Meta to Spend Billions on AMD Gear, AI Scare Trade Continues

Summary

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Bloomberg Tech — “Meta to Spend Billions on AMD Gear, AI Scare Trade Continues”

Date: February 24, 2026
Hosts: Caroline Hyde (New York), Ed Ludlow (San Francisco)
Guests/Contributors: Riley Griffin, Ian King, Hillary Frisch, Mandeep Singh, Brody Ford, Michael McDermott, Ryan Pope, Matt Hart

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Episode Overview

This episode centers on Meta’s massive, multi-billion dollar deal to buy AMD chips and data center hardware, marking a new surge in the AI infrastructure arms race. It also dissects the resulting market turbulence, the challenges and opportunities facing software vendors amid rapid AI disruption, and features interviews with key industry insiders and startup founders trying to compete with the tech giants. Additional segments touch on pending major media mergers, the regulatory and business implications of prediction markets, and a look ahead to President Trump’s State of the Union, particularly regarding energy costs for AI.

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Key Discussion Points & Insights

1. Meta’s Multibillion-Dollar AMD Deal: Scope and Strategy

[02:59–09:49]

• Deal Details:
  • Meta has agreed to purchase AMD chips and data center gear in a deal worth tens of billions—6 GW of compute capacity over time.
  • The contract includes share warrants for Meta, similar to AMD’s structure with OpenAI, involving operational and financial milestones.

  “It's a real endorsement…They're playing catch-up with Nvidia…This is a real strong affirmation and it also includes share warrants…”
  — Riley Griffin, [03:36]

• Motivation & Market Context:
  • Meta is aggressively “front-loading” compute capacity to fuel its AI ambitions, targeting hundreds of gigawatts as it pursues artificial superintelligence.
  • Spending is projected at $135 billion in CapEx this year, much of which focuses on chips for both AI objectives and Meta’s core social products.

  “Mark Zuckerberg last month announced MetaCompute with ambitions to get hundreds of gigawatts to fuel its data centers and ultimately reach that super intelligence goal ... spending won’t stop.”
  — Caroline Hyde, [03:59]

• Diversification & Competitive Dynamics:
  • Meta diversifies its hardware bets: custom chips, Nvidia and AMD hardware, each for different AI workloads and applications.
  • The move doesn't signal immediate anxiety for Nvidia's dominance; demand is so high that “all boats are floating.”
  • AMD’s inclusion signals tighter relationships through equity-sharing, validating AMD’s growing presence in the market, though it still trails Nvidia in revenue and installed base.

  “Ultimately, when the market slows down ... then we'll see the market share shift because then it'll really matter.”
  — Riley Griffin, [07:46]

  • Regulatory approvals and energy delivery bottlenecks are gating factors; specific chip deployments remain to be determined.

2. AI Disrupts Legacy Software Markets

[10:17–16:29]

• Market Impact:
  • IBM shares plunge after Anthropic’s “Claude” AI model showcases ability to modernize the COBOL programming language, challenging IBM’s core infrastructure.

  “You've got to feel powerful if you're Anthropic right now, right? ... Markets are really jumpy. The potential that Claude or another AI tool can disrupt the leaders in a given software category is really frightening investors right now.”
  — Brody Ford, [11:02]

• AI’s Dual Role:
  • AI can both disrupt and enhance established platforms. Cloud and SaaS companies must urgently show that AI is additive, not just offsetting declines.

  “The idea that software vendors lose the kind of pricing leverage they've enjoyed for so long because of that potential disruption—it's really something that markets are struggling to grapple with right now…”
  — Brody Ford, [12:04]

• How Companies Defend Against AI-Driven Panic:
  • Companies must demonstrate real adoption and value-add from AI, not just claim association.

  “What the vendors really have to do is show that AI is additive to the business, to beat and raise and show that AI isn't just offsetting declines in the core business, but it's actually adding ...”
  — Hillary Frisch, [14:55]

3. Research, Market Reactions, and AI’s Real Disruption Potential

[16:29–18:46]

• Market Jitters:
  • Reports (e.g., from Citrine, Harvard) amplify risk concerns but also point to new outperformance from AI-infused financial analysis.
  • AI’s impact is uneven—while some subsectors are defensible (security, data infrastructure), others (application software) face existential threats.

  “AI represents a risk, and it also represents an opportunity for many of the incumbent vendors ... there are reasons why a lot of subsectors should be relatively more defensible...”
  — Hillary Frisch, [17:34]

• Security & Data Platforms as Defensible Moats:
  • Security vendors integrate AI for vulnerability scanning but retain an edge due to physical enforcement—and AI itself increases attack surfaces.
  • Next-gen data platforms (Snowflake, MongoDB, Databricks) support new AI applications, automate complexity amid the explosion of data.

4. AI Hardware: The Race Beyond Nvidia

[27:37–30:09, 33:26–39:13]

• Meta’s Leverage and AMD’s Play:
  • Meta’s deal structure with AMD gives it leverage over Nvidia, potentially reducing chip costs as a percentage of CapEx and balancing future supply.
  • Co-engineering and focus on inference (MI 450) signal AMD’s intent to differentiate via custom solutions for Meta’s AI workloads.

  “This could potentially double, you know, every year in terms of just by adding one customer at the scale that they plan to buy the chips from AMD.”
  — Mandeep Singh, [28:02]

• Startup Competition:
  • Matt X raises $500M to build hybrid (HBM+SRAM) AI chips, targeting ultra-high throughput (flops per mm²) and low latency for LLM workloads.
  • Their approach breaks strict compatibility requirements to maximize performance for AI tasks—a “blank slate” design.

  “If you want to absolutely nail the LM workload, you have to be willing to break compatibility with previous chips.”
  — Ryan Pope, [37:15]

5. AI’s Verticalization: Domain-Specific Solutions

[39:39–44:37]

• Basis (Accounting AI) Story:
  • Basis distinguishes itself from general-purpose tools (like Anthropic’s cowork agent) by specializing in accounting: full business tax return automation, audit-ready accuracy, user experience tuned for experts.

