Open-Weight AI Debate Takes Center Stage

24 Jul 2026 · 43 min · 24 chapters

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In short

Bloomberg Tech episode covering (1) a coalition letter urging Washington to embrace open-weight AI models, (2) Intel’s AI-driven earnings and market reaction, (3) Scribe Therapeutics’ CRISPR IPO and epi-editing for heart disease, and (4) additional tech/business headlines including SpaceX Starship and AI infrastructure finance.

Guests and backgrounds

  • Sarah Fry, Bloomberg Tech managing editor (moderates open-weight AI debate).
  • Antoine Shkaivan, head of global technology infrastructure research at New Street Research (Intel stock analysis).
  • Jennifer Doudna, Scribe Therapeutics co-founder and scientific advisor; Nobel Prize for CRISPR.
  • Andrew Feldman, Cerebra Systems co-founder and CEO (AMD partnership for fast inference).
  • Michelle Guida, CEO of the Crack Institute for Tech Diplomacy at Purdue; former U.S. assistant secretary of state for global public affairs.
  • (Also referenced: Intel CEO Pat Gelsinger; AMD CEO Lisa Su; NVIDIA CEO Jensen Huang.)

Key claims

  • Open-weight AI is framed as essential for innovation, competition, and national security; debate centers on Chinese open-weight models’ availability and security risk.
  • Intel’s bull case is “priced in”; even with recovery, structural margin/share disadvantages vs TSMC/AMD/ARM remain.
  • Scribe’s epi-editing aims to change protein production without permanent DNA edits; targets LDL lowering with a one-time/few-time approach.
  • Cerebra + AMD split inference: Helios handles prompt processing; Cerebra generates answers for ultra-fast throughput.

Notable examples

  • Moonshot Kimi K3; Hugging Face open-model security incident; alleged unauthorized distillation and chip use.
  • Intel forecast: AI data-center CPU demand outpacing improving supply; CapEx >$20B.
  • Scribe IPO: $128.7M raised; priced at $15; Doudna discusses phase 1 trial.
  • Cerebra/AMD: Helios + Cerebra server pipeline; disaggregated, standards-based approach.
  • SpaceX: Starship test flight; Falcon 9 bookings reportedly halted beyond 2028.

Written by AI. May contain mistakes. Listen to the episode to check what was said.

Chapters

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Open AI Models and Innovation

0:00 to 0:22

Discussion on the importance of open weight AI models for competition and security.

“With the highest number of young STEM graduates per capita in the EU, Ireland has the people and skills your company needs to succeed here.”

Open AI Models and Innovation

1:43 to 2:46

Discussion on the importance of open weight AI models for competition and security.

“Bloomberg Tech is live from the heart of Silicon Valley with Ed Ludlow in San Francisco.”

The Impact of Chinese Models on US AI

2:58 to 4:18

Exploration of how competing Chinese AI models are affecting US technology policy.

“Bloomberg's tech managing editor Sarah Fry is with us.”

Concerns Over Model Distillation

4:26 to 6:32

A discussion on the implications of unauthorized distillation of US models by China.

“He's talked about the importance of open models, open weight, AI is open source.”

Intel's Earnings and Market Reaction

6:36 to 9:28

Review of Intel's earnings report and current market perception of the company.

“When the earnings hit last night, we saw the stock in after hours go as high as a gain of 13%.”

Intel's Competitive Landscape

9:42 to 12:39

Analysis of Intel's position in the semiconductor market relative to competitors.

“All of that puts Intel in a good position, you know, to, well, number one, as you said, you know, address the huge demand that there is for CPUs in this agentic era.”

Podcast Subscription Reminder

14:00 to 14:17

Learn how to subscribe to the podcast on various platforms.

Innovations in Gene Editing

14:46 to 16:48

Explore how Scribe Therapeutics is transforming gene therapy with epi-editing.

“Scribe Therapeutics co-founder and scientific advisor Jennifer Doudna is with us now.”

Safety and Efficacy in Gene Editing

16:48 to 18:16

Discuss the importance of safety in non-permanent gene editing technologies.

“Let's bring it back to basics, heart disease.”

AI's Role in Drug Discovery

18:16 to 19:05

Understand the current limitations of AI in the field of drug discovery and its synergy with human innovation.

“in ensuring that their strategy, this epi-editing approach, is really, truly safe and effective for the indications they're going after.”
Show all 24 chapters

Market Reflections on Scribe's IPO

19:05 to 20:24

Review the market's reaction to Scribe Therapeutics' initial public offering.

“It's an amazing technology that allows scientists now to accelerate the kinds of work that we do.”

Tech News Highlights

20:24 to 23:06

Get the latest updates on TikTok, SoftBank, and SAP's AI initiatives.

“A story I just want to bring you real quick in the markets.”

SpaceX's Starship and Industry Changes

23:06 to 24:38

Delve into SpaceX's strategic shifts and the implications for the launch industry.

“coming to them wanting either a dedicated ride on Falcon 9 or a rideshare ride.”

