideas full potential. Try LTX2 today at LTX.io slash model. So Nvidia just wrapped up GTC, which is their annual global AI conference.

14:33What are some of the headlines that came out of that? So the biggest headline that came out of the event was Jensen Wang, Nvidia's CEO, saying that he saw a visibility to a trillion dollars of GPU and Nvidia product sales through the end of 2027. So that was like a big headline number. That was twice the amount he had predicted that Nvidia would sell through 2026. So he's saying basically a year later, I can see that we're going to double that number, which is a ready massive 500 billion. And we're going to have a trillion dollars of worth of revenue, which is a pretty astounding number, although it's interesting that Nvidia's stock is priced so highly, that the market did not respond that much. It kind of shrugged it off. And in fact, there was a little bit of a bump up when he first came out with the number, but by the next day the stock was actually a bit down from where it had been. So that was the big headline. But then sort of under that, there were some very interesting other announcements. One of the most interesting I thought is that they said that their next generation server rack

15:33that's going to come out by 2027 is going to include both Nvidia's latest generation via Rubin GPUs, but also these things called LPUs, or language processing units. And those are being made by a company called GROC, which was an AI chip startup, that Nvidia did this partnership deal with early in the year. One of these weird, they're often called reverse aquahires, where they licensed GROCs technology and then hired in to Nvidia GROCs, co-founder and CEO, Jonathan Ross, and also some other members of the founding team. I think what's interesting here is it's an acknowledgement that you might need other chip architectures, particularly when it comes to AI inference. And this was an acknowledgement, really for the first time by Nvidia, that maybe the GPU is not the ideal architecture for inference, and maybe we're going to want to use some other kinds of chips. All right. This is also kind of hot off the press.

16:33Jeff Bezos is apparently raising a hundred billion dollar fund. It's an AI manufacturing fund, to basically buy manufacturing companies and AI buy them, implement AI to speed up their automation, and he's targeting aerospace, chip making, and defense. What do we know about this? Yeah, so this is a brand new announcement from Bezos. They haven't started to make any investments yet, but it is very interesting. And it follows a playbook you've seen a lot of other private equity players thinking about in the past two years, and you've actually seen a number of new sort of P funds be launched with the idea around, it's sort of a similar concept or similar thesis. We're going to buy up a lot of old line companies in existing industries. We're going to add a bunch of AI to them. They're going to be so much more productive, and then we're going to sell them basically back off, and we're going to make a lot of money. We'll see what happens here. It probably is true that some manufacturing in some industries is really backward or really using very legacy processes,

17:36but it's also true that a lot of manufacturers have invested a good amount over the past several decades in automation, in robotics. I wonder where the gains are still, and what companies he is going to buy. Where is he going to go to find these kind of, especially with a hundred billion dollar fund. You're going to be making some pretty big investments, so these have to be fairly large manufacturers, and yet you have to find large manufacturers that have not already implemented a good amount of automation. I think that's going to be interesting to see what he invests in. One of our investment thesis at my fund, Bluetooth Adventures, is that there's a huge opportunity in these antiquated, these huge industries that are maybe not AI forward and coming in and reimagining the workflows. I do believe that this is a huge business opportunity, but I also wonder if we're underestimating the cultural, like the actual workforce challenges to bring people on board and what that looks like.

18:36Yeah, no, I think it's a fascinating area. It is going to be one of the big differentiators. It's like, can you actually get your workforce to think differently? Next, I want to ask you about these AI Neolabs. These are not companies in the traditional sense. They operate really more private research institutions, and they're often founded by former open AI, DeepMind, and Thropic, and Google Brain researchers. And the idea is that they're not really fixated on building a product or shipping product, but it's more like, let's explore what is possible. I'll just share it. Humans and is fairly new. I just saw news about a company called Mirandle that is former and Thropic researchers. They're raising 175 million at a billion dollar valuation, specifically doing AI, R&D for biology and material science. Again, as an investor, I am really curious about these companies because they're raising massive rounds of funding at crazy valuations, pre-product, pre-revenue.

19:36What is the commercial viability of some of these labs? That's a really good question. I think the hope is that they all become open AI or in Thropic, or really maybe open AI is the best example. Because open AI started out, you know, it was doing Blue Sky research. It was playing around with lots of different ideas around how you build more intelligent AI models. It was originally doing a lot of work and reinforcement learning. And then it started doing, playing around with these transformer based language models, kind of on the side. And then suddenly, you know, those took off, it hit it big, and reoriented the whole company around that, and came out with a way to productize it almost by accident. It was sort of an accidental company in some ways. And I think investors may be hoping that lightning strikes twice and you can do the same thing with another lab that they'll, you know, you're going to fund all this Blue Sky research. These guys are really smart. They're going to find something, and then we'll figure out how to productize it, and the money will flow in.