  “You want domain specific capabilities ... we announced today the first example of a long running agent completing an entire business tax return workbook. That's something that you can't really do in any other AI tool.”
  — Matt Hart, [39:39]

  • AI is positioned as a co-pilot rather than a job destroyer: it empowers accountants to accomplish more, tackling accounting tasks that were previously infeasible due to resource limits.

6. Macro Context: Power, Regulation, and Prediction Markets

[45:22–51:13]

• US Policy Response:
  • Anticipation around President Trump’s State of the Union speech: expected focus on tech giants’ energy consumption, with new commitments from big tech to share higher electricity costs of data centers.

  “President Trump is set to announce a negotiated commitment from big tech companies to pay more when it comes to electricity costs related to AI data centers in a bid to remove some of that burden from U.S. consumers.”
  — Caroline Hyde, [45:23]

• Prediction Markets:
  • Segment explores the proliferation and regulation debate around online prediction markets (Kalshi, Polymarket), their uses in politics and events, and their surprising predictive accuracy—especially with high liquidity.

  “Prediction markets are more accurate than polling and certainly more accurate than you or me or any individual trying to prognosticate about elections.”
  — Brody Ford, [47:55]

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Notable Quotes & Memorable Moments

• On AI Hype & Software Panic:

  “Investors shoot first and ask questions at some very distant date. So we're seeing a pretty dramatic compression in terminal multiples of many of the names.”
  — Hillary Frisch, [13:58]

• On the Scale of Meta’s Bet:

  “They're going to try to get as much as they can, gobble it up while there's still availability ... could be applied not just for AI purposes, but for that core social media business which still drives more than 98% of their revenue.”
  — Caroline Hyde, [08:34]

• On Hardware Demand:

  “Demand for LLM Compute is just insatiable. All of the Frontier labs are looking at where this space is going and they're all concerned: I'm going to run out of silicon.”
  — Ryan Pope, [33:54]

• On AI as a Copilot:

  “From our perspective, this is going to allow firms and the accountants at those firms to take on even more work and get more things done, get more things done in the same way that software engineering has been able to take off over the course of the last 12 months.”
  — Matt Hart, [44:37]

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Timestamps for Key Segments

| Timestamp | Topic / Segment | |---------------|--------------------------------------------------------------| | 02:06–09:49 | Meta’s AMD deal: context, mechanics, market implications | | 10:17–16:29 | AI-driven disruption in legacy software & SaaS, Anthropic’s impact | | 16:29–18:46 | Research on AI risk, ‘AI panic’ vs. real change | | 23:03–23:56 | News headlines: Anthropic, OpenAI, market moves | | 24:28–26:18 | Paramount’s increased bid for Warner Brothers | | 27:37–30:09 | Analyst insight: AMD vs Nvidia, Meta’s CapEx, deal dynamics | | 33:26–39:13 | Startup insight: Matt X’s $500M round and chip strategy | | 39:39–44:37 | Domain AI: Basis transforms business tax filing | | 45:22–47:49 | State of the Union preview: Tech energy policy | | 47:11–51:13 | Prediction markets: regulation, accuracy, societal impact |

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Tone & Narrative

The episode is fast-paced and energetic, toggling between bullish, anxious, and occasionally irreverent as the hosts parse market mayhem and hype cycles. The language is sharp, often skeptical, and frequently lightened by in-jokes (“Matter is traded flat as a pancake”), with a focus on giving investors and tech watchers a strategic lens on both headline-grabbing deals and underlying systemic shifts.

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Summary

This Bloomberg Tech episode skillfully unpacks the dual boom of AI infrastructure—exemplified by Meta’s huge AMD hardware deal—and the resulting volatility in software markets as AI agents threaten established players, create new platforms, and drive fierce competition for chip dominance. By mixing high-level analysis, timely news scoops, and direct input from both established analysts and emerging founders, the show offers a comprehensive, nuanced, and vivid snapshot of the ever-evolving technology landscape in early 2026.

Transcript

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[Caroline Hyde]

Bloomberg Audio Studios Podcasts Radio News. Bloomberg Tech is alive from coast to coast With Caroline Hyde in New York and Ed Ludlow in San Francisco,

[Ed Ludlow]

this is Bloomberg Tech. Coming up, Matter agrees to buy AMD chips and datacenter gear in a deal worth tens of billions of dollars plus

[Ed Ludlow (Co-host or secondary host)]

a whiplash in markets. It erupts again as investors navigate the disruptive power of agentic tools and unve

[Ed Ludlow]

bianc traffic and Warner Brothers Discovery is considering a new takeover bid from Paramount Skydance, with its board set to review the proposal and respond.

[Ed Ludlow (Co-host or secondary host)]

But first we check in on these markets that bounce back after yesterday's sell off. Again, anthropic front and center. The latest tools that have been battering software are now adding some fuel to them. We'll get into that story a little bit later, but at the moment, NASDAQ 100 up by 910 of a percent reprieve. Remember also consumer confidence from a macro perspective coming in better than anticipated. Look at Bitcoin though, just nothing better than anticipated with this particular asset. We're currently at 63,993. The pressure still there and but what have you got?

[Ed Ludlow]

Let's get to our top story. Shares of AMD pushing higher. Matter Flat had been slightly softer. At one point in the session AMD was up about 9% and on track for its best day since November. This is a 6 gigawatt deal. Matters agreed to buy AMD chips and datacenter supplies in a deal worth double digit billions per gigawatt. This is the social media giant looks to prioritize its its ambitions here to break it down, Bloomberg's in King on the chip side, Riley Griffin on the metal side around the table. Ian, I'm going to start with you. The basics of the deal. Six gigawatts over time, AMD accelerators but also other gear. It's a big deal for them.

[Riley Griffin]

Yeah, it's a real endorsement from one of the biggest buyers of this kind of equipment. Obviously they're playing catch up with Nvidia who had their own deal with Matter last week. So this is a real strong affirmation and it also includes a share warrants as well that are going to matter.

[Ed Ludlow (Co-host or secondary host)]

Riley, this is all about Meta Compute. Talk us through just how large the scale is for demand for this sort of infrastructure.

[Caroline Hyde]

Right now it's insatiable demand from Metta. Mark Zuckerberg last month announced medicompute with ambitions to get hundreds of gigawatts to fuel its data centers and ultimately reach that super intelligence goal where I can outpace human intelligence. And this is just the latest in a frenzy of deals. Again, we're anticipating 135 billion in CapEx this year, but now we know the spending won't stop.