Open-Weight AI Debate and National Security

24:38 to 28:00

Examine the debate surrounding open-weight AI models and their implications for national security.

“Hey, guys, welcome back to Bloomberg Tech.”

The Debate on Open Weight AI Models

28:00 to 30:20

Explore the implications of open weight AI models and the competition with China.

“open source models, right, in a way that is detrimental to American interests.”

The Need for Proactive American AI Strategies

30:20 to 31:20

Discuss the necessity for the U.S. to develop its own AI technologies.

“Yeah, I think, look, the president has this great group on his PCAST, this presidential advisory board with a bunch of technology leaders.”

Collaboration with Allies and Lessons from Huawei

31:20 to 32:09

Analyze the importance of international cooperation and historical lessons in technology.

“When I was at the State Department, Huawei was a threat across the world.”

Transition to AI Speed and New Partnerships

32:09 to 32:20

Introduction to the shift in focus towards AI speed and partnerships in the industry.

“So coming up the AI race also shifts to speed.”

Cerebras and AMD Partnership Explained

32:20 to 34:20

Detailed explanation of the Cerebras and AMD partnership to enhance AI performance.

“Shares of Cerebra Systems are down about 10 % right now.”

Revenue Models and Market Size Dynamics

34:20 to 39:40

Discuss how speed in AI contributes to market growth and revenue models.

“How have you guys agreed to do this in a way that is economically equitable?”

OpenAI's Market Impact and Future Directions

39:40 to 42:00

Evaluate the impact of OpenAI on the market and the challenges in measuring productivity.

“Anybody who builds a part that would integrate into an extraordinary solution.”

AI Cost and Productivity Strategies

42:00 to 42:58

Learn about the strategies for improving AI productivity and cost-effectiveness.

“both from China and others, are trying to capture this with a fast-follow strategy.”

Viking Global Investors' AI Positioning

42:58 to 45:13

Explore Viking Global Investors' conservative stance on AI stocks and market risks.

“With AI stocks soaring this year, Viking Global Investors told clients that its conservative position on the sector was a, quote, missed opportunity.”

Closing Thoughts on Tech Earnings

45:13 to 45:27

A recap of the week in tech and upcoming earnings to watch.

“Bloomberg's Hemmer Palmer with a must read.”
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Transcript

Automatic transcript. May contain errors.

0:00With the highest number of young STEM graduates per capita in the EU, Ireland has the people and skills your company needs to succeed here. IDA Ireland, the National Investment Development Agency, can help you find and nurture the people you need to internationalise and thrive. Our talent is just one of the extraordinary benefits Ireland has to offer. Learn more at idaireland.com. Invest in extraordinary.

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1:00Get the news you need in just 15 minutes. Start your day with Bloomberg Daybreak, the podcast with a global view on the stories that matter. I'm Nathan Hager. And I'm Karen Moscow. Join us each morning for curated stories on current events, politics, business, and foreign relations. Plus one conversation on the day's biggest developments, all in just 15 minutes. Subscribe to Bloomberg Daybreak for a precise, thoughtful take on the stories that matter. Listen to Bloomberg Daybreak each morning on Apple, Spotify, or anywhere you listen. Bloomberg Audio Studios. Podcasts. Radio. News.

1:43Bloomberg Tech is live from the heart of Silicon Valley with Ed Ludlow in San Francisco.

1:52Ed Ludlow:This is Bloomberg Tech. Coming up, tech's biggest names are making the case for open AI, arguing open weight models are key to innovation, competition, and even security. Plus, Intel showing signs of an AI-driven comeback, forecasting stronger sales as its data center business accelerates. And AMD and Cerebris are teaming up to challenge NVIDIA, promising some of the fastest AI systems on the market. We speak with Cerebra CEO Andrew Feldman. Our top story this Friday, a major push to shape the future of AI. A coalition of technology companies, CEOs and venture firms is urging Washington to embrace open weight AI models, arguing they're critical to American competitiveness, innovation and national security.

2:38Ed Ludlow:The signatories include Microsoft Satya Nadella and NVIDIA CEO Jensen Wang, who used his very first post on X to share the letter. It argues, quote, the United States should lead in building an open AI ecosystem because it expands opportunity, strengthens competition and extends American technological leadership. Bloomberg's tech managing editor Sarah Fry is with us. The idea of open weight and open source, that's not new. But it was very, very interesting, the timing of the heavyweights of this industry coming out almost in unison and saying we need to think about this area. I mean, it's a huge issue because right now, and they didn't say it in the letter, there is a really intense discussion happening about Moonshots Kimi.

3:26This is a model that just came out of China that is pretty equivalent with U.S. models, and it's changing the way people think about it. Whereas previously, the Chinese models were good open-weight models and able to undercut U.S. models on price, and they were very popular. But they didn't actually get to the point where the innovation looked like it was about equivalent with what you could get from U.S. And that's caused a lot of concern in Washington, maybe some policymakers threatening to change things, restrict things. And, of course, U.S. startups really depend on those open weight models.