20:36So I think that's kind of the bet, but it is a high-risk bet. And it's quite possible that it won't work out. One of these Neo Labs, called the Thinking Machines Lab, which Miramarati, the former CTO of OpenAI, founded with a bunch of other X sort of OpenAI alums, they've really struggled. So they've, they have put out a small product that helps other AI researchers optimize training. That's their product that they've put out so far. But other than that, it's not really clear what they're working on, and they've started to suffer a lot of staff defections to other AI labs. They lost some people to meta. They've lost some people who've gone back to OpenAI. They lost some people who went to do their own startup. They lost someone to Google. It's like, you wonder what's going on there. And I think part of, you know, from the reporting we've done on it, so far, it does seem like part of the issue has been the lack of a product strategy. And there's been some disagreement among the co-founders about how they, which way they want to build,

21:38and what is their product going to be. And I think that kind of lack of direction or lack of agreement, has caused problems. And you could see maybe that some of the other Neo labs may have some of the same issues. But I am interested to see what happens, because they are all working on interesting kind of outstanding problems in AI. A lot of them are trying to solve issues around continuous learning, or they're trying to build world models, which better understand cause and effect, or they're trying to work on problems around common sense reasoning. There's all these sort of outstanding issues in the field. All right, so Jeremy, there's been massive layoffs at companies like Amazon, Oracle, and Meta. Our company is really cutting jobs because of the productivity gains of AI, or is AI really just becoming a scapegoat for a volatile market? And how can we know? Yeah, that's a really good question. And I think the answer is it's hard to tell what's really happening here. In some cases, there's clearly a little bit of what's being called AI washing.

22:40Going on, where AI's companies are saying that these cuts are due to AI, and due to productivity gains from AI, because it makes the company sound very cutting edge, and they're doing something really smart, and wow, they've really figured it out. When actually they're using that as an excuse to cover up for poor business decisions, and in a lot of cases, they're still trying to unwind tremendous amounts of overhiring that took place really during the pandemic years. Some of these companies tripled their work forces in just three years, and then they're still trying to sort of slim down. But in some cases, I think we really are seeing big productivity gains from AI, particularly around software development, and some of these companies are saying we just don't need as many developers. And the other thing I think you're starting to see, which is AI related, but is not quite about the productivity gains of AI, has to do with the cost of AI, and the cost of the AI capital spending, especially in the case of Oracle and Meta, which are among the companies that are spending tens of billions of dollars to build out AI infrastructure, to build out data centers.

23:43I think in those cases, there's some sense that we need to find saving somewhere else, at least some savings, and one place to find it is labor. And I think in some cases, companies are betting not on present productivity gains, but on hoped for future productivity gains, that they're saying, well, we have to find cuts to compensate for this spending somewhere, we are going to assume that AI is going to enable us to save on increased productivity in the future and save on labor costs, so we're going to make some of those cuts now. And then one other kind of technical thing that's going on, some of these software companies have a tremendous amount of stock-based compensation and also have been trading at really high multiples. And I think there's a sense that as those multiples come down, there's a sense that they're going to have to issue, if they keep the same number of employees, they're going to have to issue even more stock to compensate them, because now each share is worth less. That is going to have this huge dilution effect on existing investors. And I think they're worried about that,

24:43and I think one way to avoid that dilution effect is actually to cut staff. More with Jeremy after a short break. When it comes to AI, we spend a lot of time talking about what it takes to move models from research into reality. Enter LTX2 from LightTrix. It's an open-source audio video foundation model built for synchronized sound and video, native 4K output, expressive motion, and precise multimodal control, all running on consumer GPUs. With over 3 million downloads on hugging face, LTX2 gives you full model weights, training frameworks, and evaluation tools to build real production workflows.

25:46Don't settle for a first draft. Get the complete creative engine to reach your ideas full potential. Try LTX2 today at LTX.io-model. So I want to shift topics now, and I want to talk about AI and the Middle East. As you know, I'm Egyptian. I grew up in the Middle East, so this feels especially close to home. And I've been checking on family and friends who live in the region. There is, of course, so much suffering with the war in Iran, and the ripple effects for the Gulf countries, and, of course, Lebanon too. But I want to talk about the implications of this war on AI in the Gulf states. You know, a lot of these Gulf countries have big ambitions to be AI hubs. How does this instability threaten or reshape these ambitions? Yeah, it's very interesting. I think it's a big outstanding question as we go forward.

26:46We did see in the first week or week and a half of the war that Iran did launch some drone attacks, a missile attacks against data centers in the UAE and in Bahrain. And it was really the first time that we saw deliberate targeting of data centers. Iran even said that they were targeting these data centers because they knew that AWS did work for the US government. Some of the US military applications are run on AWS, including the instances of Claude that were so controversial. But it's unclear if the attacks actually affected any US military operations. But what they did do is they took out a lot of other services for people in the Gulf region. I was talking to somebody who said that a lot of your online banking was down for his bank in Dubai for days after this. It really caused quite a lot of disruption. And I think it's making people question, is this the safe region that we really want to be investing in when it comes to AI?