[Ed Ludlow]

The warrants part is very interesting. It's very similar to what AMD did with Open Air. There are operational and financial milestones in both directions in order for Matter to potentially become a very big shareholder of amd. Could you explain that?

[Riley Griffin]

Yeah, I mean the way, the way to look at it, Lisa sue said, look, this basically ties us closer to Matter. They get these shares if we're in a very good position. I mean the last tranche I believe is about $600 there. You know, yesterday they closed at less than 200. So we've got a room to go before that becomes a reality. But you know, her point was that this kind of locks us together and tightens our relationship.

[Ed Ludlow]

It was really interesting to read through the materials in our reporting, Riley. Like AMD has played this card before, the emphasis is on inference. So MI 450 generation of accelerator, the engineering teams will work together. But the inference part, like is there anything unique about this different to what Matter is doing with Nvidia? Because we had a very similar deal very recently.

[Caroline Hyde]

It's a really good question. Not only is it similar to what Matter is doing with Nvidia, but Metta also has its own internal pipeline of custom chips that it's building for AI purposes. What we heard yesterday is that they see see different applications, different workloads here being supported by all three of those verticals. And so they're trying to diversify as they pursue this massive scale in terms of compute.

[Ed Ludlow (Co-host or secondary host)]

And take us back to Nvidia because we've got their earnings coming up tomorrow. And how much does this show that there is anxiety that companies are diversifying, looking at amd, looking their own in house chips? Or actually does it still not are concerned Nvidia is still dominant?

[Riley Griffin]

Yeah, I mean at this point all we can do is say look at the numbers and the numbers. Assuming Nvidia comes in and executes on what Wall street thinks it's going to do, the numbers say there's no anxiety here, all boats are floating, everybody's benefiting from the same massive spending in equal measure. I guess what would change that would be if Nvidia does not hit those targets, does not exceed those targets, I think would change the conversation considerably.

[Ed Ludlow (Co-host or secondary host)]

And Riley, the conversation is nuanced when it comes to capital expenditure. Many would say yes, a lot of it is about the chips, it is about the data centers, but it's also about the power. Can we understand really how much Matter is having to focus in on where they can spend on GPUs or their own homegrown chips and where they do it globally as well.

[Caroline Hyde]

So we asked yesterday where they thought they would deploy these chips and they couldn't specify which data centers which we know that some of their biggest projects are targeting 5 gigawatts.

[Ed Ludlow (Co-host or secondary host)]

Right.

[Caroline Hyde]

But they need to get certain regulatory approvals and they need energy companies to be able to deliver there on the ground. So as for the merging of the energy and the compute here, time will tell as we home in on where those chips will actually go.

[Ed Ludlow]

It's probably time for a bit of a reality check in and I'm hoping that you'll provide it for us like in any given quarter right now. AMD is going to do $10 billion of revenue all told. Every, every single segment. Nvidia's data center business is at more than $50 billion a quarter. Yes, that includes networking, but they're now one in the same. Right. You can't have chips without the other. How do we know if this is evidence that MD is catching up?

[Riley Griffin]

I mean, again, you have to go back to the percentages, the growth percentages. And at the moment both of them would say, you know, this isn't about competition, this is about there's so much demand. A company like Matter, which makes its own chips, is buying from both of us that that would be the answer. But ultimately, when the market slows down, and you can be the judge of when that happens, then we'll see the market share shift because then it'll really matter.

[Ed Ludlow]

Matter is not a hyperscaler, but it operates its own data centers at hyperscale, if you know what I mean. I'm thinking back to when Mark Zuckerberg was sat next to the President $600 billion over the next few years. And then he's also talked about this idea that they might misspend $200 billion here or there, here or there. But that's no bad thing. He's front loading purchases. Just explain his thesis a bit.

[Caroline Hyde]

Yeah, his, his strategy is just that he's used the language of front loading capacity. They're going to try to get as much as they can, gobble it up while there's still availability. And this, he says, could be applied not just for AI purposes, but for that core social media business which still drives more than 98% of their revenue.

[Ed Ludlow (Co-host or secondary host)]

Right.

[Caroline Hyde]

So they see applications across the board and they're not worried about getting too much in the, in the interim.

[Ed Ludlow (Co-host or secondary host)]

And why does AMD have to keep giving its shares away?

[Riley Griffin]

Again, we asked Lisa about this and she said that at least this is Lisa Su, the CEO, and she said this is different than the open air ideal. The open air ideal is a slightly different arrangement. That is a company, obviously that is seeking liquidity. Matter clearly does not need liquidity. This is just a way of showing matters commitment to what they're doing. You've got to remember that, you know, AMD is only a couple of generations into being any type of presence at all in this market. So if a big buyer of this stuff comes along and says, oh, we like your gear, oh, guess what, we also like you as a company like your prospects, then that is somehow a bigger validation than just a straight purchase agreement. And that really was what they were pushing as an idea that look, this is how closely we are tied together

[Ed Ludlow (Co-host or secondary host)]

and affecting from the upside. Bloomberg's in King and Riley Griffin, thank you so much for joining us on that roundtable. Meanwhile, coming up, software earnings. They take center stage to what to expect as AI fears enter the picture. This is Bloomberg Tech.

[Bloomberg Host/Announcer]

Foreign.

[Ed Ludlow]

Shares of IBM had the worst day in more than 25 years Monday after Anthropic announced that its clawed code could help to modernize the dated coding language cobol. Largely run on IBM computers. This is Anthropic continues to unveil new AI tools for its cowork agent software across human resources, investment banking and design. Bloomberg's Freddie Ford joins us for the latest. COBOL was invented in 1959. There are 200 billion lines of cobalt coal to underpin financial systems banking payments around the world. And basically Anthropic said it would be really useful to use Claude to help maybe investigate looking to change that. And then one of the most storied technology companies in history had its worst day in 25 years. Take it from there.

[Brody Ford]

You've got to feel powerful if you're Anthropic right now, right? If you just the name of a product the company associated with that project Tanks. I mean IBM has been talking about using AI for COBOL modernization and it seems successfully offering that tool for a couple of years now. And yet markets are really jumpy, right? I mean the potential that CLAUDE or another AI tool can disrupt the leaders in a given software category is really frightening investors right now. And it's just, it's an incredibly jumpy market.