4:05So if the U.S. were to have something that was equivalent, that would really help a lot of a lot of the companies. But, you know, everything's getting built right now. And we have a lot of dependence on these Chinese models. I'm very curious what's going to happen in Washington as we digest what this means for the market.

4:25Ed Ludlow:I don't want to trivialize this, but it was fascinating that Jensen Wang elected to create an X account and use his first post as a mechanism to communicate this. For Jensen, this isn't new. He's talked about the importance of open models, open weight, AI is open source. The distinction is if you use a closed model, you go via the API, but you can't see the model. You can't download it. In open weight, you can download and run the train model. The data code aren't necessarily public. On open source, all of it's there available. You were absolutely right to frame this post Kimmy K3. But also with what happened with the open AI mistaken hacking of Hugging Face, it also raised some of the limitations of U.S.

5:14Ed Ludlow:open models because Hugging Face wasn't able to defend itself in that respect. What do you think happens next? How serious is this? Well, I think that it is serious because the whole market is resting on this idea that all of this tremendous capital expenditure investment, the build-out of data centers, it's all going to end up having a return on investment for U.S. companies. There's a whole other factor we haven't talked about yet, which is some concern that these Chinese models are built in part using unauthorized distillation of U.S. models, including Anthropics Cloud. So if all of that investment from the U.S.

5:53companies in their future innovation is then just being used to boost what China can accomplish, whether it's through distillation or through unauthorized chips use, that's a matter of big debate too. And that could really affect the ROI for these companies on the many, many billions that they're pouring in to build out of the future of AI.

6:19Ed Ludlow:That's probably the bit we don't know. You know, why did they do this and why now? Was it to counter distillation? Was it to try and get ahead of what happened with OpenAI hugging face? We'll find out. Bloomberg Sarah Fryer, who leads the team here at Bloomberg Tech. Thank you very much. Let's turn to earnings. Shares of Intel. It's interesting. Now down 3 percent. When the earnings hit last night, we saw the stock in after hours go as high as a gain of 13%. The chip maker delivered a stronger than expected forecast as demand from AI data centers is fueling a surge in its service business, particularly CPU.

6:56Ed Ludlow:CEO Lit Bhutan telling me CPU demand is now outpacing what is improving supply. Joining us now is Antoine Shkaivan, head of global technology infrastructure research at New Street Research. research. He has a neutral rating on the stock with a$115 price target. I want to get into the technology. I want to get into what Intel is actually doing and well. But the stock, you know, I was sat here last night and the gains were massive. Then they eroded. Now we're down 3%. With time, what has the market changed its mind about? I think, I mean, thanks for having me on the show, Adam. I think, you know, what's happening is the market is realizing that actually that's the, even the bull case is already priced in.

7:43Ed Ludlow:Even if you take like an Intel in 2030, where manufacturing is fully turned around, which by the way, we had indications of that yesterday on the print, you have a foundry EBIT margins up nine points sequentially. So they're headed really towards break-even. Even if you assume that in 2030 Intel is fully recovered, they're going to still have some structural cost disadvantages compared to TSMC. And gross margins are never going to reach the same level as TSMC. And in products, even if they're doing extremely well, and even if the overall agentic tide is lifting all boats, Intel is probably going to keep losing share to AMD.

8:28Ed Ludlow:It's probably going to lose share to ARM. You know, you have these hyperscale in-house designs. You have NVIDIA ramping, you know, Grace, Vera, etc. All of that is going to take share from Intel. And if you put all that together, even the bull case, you know, doesn't make much room to the current levels the stock is trading at. Okay, Ed, calm down. remind yourself and the audience that going into the print, the stock was up 170 % year to date. So that might be a part of it. What's interesting as well is that Intel never said they'd fixed everything, just that they were making progress. So the way that Lit Bu explained it to me is that, you know, their processes and production for their own products is improving.

9:10Ed Ludlow:But they're still in a place where demand for CPU in particular is outpacing what is improving supply, right? Right. And you'll remember last quarter, they basically left money on the table because they couldn't meet the demand. Do you recognize that kind of operational progress? Yes. I mean, we heard a lot of very encouraging data points on, you know, capacity increases on the call. First of all, you know, you have yields, of course, that are improving, that directly increases, you know, the output of the good chips that you can produce. On top of that, Intel has a lot of shells that they've been building over the last few years that they can now fill up with equipment.

9:48Ed Ludlow:All of that puts Intel in a good position, you know, to, well, number one, as you said, you know, address the huge demand that there is for CPUs in this agentic era. And two, potentially start addressing, you know, demand from external customers as well. You know, they targeted 15 billion external foundry revenues in 2030. And I think there's increasing evidence that it is actually pretty tangible. So let's talk about CapEx, which will be more than$20 billion now this year and grow over the next couple of years. Lit Bhutan, the Intel CEO, is cautious. He won't deploy CapEx unless he thinks there'll be a return.