27:49Do we want to be using these data centers for training, for inference to cover large swaths of the world? The countries in the region, Saudi Arabia and UAE, we're trying to sell themselves as, oh look, our cost of energy is so cheap here, that we can produce intelligence at a much better price point than anywhere else. Therefore, it makes sense to do all your training here. And if you're at least serving any of the geographies near the Middle East, so maybe into Asia or down into Africa, it would make sense, maybe even into Europe, it would make sense to run your inference loads out of the Middle East as well. And I think that's all kind of being questioned now because of this. I was talking again to a friend who works in the AI sector in the Gulf. He thought it might be more of a problem is going to be trying to convince Western AI researchers to come and work in the region. The Gulf nations had been relatively successful, particularly the UAE at doing that. And he thinks that's going to be really challenged, at least for the next few years, that it's going to be very hard to lure high price and rare AI talent

28:56that's not native to the region to come and relocate to the region. I have a lot of American friends who live in Dubai. And I think the UAE in general has, sounds like the UAE in general has done a great job just kind of rallying people and giving people a sense of safety. So I don't know any of my friends who are based in the UAE who are kind of thinking about coming back, but it's complicated. It is also unfolding in real time, so we'll see where it all lands. Right. All right, let's talk about AI agents. OpenClaw was kind of made headlines a few weeks ago and it kind of went viral. It had its viral moment. And I didn't personally try it out because I felt like there were too many security risks. But it is still continuing to grow and apparently especially in China. So tell us more about that. That surprises me. People in China have gone crazy for OpenClaw. I was talking to my colleague who's based in the region and he says it's just nuts. Everybody is using it.

29:57Everybody wants to use it. You had the major Chinese internet companies setting up these kind of kiosk where they would help people install OpenClaw on their laptops. And people were lining up like around the block to get this done. And there were all these stories about little grandma's and aunties who were going to get OpenClaw on their laptops. And I don't know what they were using it for, but they were very enthusiastic to have it. And people have gone wild for it. And I'm actually quite surprised myself because of the security risks that you were talking about. We did a lot of reporting around this. And OpenClaw is not the safest thing to do. It could potentially, depending on what you give it access to, cause you all kinds of problems around data security and privacy. And I'm really surprised. And in the Chinese context, there aren't like a lot of stories about people who've been scammed or losing, you know, vital financial information and stuff due to how vulnerable OpenClaw is to these prompt injection attacks.

30:57It's pretty vulnerable to like potentially importing malware onto your machine. And depending on where it goes out and explores on the internet. So, yeah, I'm surprised, but people have apparently gone wild for it and just love it. And one of the great things about OpenClaw is that it's persistent. It's always on. So it can do stuff for you 24-7. I think people love that idea. And people are kind of eager for that. And it's interesting that OpenClaw has also spawned all of these sort of copycat products that you're starting to see come out from the likes of Proplexity, which created the thing called Proplexity Computer. Microsoft created this thing called Microsoft Tasks. Andthropic created a version of Claw that functions a bit like OpenClaw now. The idea of these other versions was to try to essentially give an OpenClaw-like experience, but try to solve some of those security challenges. You're starting to see what some of the other solutions now being rolled out by the likes of Microsoft is it is easier to configure and set up. I think it's going to have to get really easy for people to get mass adoption.

31:58We use a lot of Anthropics Cloud Code, and we initially started kind of implementing a chief of staff AI agent in the terminal, which took a little bit of finagling, but once you got through the first kind of instantiation of it, it was fine. But now they just have it in their app, and it's a lot easier to connect. Right. So I'm curious to see what the next iteration of these things are. I think they are. The interfaces are becoming more and more accessible by the day. Yeah, yeah, absolutely. Yeah. Yeah, that's exciting. So Jeremy, we covered a lot of ground. So one last question. What is one topic you're watching that we haven't talked about? Oh, gosh. Well, one thing I'm watching is what's going on at Meta. Meta famously spent all this money to create this new super intelligence lab. And they've spent tens of billions of dollars building out AI infrastructure, billions of billions of dollars hiring top AI researchers.

33:00And now we're hearing reports that they've delayed again the release of their latest model, presumably because it hasn't, you know, the training hasn't gone as well as they wanted. It's apparently, you know, maybe not up to snuff yet. Years, rumors about, you know, what's going on there. And they just reorganized how they run AI across the company creating a new AI applications group that reports to their CTO buzzword. So I think that's one to watch. You know, it's like what's actually happening there? That's a story that we're watching. Jeremy, that was fascinating. So much to unpack here. Thank you for joining us. Thanks so much for having me on around it. Pioneers of AI is a weight-watt original production. Our executive producer is Eiff Trope. Our producer is Rachel Ishikawa.

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