[Ed Ludlow (Co-host or secondary host)]

IBM senior VP Rob Thomas was pushing back against this writing in a blog and you quote him in your story that the value of IBM mainframe delivers has nothing to do with cobol. Is trying to talk about the platform more broadly. Brody but what you say is so brilliant how powerful Anthropic must feel also to the upside because look, they do a partnership with Intuit today and that fuels Intuit shares a little bit on the upside. So it can be make or break in either direction.

[Brody Ford]

It feels into it a bit on the upside, but the company's still down what, 40% this year? I don't know if it's quite that dramatic, but it's a scary time to be an application software vendor, right? I mean the most extreme idea that companies are just going to vibe code their own solutions, I don't think anybody really believes that. But the idea that software vendors lose the kind of pricing leverage they've enjoyed for so long because of that potential disruption. It's really something that markets are struggling to grapple with right now and it's going to be a really interesting earnings cycle.

[Ed Ludlow]

It's basically pitching itself now as a platform. Right. So historically, Claude is focused on coding and making engineering more efficient. And like if you're an Intuit customer, you already use all of Intuit's platforms and data. You just have an agent inside of it. If you're a small business or, or a consumer. It's the same with DocuSign. We're seeing all these names move. How is it making these companies better, Brody, you cover this beat inside and out.

[Brody Ford]

Well, it's forcing them to really try to drive adoption and use among customers. Like, we all know that a lot of the hype was a bit premature in terms of how mature these tools were actually and how ready they were to be used in the enterprise. And it's really holding toes to the fire that, hey, it's time to make sure your customers are actually using your AI tools or else the market's going to sell your stock and act like you are going to go poof in a couple of years.

[Ed Ludlow (Co-host or secondary host)]

Bloomberg's Brody Ford. Always a perfect way with words. We thank you. Let's get more on the wider impact on tech and software with Cambridge Investments. Senior Research Analyst for Software for IT Services, Hillary Frisch. Hillary, the perfect person. I go back to in many ways, what Brady was just saying. We're questioning, questioning just how good the tools are. Have we seen a sudden shift in how brilliant these AI agents are in the last few months?

[Hillary Frisch]

We have. We're seeing the sell off in software and particularly SaaS, because so much is changing so rapidly and these tools are evolving tremendously. That said, there's probably a pretty big disparity between some of the capabilities of the tools and, and what's happening, and likely to happen probably even intermediate term in the marketplace, particularly the enterprise marketplace. But investors shoot first and ask questions at some very distant date. So we're seeing a pretty dramatic compression in terminal multiples of many of the names.

[Ed Ludlow (Co-host or secondary host)]

At what point are they going to become discerning? Because at the moment it's very hard for a CEO for Arvind Krishna over IBM for whether it's ServiceNow Bill McDermott to disprove. That's right. That they're not going to be impacted.

[Hillary Frisch]

That's right.

[Ed Ludlow (Co-host or secondary host)]

So how do they prove a negative? How do you start to see people willing to catch a falling knife and be like, oh, these are platform Companies, they're not going to be disrupted or maybe they will be.

[Hillary Frisch]

Sure, sure. It's so hard to tell the near term reaction to any kind of event. It's been asymmetrically skewed to the downside. I think what the vendors really have to do is show that AI is additive to the business to beat and raise and show that AI isn't just offsetting declines in the core business, but it's actually adding to the business and that could really change the narrative. We actually saw that with the Snowflakes of the world two years ago with MongoDB last year into this year. But that's typically what's required for, for investors to realize it's not just a zero sum game.

[Ed Ludlow]

On the Bloomberg terminal. There are let's say a dozen reports of single name stocks that are moving because of the association with Anthropic who held an event this morning. You study the software sector, right? Very closely. Is there any evidence those, those names are moving because people genuinely believe there's a fundamental change to how they do business or is it just simply name association at this point?

[Hillary Frisch]

I think it has to do with the idea that if Anthropic sees the need to partner with these companies, Anthropic see is that they provide something that Anthropic doesn't and they understand these are incumbent vendors with installed customer bases and loyalty and processes and things like that. It doesn't mean there isn't future disintermediation, disintermediation risk, we all know that. But I think it's a signal to investors that these, these companies are viable and important to the ecosystem and investors have not been assuming that over the prior few weeks.

[Ed Ludlow]

Hillary There was a research report, a bearish research report from a little known outfit called Citrine that basically outlined various risks to different sectors from AI. One of the co authors joined Bloomberg Television. I just want to play you some of that conversation.

[Mandeep Singh]

I thought there was going to be a small reaction. It was definitely larger than we expected. But I think it's not that surprising when you take a step back and consider kind of where the markets are in the U.S. you know, the AI trade has been going on for three and a half years. It's been more or less a straight line up and essentially like everyone is max long today and so there really aren't many incremental buyers left.

[Michael McDermott]

And so it on the one hand,

[Mandeep Singh]

you know, spooks people when, when you do consider what is negative about this. But I think specifically the market right now is trying to digest this idea that AI has gotten a lot more powerful in the last six months.

[Ed Ludlow]

You know, in that he's kind of saying well this is kind of the function of the market of the last three years. But still poses the central question which is is AI rendering existing software obsolete or is it making it better? Just your reaction to that research report and the co authors thoughts there?

[Hillary Frisch]

Sure, I think it's both. I think I represents, represents a risk and it also represents an opportunity for many of the incumbent vendors. We could take SAS separately but we've been talking internally about what I call the great catch down to sas. Every other sector or every other part of software selling down to SaaS on disintermediation risks. But there are reasons why a lot of subsectors should be relatively more defensible and we could talk about those if you like.

[Ed Ludlow (Co-host or secondary host)]

Okay, well let's talk about what's been defensible because there's this drip feed of a doomerism, shall we say in these various reports and blog posts coming from the CEO of Anthropic himself to over at Citrini or we've also had Harvard coming out with their piece that we're seeing it being incredibly effective when it comes to financial analysis and portfolio decision making. The Harvard led study is talking about how trading, mutual fund trading decisions. 71% it predicted. Right. The model was trained over a five year window. But they're also talking about maybe the outperformance but is what it misses. So from your perspective, where's the outperformance going to come from? Some of the companies that can withstand this, that can show that they're, they're really effective while using the AI tools.