10:25Ed Ludlow:How did you interpret all that? Well, I think it's very reassuring for investors to hear that. I think in order to generate that demand, Intel still has to execute. Now, let's keep in mind that EBIT margins for boundary are still in negative territory. Gross margins are probably also still in negative territory. So they still have a lot of progress to make to end up in a situation where they can actually really invest that capex with the confidence that they're going to be able to sell those wafers and turn the profits out of selling those wafers. um now in addition you know like the sort of you you alluded to the 20 billion dollar comment a lot of that is going to be of course for for equipment because as i mentioned they have a lot of tools not space yeah tools not space yeah exactly for equipment and now the question is what happens in 2027 and for that i think uh it's still open-ended you know it depends on whether we can uh you know keep improving those yields keep improving the cost structure of these where it fers and get into positive margin territory for boundary.

11:29Ed Ludlow:Let's widen this out to what's happening in infrastructure. What do we learn from Intel's print about the AI cycle? Well, of course, like the DCAI print is impressive. Like they're growing nearly 60 % of the DCAI business. I think an interesting data point is that Intel also still has a lot of room, to improve their roadmap on the AI XPU front. We're talking about a 2 billion run rate today for everything that's not CPUs in the DCAI segment. They think they have visibility to 4 billion. That's orders of magnitude smaller than, for example, like an NVIDIA that's approaching a$400 billion annual run rate for their data center business.

12:20Ed Ludlow:So I think that's an interesting data point also that Intel still has plenty of opportunities maybe to gain some momentum there. On the CPU front, I mean, it's an excellent 3D cross for AMD. If Intel is growing that quickly, despite, I think, a roadmap that's not that competitive, like if you look at the density of the chips that they're putting out, like the number of threads, the number of cores, which nodes they're manufactured on. I think AMD has a much stronger roadmap. So it's definitely a strong read-a-class for AMD on the CPU front. Anton Schraiban of New Street Research back on Bloomberg Tech.

13:01Ed Ludlow:Thank you very much. Coming up on the show, Scribe Therapeutics, the company behind gene editing CRISPR technology IPO today. And look who's joining the show, Scribe Therapeutics co-founder, scientific advisor, Jennifer Doudna. That's next. This is Bloomberg Tech. Thank you.

13:47Invest in extraordinary.

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14:29Ed Ludlow:Jennifer Doudna won the Nobel Prize for pioneering gene editing technology CRISPR. Today, Scribe Therapeutics, the company she co-founded, just raised$128.7 million in its IPO for a much bigger ambition, using CRISPR to prevent heart disease. Scribe Therapeutics co-founder and scientific advisor Jennifer Doudna is with us now. I've been reading so deeply about this. I think the best place to start is that your lead therapy aims to lower LDL cholesterol with just a single treatment. But distinct and unlike earlier gene editing approaches, you say it does not permanently edit a patient's DNA. Explain why that's such an important distinction and move forward in the technology.

15:14Well, great to be here, Ed. It's an exciting moment in gene therapies because, as you just said, Scribe Therapeutics has a strategy that involves what we call epi-editing. It means making changes in DNA that aren't permanent but alter the production of proteins. We think this is an incredibly important moment in the field because it means we can now use this therapy safely and effectively for common disease.

15:41Ed Ludlow:Jennifer may I ask you know in any IPO there's obviously a reason to do it and raise the proceeds right now where are you in in the cycle and the process and what will you use those proceeds for well Scribe Therapeutics is a clinical stage company we're already in our phase one trial for the first indication the funds that are raised today will help move that forward and progress these therapies so that they can be deployed much more widely. At the start of our conversation, you explained the technology difference. When it comes to regulators, how important is that distinction going to be versus the sort of permanent editing of one's DNA?

16:24Well, Scribe is a company that was really founded on great science and has an amazing scientific team. They've invested the last several years in improving the technology to the point where it's safe and effective to treat disease as a strategy for making non -permanent changes in DNA. So we think that this is going to be an effective way to prevent cardiovascular disease in the future that will be so safe that you can provide it much more broadly.

16:58Ed Ludlow:That's what we're talking about. Let's bring it back to basics, heart disease. And it's amazing, millions of people across America and across the world take statins, right? Every single day. But then there's a lot of evidence, a lot of data to support that then they stop. This is a one single treatment that you're working towards. And I wonder just how important that will be for the behaviors of the patients receiving it. Right. We think about this a lot. I think it's very interesting to think about a way of treating or preventing disease that doesn't require taking a pill every day, right? That is really effectively a one or few time treatment.

17:39That means that people are free of having to remember to take a pill and they don't have to worry about those kinds of side effects. It's a really interesting moment where I think we're going to see a real change in the way that medicine is delivered in the future.

17:54Ed Ludlow:When the Bloomberg Tech audience hear the phrase gene editing, inevitably people have concern. What is it from a safety perspective that they need to understand? Well, the CRISPR technology is built around a strategy for targeting DNA precisely. With any technology, there's always risk. But I think what's exciting about Scribe's approach is that they've invested several years in ensuring that their strategy, this epi-editing approach, is really, truly safe and effective for the indications they're going after. And as we discussed before, this is not a technology now that makes a permanent change to DNA.