[Hillary Frisch]

Sure, sure. I think of security as an example of that. Anthropic introduced a vulnerability management tool. Not even management, just a scanner for vulnerabilities in code that's produced on the platform. And that's a build time phenomenon. Most security vendors are runtime but they bring a lot to bear that we could talk about from a technological perspective that it's going to be hard for an LLM or an agent to have. They have the physical infrastructure, they cover all the enforcement points. It's partly a physical phenomenon, not just a digital phenomenon per se. But on top of that, when you think about it, I don't know how entities and especially regulated entities can have the fox guarding the henhouse when it comes to security. And kind of the same existed in cloud as well because AI creates so many vulnerabilities, so many new vulnerabilities that we've never had that it's a major issue when you're looking to what's becoming the greatest attack surface to be the solution to the problem. Similarly, the data platform vendors are really the platforms for the next generation of AI applications. We're seeing them build on top of the snowflakes. The MongoDB is even potentially the oracles to some degree. Datadog, that's slightly different, but what customers are looking for is higher levels of automation to make their lives easier when there's a tsunami of data coming at them. These infrastructures and oftentimes are quite different. The data models are different from LLMs. The infrastructure on which they run are far more efficient than what LLMs do do and seem to be able to do. And so I believe the greatest source of automation is going to come from these incumbent vendors. I should have mentioned databricks, of course, in which Clearbridge has a private investment and so solving headaches for customers in the face of a ton of complexity is going to be of paramount importance.

[Ed Ludlow]

Hillary Fresh clearbridge Investments thank you very much. Now coming up on the program, Paramount is said to have raised its offer for Warner Brothers More on the drama to buy one of Hollywood's most storied brands. This next this is Bloomberg Tech.

[Bloomberg Host/Announcer]

How do you shift AI from being a flashy feature to a trusted partner in consumers everyday lives on the ground at CES Bloomberg Media Studios? Asked Michael McDermott, EVP of Samsung.

[Brody Ford]

Our 2026 vision is built around an AI companion. It understands you and responds intuitively. This intelligence works quietly in the background

[Riley Griffin]

across TVs, home appliances and mobile devices.

[Brody Ford]

By putting AI at the center of everything we do, we're simply improving everyday life for everyone everywhere.

[Caroline Hyde]

You need to make a huge presentation in an hour. Luckily, Adobe Acrobat Studio uses AI to take all your documents and generate a presentation with a single click, building slides faster than ever before. So if you need a last minute pitch deck, do that with Acrobat. Need to level up your presentation design? Do that with acrobat. You have 30 documents that need to be simplified into a proposal. Do that with Acrobat. Learn [e-mail] do that with Acrobat.

[Bloomberg Host/Announcer]

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[Ed Ludlow (Co-host or secondary host)]

time now for talking tech. And first up, Anthropic has accused Deepsea, Mini Max and Moonshot up to six, distilling its clawed models to bolster their own AI capabilities, adding to concerns in the US About Chinese firms improperly gaining an edge. Representatives for the three firms didn't respond to requests for comment. Sticking with Anthropic. Look, sources say the company will let some current and former employees sell their shares at a valuation of about $350 billion, the level reached during a recent fundraise. Anthropic has lined up 5 to 6 billion dollars from outside investors, though the amount and details have not yet been finalized. And Canada, well, it summoned OpenAI executives after it was revealed the company debated but ultimately didn't refer a chatbot user to the police. That person became the sole suspect in one of Canada's worst ever mass shootings. OpenAI banned the use of months before the attack, but said it found no credible or imminent threat.

[Ed Ludlow]

Ed okay, let's take a look at shares of Warner Brothers Discovery, Paramount and Netflix and get the latest. Paramount has raised its offer for Warner brothers from its $30 a share all cash proposal. That's according to Bloomberg reporting. Now Warner Brothers Discovery and its board is reviewing that revised proposal. Bloomberg's managing editor for media and entertainment leading the screen time team for sure. We actually don't have the specifics, I don't think yet of how improved this offer is, but it's on the desk of Warner Brothers Discovery, its leaders and its board. Take it from that.

[Brody Ford]

Yeah, I mean, you see both sides taking this more seriously and being quiet. I mean, there's been a kind of a progression with these talks where back when the first bidding war was happening, you had Warner Brothers reviewing offers from Comcast and Netflix and Paramount. It was very quiet, Right. People didn't say a lot because everyone thought they were in it. Then Warner Brothers picked Netflix and it got really loud. Paramount accusing Warner Brothers of doing things that weren't right. Netflix and Warner Brothers often firing back. And now it's gone quiet again, which to me is clearly a sign that the board is seriously reviewing the Paramount offer. If Paramount has increased it by a dollar to a share, which we assume they have, it seems hard to believe that they would outright reject it, as they have the recent ones. Which means that they would have to go to Netflix and sort of say, what do you got for me?

[Ed Ludlow (Co-host or secondary host)]

Well, exactly. We'll get a drip feed of what it is exactly that they've got. But if it is markedly better, do we expect Netflix to respond in kind?

[Brody Ford]

You know, it's a. It's a tough question to answer. Netflix has communicated to some of its shareholders. I've heard from people at Netflix that they feel they have the balance sheet to go up. Right. We're talking about a growing business with a really significant market cap, even if the stock's taken a little bit of a beating during these negotiations. So relative to Paramount and even relative to the Ellison family, Netflix should have the money to go there. It's a question of whether they want to. You know, their stock is down. I. I've lost track at this point. It's more than 30% since these negotiations started. And they may decide that there is a number that is too high for them. We just don't know what that threshold is.

[Ed Ludlow (Co-host or secondary host)]

It continues to evolve and we know that you'll always have the story, but mostly for sure. Thank you so much. And coming up, more on matter and AMD's multibillion dollar deal as the race to power AI intensifies. And AMD up 7% coming off of those previous highs.

[Ed Ludlow]

Yeah, and then met a flat as a pancake. Much more to come. It is half time. This is Bloomberg Tech. Welcome back to Bloomberg Tech. We're continuing to track the impact of AI on legacy software. Essentially lots of names. Actually moving to the upside, the story is anthropic and basically taking its CLAUDE agent and linking it in a platform for everything from hr, investment banking, documents. And that is pushing a lot of names higher. IBM is up 4%. But remember yesterday, Monday, it fell by the most since 2000 when it said that Claude could be used basically to improve archive change, update COBOL coding bases, a program that was invented in 1959. Otherwise, our top story is a deal between AMD and matter, 6 GW of capacity over the balance of the decade, largely focused in the first instance on AMD's latest accelerator and the server that it's based on MI450. But this is basically $60 billion of potential revenue for AMD over that time period. The stock up more than 7%. Matter is traded flat. But I guess that it's hard to gauge if this makes sense. Any difference in Meta at all given its existing spending commitments?

[Ed Ludlow (Co-host or secondary host)]

Car well, someone's been writing on just that. Bloomberg Intelligence senior analyst Mandeep Singh says that matters 6 gigawatt MD deal actually lowers chip spending as a share of capex and secures supply tailored to inference. He also writes that the stock link structure could give Matter added leverage against Nvidia. Mandeep Singh joins us now. Why does it need leverage against Nvidia? It struck a deal last week with them. Is this more like we've got other options?

[Mandeep Singh]

Yeah, and look, I mean, the fact that they are planning to use Nvidia CPUs, to me that was a sign that, you know, if you had to get the GPU capacity from Nvidia, you pretty much had to use everything they had to offer. With this deal, I think AMD sort of comes across as the more desperate partner in terms of, you know, giving Meta their stock warrants and making sure that, you know, they are at Meta, which is going to spend $135 billion. Out of that, half of that will be on chips, approximately. So think of it this way. They currently are about a 10 to 12 billion dollars run rate. This could potentially double, you know, every year in terms of just by adding one customer at the scale that, you know, they plan to buy the chips from amd.

[Ed Ludlow]

You know, the way that AMD puts it, right, single, double digit, sorry, billions of dollars per gigawatt. But the gigawatts need to get built, right? There are operational milestones. Every time I go and see AMD or we speak to Lisa sue, she puts a lot of emphasis on inference, you know, Mi 450 in particular, and what those systems can do in the inference phase. Do you in this deal see a point of differentiation for AMD if they do go after the inference piece?

[Mandeep Singh]

I do. And simply because all these companies are trying to emulate what Google has been doing with TPUs. And remember, TPU's are used for both training and inferencing, not just for Gemini, but also for Anthropic. So the fact that they have signed this deal and are willing to go from being a merchant silicon provider to a custom silicon provider for Meta, and Meta's workloads are more skewed towards video and, you know, the family of apps they have similar to Alphabet. To me this is a sign that's what Matter feels they can accomplish. You know with the AMD chips. Yes they will continue to use Nvidia for training but for inferencing Meta's workloads are different from, you know, any other provider when it comes to the chat bots or anything else that they're doing.

[Ed Ludlow]

You know AMD was at pains to point out they'll kind of co engineer the roadmaps of to future server design starting in my 450 and go beyond that. Mandeep Singh of Bloomberg Intelligence with the react. Thank you so much. Now coming up on the program, Rand Pope from Matt X joins us to discuss his chip startup's latest fundraise as it aims to take on Nvidia. That's coming up next. This is Bloomberg Tech.

[Caroline Hyde]

You need to make a huge presentation in an hour. Luckily, Adobe Acrobat Studio uses AI to take all your documents and generate a presentation with a single click, building slides faster than ever before. So if you need a last minute pitch deck, do that with Acrobat. Need to level up your presentation design? Do that with acrobat. You have 30 plus documents that need to be simplified into a proposal. Do that with Acrobat. Learn [e-mail] do that with Acrobat.

[Bloomberg Host/Announcer]

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[Ed Ludlow]

AI startup Matt X has raised more than $500 million to build hardware to compete with Nvidia. The chip company was founded by two alumni of Google's semiconductor business and its aim is to make a product specifically designed to run large language models. Co founder and CEO Ryan Pope joins us now. I think we should get into the specifics but my goodness, $500 million is quite a large Series B. What do you need that level of capital for and what is it to referring reflect?

[Michael McDermott]

Yeah so I mean I would say very happy to be here and thank you. One of the really what it reflects is on the one hand very strong confidence from from some of our lead investors in the product We've this is, this is from Jane street and situational awareness have have led our round very strong on Jane street sides. They're absolute technical experts. They understand the kind of product we're doing and then situational awareness the that's Leopold Ashen Brenner's fund. He wrote the book on AGI and he really understands where where this whole space is going, what we like, what we are looking to do with with this product and with this money. Firstly, I would say the demand for LLM Compute is just insatiable. All of the Frontier labs are looking at where this space is going and they're all concerned I'm going to run out of silicon. I won't be able to serve all the demand I've got. So our goal overall has been to make the highest throughput per square millimeter of silicon that any product.

[Ed Ludlow]

This is about computational density that's right. That's right. And so you guys are basically saying throughput in terms of flops per millimeter squared, like this is something you can own. What was the breakthrough, you know, what is it that you're so good at to achieve this?

[Michael McDermott]

Yeah, so there's really a combination of two things. If you look at the products in the market previously there's been the HBM based family, which is Nvidia, Google, Amazon, and then there's been the SRAM based family.

[Ed Ludlow]

And you are sram.

[Michael McDermott]

We are both actually uniquely. So it's kind of taking two good ideas and putting them together. It is possible to do both very high throughput as you get from hbm, but also very low latency as you get from SRAM and do that in the same product. What it gives you is actually a product that is better than any other product in the market at throughput. This is exactly the flops per square millimeter that you described, while also matching some of the best like the Cerebras and the Groq at latency.

[Ed Ludlow (Co-host or secondary host)]

Let's talk about how quickly people could start deploying this right now, because what your aim is to complete the final design this year. You hope to start manufacturing shipping even in 2027. Who do you need to partner with on that? How do you expect to be manufacturing here in the US or abroad?