18:34And I think that's a real difference.

18:37Ed Ludlow:You had one of the most interesting and engaging conversations I've listened to this year with Bloomberg's Emily Chang on the circuit. And you talked about AI. and you had a level of skepticism about where AI really is today across drug discovery, its utility in your field. I know it's not been that many weeks or months, but have you changed your mind? Do you still hold that position on the limits of AI in your field right now? Look, I think AI is an incredible tool. It's an amazing technology that allows scientists now to accelerate the kinds of work that we do. That being said, it doesn't replace scientists.

19:16We still need innovators. We still need creative people. We still need the new ideas that come out of left field. And we don't see that with AI. We see it being a great way to accelerate our ideas and make it possible to do things faster. And I think it's a great partnership.

19:32Ed Ludlow:Jennifer, bear with me if you would, but we have some headlines that are just crossing that right now Scribe is indicated to open at about$29 a share. The IPO priced at 15. So interesting because this was a difficult environment for biotech IPOs. We're also learning that the allocation, about 75 % of the shares to just 10 investors reflect on that. I mean, this must mean a lot to you, but clearly, you know, investors are very receptive to this. I think our investors really get this technology. They understand what's different about what Scribe is doing. They understand the quality of this team, its leadership and its commitment to real science.

20:14And that's what we're seeing, I think, reflected in the marketplace.

20:19Ed Ludlow:Scribe Therapeutics co-founder Jennifer Doudna, thank you very much for your time here on Bloomberg Tech. A story I just want to bring you real quick in the markets. BlackRock began marketing$12.3 billion of high-grade bonds to fund a meta data center project, testing investor appetite. This is concerns grow about excessive AI infrastructure spending, a source told Bloomberg. The bonds are being offered by a superpilot investor holding company tied to BlackRock and JP Morgan Chase and Morgan Stanley are running the offering, which is expected to price next week.

20:59Ed Ludlow:It's time for Talking Tech. First up, the EU escalated a probe against TikTok, accusing it of failing to protect the safety and privacy of teen users. The commission said TikTok's custom accounts for users under 18 can be easily found and viewed by other people online, which goes against the block's content moderation rulebook. Plus, SoftBank is considering an acquisition of Gravis Robotics in an effort to target the AI technologies underpinning robotics, according to sources. A deal could ultimately value Gravis at more than$500 million. And SAP reported stronger than expected cloud growth as more customers adopt AI-powered enterprise software.

21:42Ed Ludlow:Bloomberg spoke with CEO Christian Klein earlier about that, but also how AI tokens are now managed like any other business expense. In the R &D cost, you see a higher token consumption as we are using AI to code additional features, but especially now additional agents. But vice versa, you also see a huge productivity increase of 30%. Obviously, we are also managing tokens as part of our cost budget. You have a headcount budget, you have a party budget, and you have tokens. So our managers in R &D, in the go-to-market space, they have one budget, and they have to manage that also according to the productivity assumptions we reflected in the budget.

22:24Ed Ludlow:After two postponements, all eyes are on SpaceX's Starship test flight today. The mission includes upgraded Starlink satellites that will intentionally burn up during re-entry. The launch comes as SpaceX makes a major strategic bet on Starship. Bloomberg's learned the company is already turning away some potential Falcon 9 customers beyond 2028 as it shifts resources to its next generation rocket. That's all according to sources. Bloomberg Sana Pashanka broke the story and joins us now. Really interesting to work with you on this one. There's a lot of detail in there, right? Tell us about what we've learned SpaceX's attitude is to those satellite companies coming to them wanting either a dedicated ride on Falcon 9 or a rideshare ride.

23:12Ed Ludlow:What do we know? So what we know and what we've been hearing from sources and customers is essentially that SpaceX is fully booked through 2028 and they're turning away customers for dedicated Falcon 9 launches past that time point. So a dedicated launch is when a satellite company will buy the entire rocket and launch multiple of their satellites to orbit. And they're also turning away customers for their ride share missions, which is when multiple satellite operators can all put one or two satellites and hitch a ride to orbit to test satellites or if they only need a couple to get to space. And yeah, this is a really big deal for a long time.

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23:55Falcon 9 has commanded a near monopoly on the launch industry. It launches more than any other rocket in the world. So it's a pretty big deal that they're halting these reservations for now.

24:09Ed Ludlow:Sandra, the background point, not just in our reporting, but tonight as well with the test flight, is Starship matters. Very quickly, explain why Starship matters so much. Starship matters because it's key to Musk's ambitions for SpaceX, which are to build data centers in space. It's key to expanding the Starlink communications network, and it also will be the vehicle that is intended to land humans on the moon and Mars. Bloomberg, Sana Pashankar, really top reporting. Thank you very much.

24:47Ed Ludlow:Hey, guys, welcome back to Bloomberg Tech. It's been a jittery week, at least through the lens of technology markets. The Nasdaq 100 on a five day basis or over the course of the trading week. It's down about eight tens of one percent. But it's actually on track for two straight weeks of declines, something that hasn't happened since the end of March. And the index itself at its lowest level since the first week of May. A lot of that's the earnings story. There has been a lot in the world of AI about security incidents, about the debate on closed versus open and a lot of industry moves as well.