[Michael McDermott]

Yeah, so I mean there's a few big parts of the supply chain and this is common for us as well as many other semiconductor firms in this space. Really you need logic wafers, memory wafers, which is hbm. And then, and then you need rack build outs. And so those are the big parts of our supply chain. TSMC is well recognized as the best provider of logic wafers. And then the memory, memory wafers. There's the big three, which are sk, Hynix, Samsung and Micron, and then there's a whole range of of providers across the rack and manufacturing side. One of the big things that if you want to manufacture in very large volumes, we hear about these, you know, multi gigawatt deals that are coming out the. These require, you know, billions of dollars of manufacturing and then actually setting up like hundreds of millions of dollars put into setting up supply chains in advance of delivering that. And so that's a big part of what we're doing, excited to be able to do.

[Ed Ludlow (Co-host or secondary host)]

Now you left Google in 2022 and the goal was creating a better chip from scratch. Right. But have you been impressed by the leaps that TPU has taken? It seems to have impressed the market. What is it that you felt wasn't at Google for you, that you now can build better?

[Michael McDermott]

Yeah. So I think what is really required is if you want to absolutely nail the LM workload, you have to be willing to break compatibility with with previous chips. And so one of the strong guarantees you see all of the existing players providing is you can take a program that was written on my previous generation chip or my generation of chips five years ago and it will run on my next generation chip. And so a lot of what that means is there are constraints on my chip has to support all of the previous number formats I supported, it has to support all of the different programming model, the way I communicate between cores on the chip. All of those have to be the same as each other. We felt that it would be necessary like if you really want to just absolutely nail this workload without regards for backwards compatibility or other workloads or anything like that, you need to something of a blank slate design is required. For us this means very large matrices, very low precision support and then in fact an ability to split your very large systolic array into small pieces.

[Ed Ludlow]

You name checked Grok I think with some admiration a second ago, I mean like when in video acquired Grok, Jensen Huang's view was that they were struggling to find their place in the world in the market. And for what it's worth, Sarah Brassi, you name checks as well filed confidentially for IPO yesterday. Why might you succeed where Grok had to go to Nvidia and I guess they're working on something, you know, and the public markets, you know are needed for capital going forward.

[Michael McDermott]

Yeah, so I would say this is like historically the market has been won by the HBM place based players. That's the Google, Amazon, Nvidia and not by Grok and Cerebras. SRAM only chips are very good for latency, but when you want to run very long context models, you run out of memory capacity. SRAM is too small. It's fast, but too small. Really the hybrid of doing weights in SRAM so you get the low latency as well as having the HBM for for very long context support is we believe that's what enables the low latency without all of the compromises that you would get otherwise.

[Ed Ludlow (Co-host or secondary host)]

Ryan Pope, thank you so much for joining us today. Matt X CEO look, we got to stick with funding news basis. A startup making tools for accounting has raised $100 million at an over $1 billion valuation. This of course as investors grow pretty wary of disruption from Agentic I here with us is Matt Hart, faces CEO. I go to the point, how is basis different from anthropic cowork plug in for an accounting business?

[Matt Hart]

Yeah, well first of all great to be here and thanks for having me. Caroline. Look we, we have an excellent relationship with OpenAI and with Anthropic and I think co work ChatGPT. The whole range of tools that they have are absolutely fantastic. I think though you can only sort of serve so many masters. And when it comes to domain specific work, specifically in our situation accounting, there's a need to build with that domain specificity in mind. I think it comes down to a couple of things. First of all you want domain specific capabilities. So for instance we announced today the first example of a long running agent completing an entire business tax return workbook. That's something that you can't really do in any other AI tool that exists out there. You need domain specific accuracy. So we are able to guarantee to the firms that we work with that the AI will meet the requisite level of accuracy for it to be used in a real manner and we can sort of guarantee that performance. You need domain specific user experience so that it's fluid and it works well for people who are experts in their field as they go about doing their work. You can't just have a chatbot or the variety of other sort of basic user experiences that you need. You need to build enterprise sort of grade features, collaboration, audit trails, auditability, et cetera, things of this nature. And finally you need domain specific deployment approaches. It's going to, you know, the capacity of a lot of these AI tools to be extremely useful in workflows probably far exceeds the adoption today. And there's going to be a great challenge over the next decade of figuring out how to get AI into all the places it needs to get into. And so we think for all those reasons being domain specific is very important. I think that's pretty evident to this.

[Ed Ludlow (Co-host or secondary host)]

And so is that 100 million to ensure the adoption curve is where you need it to be. Where does that money get deployed first and foremost?

[Matt Hart]

Yeah, it's a combination of things. I think for us, first and foremost, we're always focused on building the most capable and the most accurate AI for accounting. So we are growing our engineering and ML teams dramatically. We're fully New York based company and we essentially want to be the home for applied AI work in New York City. So that's always number one priority. But the other aspect of it is we are now starting to serve accounting Firms across all of their practices, CAs and core accounting being the initial segment, but now also tax audit, broader advisory. And over time, figuring out how we can get AI into all these various places is extremely important. Demand has exceeded our capacity to serve it and so we felt it was important to bring additional capital to make that possible.

[Ed Ludlow]

So I'm going through my taxes right now and through the portal of my accountant, who I won't name. They do a good job. I upload all of the documents W2, 1099, 1098, whatever. But there is an element of observability because I still still have to go in and double check all of the automated part of it. I know that's not the same, but the case study you gave of a business tax filing, start to finish, the observability piece must be critical if you're handling that for businesses of scale.

[Matt Hart]

Yeah, absolutely. Good question. You know, we think that the ability for an accountant to understand what's happening at a granular level as the AI is helping them get work done is extremely important. That goes back to a little bit about what Caroline was referring to in terms of the, you know, what makes us different than generic tools? Having domain specific user experiences and domain specific auditability functionality is extremely important. And then we also think that accounting firms have a very important role to play. At the end of the day, what people like yourself and what businesses around America probably want is a human that they have a relationship with, that they trust to do this incredibly important work. And so having the AI collaborate with humans to make that possible in an even better fashion, maybe we'll improve the experience that you have on your taxes in future years as firms figure out how to bring these two things together is extremely important.