25:23Ed Ludlow:Well, CapEx in AI infrastructure has been a dominant theme, but it really is on the AI and software side where we focus. Major tech leaders took to social media to tout the benefits of open weight AI models in a letter signed by NVIDIA, Meta, Microsoft, Andreessen Horowitz and many others. This comes as Moonshot's Kimmy K3 has been shaking the AI industry just this week, spurring discourse on China potentially using U.S. technology to get ahead in the AI race. Michelle Guida, CEO of the Crack Institute for Tech Diplomacy at Purdue and also a former assistant secretary of state for Global Public Affairs under the first Trump administration, writes the U.S.

26:05Ed Ludlow:won't be able to win the AI race simply by limiting China's technology and joins us now. And frankly, that's where the debate is. You know, you would have seen the headlines this morning and the open letter essentially on open weight. The timing of that, there must be a reason for it. Well, what I think you're actually seeing, Ed, is a really good example of Silicon Valley and Washington, D.C. talking past each other. because if you look at that letter, the real debate isn't about open weight models. It's about Chinese open weight models, which unfortunately are the most available, most price effective option that's on the table right now, and especially for a lot of new businesses and startups that are trying to build their AI stacks.

26:51And so the real debate is on Chinese open weight models. And the problem there is we know that presents national security risk. We know it presents corporate risk, given all that we know about Chinese technology being untrustworthy. It's why we've banned Huawei. It's why we banned and then had to restructure TikTok. It's why there's legislation moving through the House right now about banning connected vehicles that are coming from China. And so there's a pattern here. And I think the focus on what do we ban versus what do we keep open is actually a misplaced focus by both the private sector and the U.S.

27:24government. the focus should be on how do we turbocharge America's open weight ecosystem so we have a world-class, robust, really price-effective offering for the rest of the world so we can diffuse American AI as fast as possible. And not only overseas, but here at home, where businesses are trying to drive.

27:42Ed Ludlow:On the here at home bit, I've read the open letter as many times as I could before we came to air. And I'm thinking, what is the concern? What catalyzed than writing it and putting it out. One take is the concern that Washington just over-regulates open source models, right, in a way that is detrimental to American interests. Where do you sort of sit on that debate? Yeah, well, I think it's because open weight models, cheaper open weight models have become really core to a lot of how businesses are developing their AI stacks. As you mentioned earlier, we just saw a big tech wipe out$890 billion because AI is really expensive.

28:24Everybody's looking to see if we can keep up with this spending bubble. And so the cheaper, good enough versions are really important for a private sector to be building their AI stacks. The problem is it comes from an adversary. And there is no really robust U.S. trusted alternative to the Chinese open weight models that we're seeing. And then the Kimi 3 launch this week catalyzed our awareness of that. And so the debate now is not really just open weight. It's Chinese open weight. And can we get an American alternative out there fast?

28:54Ed Ludlow:So NVIDIA CEO Jensen Wong did sort of an extended interview with Axios and basically said, you know, the top lines are that the Chinese models are excellent and that the open source models that are excellent, too, should be used. And so, you know, based on your line of argument that the risk is too great if the open model comes from an economic adversary, it comes down to how influential is Jensen Wang with this administration? Well, I actually think it comes down to how fast can we turbocharge an American open-weight ecosystem. Look, all the things that he's and other Silicon Valley leaders are saying make sense if you're looking at this purely through an innovation and a commercial lens.

29:38It makes a world of sense. If you then factor in the communist adversary lens, the risk calculus looks a whole lot different. And that's why these technologies are different. Look, we just spent the better part of a decade with businesses thinking about how they decouple and they de-risk from China because of the supply chain risk, the financial risk, the corporate risk, the national security risk. And now we're talking about entrenching Chinese technology into the very foundation of our American company's AI stacks. like that makes no sense and so how do we focus instead on getting trusted american ai cheap effective price effective uh ai into the hands of american companies and as much of the world as possible that's where the focus needs to go let's go back to the beginning you

30:25Ed Ludlow:know your argument through the lens of policy research reflecting on your time in government is that at the end of the day america won't win the ai race by restricting china so it you indicate that America needs to be proactive in its own approach, get its own house in order. How far does today's action go? What else needs to be done? Yeah, I think, look, the president has this great group on his PCAST, this presidential advisory board with a bunch of technology leaders. I think they should get in a room as quickly as possible and figure out how they go on offense really quickly with American open weight AI.

31:03And by the way, get all of our allies on board, because even if we ban and limit the use of Chinese technology, Chinese AI models here, if we're using AI models from America here, but the rest of the world is running on a Chinese AI stack, it's still a problem for us. And so I think they can rally around that. And look, we have a lot of lessons. When I was at the State Department, Huawei was a threat across the world. And there's a lot of lessons to be learned there. And a big lesson is that we're not going to win on principle. we're going to win on price. So how do we get much more cost effective, trusted American AI open weight models out into the world now?

31:41Ed Ludlow:We're showing a post from Mr. or Director Kratzios from a couple of days ago. We covered that story, the accusation that Kimi K3 was distilled from an anthropic model and used illegally NVIDIA Blackwell systems. We've been over that. But just pointing that out that Mr. Kratzios is also the co-chair of PCAST along with David Sachs Jensen's on PCAST for example. Michelle Guida, CEO of the Crack Institute for Tech Diplomacy at Purdue back on Bloomberg Tech. Thank you very much. So coming up the AI race also shifts to speed. AMD and Cerebris unveil a new partnership and Cerebris CEO Andrew Feldman joins us next.

32:18Ed Ludlow:Fast inference. This is Bloomberg Tech.

32:33Ed Ludlow:Shares of Cerebra Systems are down about 10 % right now. They had jumped yesterday on some news that AMD is teaming up with Cerebra Systems on a new server designed to slash response times, taking direct aim at NVIDIA. Joining us to explain the deal, the technology, Andrew Feldman, co-founder and CEO of Cerebra Systems. So this is how it's going to work. You basically have a Helios server and a Cerebris server in combination. How is that going to work, and what is the sort of split on the workload? Sure. Good to be back, Ed. Thanks for having me. The way to think about it is that the inference problem is comprised of two parts.

33:20We call the first part processing the prompt, and we call the second part generating the answer. and those two parts of the problem have very different computational requirements and that opens the door to address them with two different machines the processing of the the prompt the the analyzing the query that part is a problem that can be parallelized and for that type of work gpus are are very very good and helios will be the best um the second part of the work which is generating the answer at extraordinary speeds cerebris is the best in the world bar none and so by bringing these two solutions together so that the helios processes the prompt cerebris generates the answer we create a a single inference flow that is the fastest in the world and has this extraordinary throughput

34:25Ed Ludlow:like um you know andrew i'm not trying to um i'm not trying to to make a scandal or a negative out of it but like for you like how does the sales channel work right so amd has like this pipeline of projects and those uh that infrastructure is like okay we're going to use helios systems but now they can also get the cerebrus uh server alongside it how have you guys agreed to split the revenues? How have you guys agreed to do this in a way that is economically equitable? You know, it's a really interesting deal. Sure. I think speed makes markets bigger, right? It doesn't make markets smaller. This isn't about carving up something that's of fixed size, right?

35:08Fast inference is productive inference. And where AI is productive, people are willing to spend more and more and more. And so the first application of this solution will be in the Cerebrus cloud, and that will be later this year. And shortly thereafter, it will be available more generally. I think we have an enormous backlog. They have an enormous backlog. I think we have customers around the world who are demanding fast inference at extraordinary scale. And the solution we're building is head and shoulders above anything else.

35:49Ed Ludlow:I find the technology approach really interesting. The parallel example is NVIDIA and Grok with a Q and Grok 3 LPX. And in that case, it's integration of the Grok system into the same server design. You didn't take that approach. Did you talk about that? What were the options on the table? Well, we don't quite know what NVIDIA is doing. They haven't really delivered it to market yet, and so we are interested to see how that works out. What we were able to do, because we use open standards-based technology for our I.O., We were able to build a solution with AMD quickly and easily because we sort of support open standards.

36:45Remember, we've also done this with Tranium from AWS. And so we adopted the same approach that by being open, by being standards-based, right? Half the leading chip makers, AMD, AWS with Tranium, are now using our solution in a disaggregated approach for high-speed inference delivery. So I think the answer is by being open and by being standards-based, we can rapidly partner with other members of the ecosystem.

37:26Ed Ludlow:you've also been a busy guy we were talking off off air about how busy everything is you know you just did a very big ipo kind of interesting to to know like who approached who whose idea was this look i've known lisa for a long time she was ceo when when my last company was acquired by amd i've watched sort of her do uh extraordinary things with that company um the returns over her tenure as CEO are mind-boggling. And so we are in constant communication. We are close with her CTO, Mark Papermaster. These are people we've known for decades. And so we're in constant communication, talking about how we might collaborate, what we might do together.

38:12And this was an idea that emerged from those discussions and made perfect sense.

38:20Ed Ludlow:in the nvidia grok with a q example which i appreciate not your company's like completely separate but you know they the mechanism was an acqui higher um as you know prior to your ipo we reported at bloomberg that some of the fabulous chip names held talks or interest expressed interest um in in also acquiring cerebrus prior to its listing did you discuss any of those kind and mechanisms with Lisa about the merits of her making an equity investment or some of the structures that AMD has deployed in other of their arrangements? Sure. AMD has been an equity investor for quite some time. They were an investor in some of our mid and later stage rounds.

39:07And so we have been talking with them and engaged in discussions on how we might work together for a long time, as we are with many of the players. And that's the advantage of being open. That's the advantage of not being a walled garden. That's the advantage of not having a proprietary I.O. technology. But using standards-based, high-speed Ethernet technology, we can engage with AMD, we can engage with AWS, we could engage with Google, we can engage with. Anybody who builds a part that would integrate into an extraordinary solution.