[Ed Ludlow]

So, so here in the central question is, is it a, an aid to an existing job or does it displace an existing role in accounting going forward? We just have 30 seconds.

[Bloomberg Host/Announcer]

Sure.

[Matt Hart]

Not a 30 second question, but I'll give you my best answer on it.

[Ed Ludlow]

Sure.

[Matt Hart]

I think, you know, if you look at what's happened with software engineering over the course of last year and you can look at this internal to basis pretty much today, no engineer at the company should be writing any meaningful amount of code. And yet our engineering team, our machine learning team, is as busy as it's ever been. We're hiring as aggressively as we possibly can be in those areas. And that's because there's so much additional engineering work that we want to be able to do. That when you free up time to focus on More things you can do, more ambitious things you can build, things you never thought you'd want, you never thought you'd be able to do. And the same thing is true for accounting. There's tons of accounting work in the world that doesn't get done today. The Pentagon's just failed its eighth consecutive audit. You know, companies are misstating financials because they don't have enough accounting resources. Beyond that, you know, the accounting, you know, if you go to any hospital system in America, they can't tell you how much it costs them to provide a simple procedure like a knee surgery. These are all things that accounting can make possible. It is sort of the fundamental way that we understand economic activity that goes on in and around our organizations. And so we think there's a huge opportunity to do more accounting work. Most accounting firms, firms see that opportunity as well and need the capacity to be able to do that. And so from our perspective, this is going to allow firms and the accountants at those firms to take on even more work and get things more done, get more things done in the same way that that sort of software engineering has been able to take off over the course of the last 12 months.

[Ed Ludlow]

Matthew Hart, CEO and co founder of Basis that was a pretty good, pretty good summary, actually a little more than 30 seconds, but we'll give you it. Thank you very much. Now, coming up, we've got to look forward to what to expect from President Trump's State of the Union address, which is later tonight. We have the preview. This is Bloomberg Tech. All eyes are on President Trump's State of the Union speech tonight. This only days after the Supreme Court decide to strike down his tariff policies. Bloomberg TV's Washington correspondent Tyler Kendall joins us. What do we need to expect?

[Caroline Hyde]

Yeah.

[Ed Ludlow (Co-host or secondary host)]

Hey, Ed.

[Caroline Hyde]

Well, President Trump is expected to tout his economic policies that are already enacted, but also push ahead some policy proposals that he would like to see enacted related to affordability as the White House really plays defense on the issue, according to recent polling. In fact, the Wall Street Journal is now reporting that President Trump is set to announce a negotiated commitment from big tech companies to pay more when it comes to electricity costs related to air data centers in a bid to remove some of that burden from U.S. consumers. I was here at the White House just last month Speaking to the U.S. energy Secretary Christopher Wright, as the administration urged the nation's largest power grid to hold an emergency power auction specifically for these big tech companies. So perhaps we'll get some firmer details here on that tonight because as you well know this has been a White House trying to thread the needle between bolstering artificial intelligence, but also trying to quell some of those concerns from Americans when it comes to jobs and of course the cost of living related to electricity because that is going to be the number one issue as we head into the midterms. A new poll out this week from Ipsos finds that 57% of U.S. adults disapprove of the President's handling of the economy. Front and center, as you mentioned, is going to that be tariff policy. And sitting there in front of the President tonight is going to be those Supreme Court justices that struck down those IPA tariffs last week.

[Ed Ludlow (Co-host or secondary host)]

Bloomberg's Tyler Kendall with the rundown. Thank you very much. And look, the State of the Union is also the target for bets on prediction markets like how she like polymarkets. Look, a market that was once a fringe obsession of economists and election wonks, now traders are wagering on just about everything. Critics call it unregulated gambling. And it's a today's big take deep dive, I'm pleased to say. Bloomberg contributor Chris Beam is here to talk us through it. It is a wonderful deep dive. And just as we think about the State of the Union, how has the idea of regulating this changed in the years?

[Brody Ford]

So currently the, the status quo is that prediction markets are regulated by the cftc and the reason is that they technically offer what are called events contracts and event contracts are derivatives. And so the CFTC argues that falls under their purview. Now there's a lot of people who disagree with the cftc, state gambling regulators, a lot of casinos and other members of the gambling industry that argue yes, that that prediction markets should actually count as gambling and therefore be regulated by the states.

[Ed Ludlow]

How good are are prediction markets at predicting the future?

[Brody Ford]

So it depends what kind of market you're talking about. A lot of scholars have looked at political markets and prediction markets to predict elections and have overall found that prediction markets are more accurate than polling and certainly more accurate than you or me or any individual trying to prognosticate about elections. What's interesting though is that those markets become less accurate the smaller they are. So you know, a presidential election market could be quite accurate. But then when you, once you get down to more, you know, state and local races, when there's less liquidity, that's going to be less accurate.

[Ed Ludlow (Co-host or secondary host)]

I mean some of the bets that we see are extraordinary. I mean, I don't know how much liquidity there is on whether Jesus Christ is going to return in the next couple of years. But that's literally something you can go and place a wager or at least a prediction on using these markets. How have the companies themselves Calcium Polymarket navigated what has been them thrust into really now success, but also backlash at the same time and worries about insider

[Brody Ford]

trading in this yeah, the companies have taken different approaches. Kalshi has really tried to position itself as the adult in the room. They emphasize the internal rules that they have around insider trading, around market manipulation. They have whole teams and software algorithms designed to detect trading patterns that might set off red flags which they then report to regulators. Polymarket is in a slightly different position because so much of their trading happens overseas and is not regulated by the cfd TC and they also just haven't talked about it as much. So I'd say Kalshi, particularly because it was the earlier entrant in the US has emphasized cooperating with regulators, trying to be above board about the markets that

[Ed Ludlow]

they provide it's the latest Bloomberg Big take and it's a must read. Bloomberg contributors Chris Beam, thank you very much. That does it for the did this edition of Bloomberg Tech. It's not as if there's a shortage of things to come this week. State of the Union and then in video on Wednesday and earnings after the

[Ed Ludlow (Co-host or secondary host)]

bell today as well. Look, just don't forget to check out our podcast. You can find it on the terminal as well as online on Apple or Spotify on Iheart. The tech news keeps coming as is the disruption. This is Bloomberg Tech.

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