39:47Ed Ludlow:Andrew, really quickly, I had a long conversation with SK Group Chair Chetewan very recently, and he said basically the difference between China's approach to AI and the US is China's going for the lowest dollar per token, whereas America is still in a place where it's focused on the highest quality tokens. From the non-HBM standpoint, would you kind of weigh in on that? Yeah, right. So we don't use HBM. And that's one of the real advantages we have. So we can generate tokens for less because we're not dependent on this sort of supply chain constrained part. Right. I think it's unclear whether the Chinese model makers are actually developing for less or piggybacking on technology that other people have invented.

40:38Right. I think that's an open question, what I don't have the answer to. But I know there's some very strongly held views that they are stealing, distilling. I'm not sure. But what I do know is I don't understand their cost to build these models. Right. Interesting. OpenAI is one of our larger customers. We do have an understanding of the amount of compute they need to build, and we have an understanding of the amount of compute that other frontier U.S. labs have. We don't really have an understanding of what the cost is. So the question is really are they making lower-cost AI because they're borrowing other people's technology, or do they have some really interesting inventions that allow them to make AI for less?

41:24That's an open question and one that relates to your previous segment and what we should do about that if it is the case.

41:31Ed Ludlow:And very, very quickly, you've seen the letter this morning, leaders in U.S. technology emphasizing America's need to focus on open weight. Do you have a viewpoint on that? Look, I think right now the market's been made by open AI with a fast follow. by Anthropic. And they have invested an enormous amount of money, a mind-boggling amount of money, and they have made this market. And I think the followers, both from China and others, are trying to capture this with a fast-follow strategy. And I think it's unclear to me what the right approach is. I think, obviously, we want lower-cost AI. What we can control at Cerebris is by building, like we're doing with AMD, solutions that deliver more tokens per unit power, that deliver more tokens per dollar, that deliver those tokens faster so they're more productive.

42:33So you can pay more. The problem isn't that tokens are expensive. The problem is that it's hard to measure how much productivity you're getting from tokens. And what we know is that when you make things faster, they drive up productivity. And so these are the dimensions we can work on, Ed, and we're diligently working on them every day.

42:54Ed Ludlow:Andrew Feldman, Terebra Systems, co-founder and CEO. Thank you very much. With AI stocks soaring this year, Viking Global Investors told clients that its conservative position on the sector was a, quote, missed opportunity. The firm's flagship hedge fund gained just 2.6 % in the first half of the year, trailing peers with greater AI exposure like KOTU. And yet the firm doesn't plan to change course. Bloomberg's Hemipalma broke the story. So they're sticking to their guns, but the performance is trailing their peers. Yes, a really interesting stance from Viking Global. This is a hedge fund that manages$56 billion.

43:29and they're taking a divergent view from what we're seeing from many of their peers that are really jumping on this AI beta market. And meanwhile, KOTU really a lot more cautious, not partaking in a lot of these stocks. And we're seeing this in their performance with their hedge fund up about 7.5 in the second quarter, but still only up 2.6 for the full year so far. And that's a great degree less than many of their competitors.

43:58Ed Ludlow:So if they're not budging and they acknowledge kind of the performance and a missed opportunity, is it that they see some opportunity in their current positioning that's going to change their fortunes? So they're very concerned about the risk that they see in the markets. So they're concerned that we could see potentially a correction, some sort of sudden shock that curbs buying of these stocks that are highly popular. They're worried about the valuations that they're seeing. So they do partake in some AI investments. They are a buyer of Samsung, which has worked out really well for them. But a lot of their portfolio is in other things like consumer, financials, industrials.

44:36And some of those stocks, some of those trades really aren't working as well as they would hope. Some of them, the firm says to investors, is potentially being unfairly considered an AI loser.

44:50Ed Ludlow:Very quick, Hema. Historically good performance of Viking or bad performance? You know, historically strong performance. And because of their cautious tone a couple years ago in 2020 and 2021, that saved them from a lot of the troubles we saw amongst their peers in 2022 when we saw that stock market crash when it came to tech stocks and private valuations. And now it saved them then. Investors may be hoping if there's a correction in the future, it'll save them today. Bloomberg's Hemmer Palmer with a must read. Thank you very much. That does it for this edition of Bloomberg Tech. What a week. more tech earnings coming up next week.

45:24Ed Ludlow:This is what it looks like. Recap on the pod. I really recommend some of the conversations throughout today's show. This is Bloomberg Tech.

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From the publisher

Bloomberg’s Ed Ludlow breaks down an open letter signed by Big Tech's biggest names, making the case for open-weight AI. The tech CEOs argue that open-weight models are key to innovation, competition, and security. Plus, Intel is showing signs of an AI-driven comeback, forecasting stronger sales as its data center business accelerates; and Cerebras CEO Andrew Feldman joins after announcing a partnership with AMD to challenge Nvidia, promising some of the fastest AI systems on the market.

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