Google Goes All-In on the AI Arms Race

Summary

Prof G Markets – "Google Goes All-In on the AI Arms Race"
Date: February 11, 2026
Hosts: Ed Elson, Gil Luria
Key Guests: Doug O’Laughlin (President, SemiAnalysis)

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Episode Overview

In this episode of Prof G Markets, Ed Elson and Gil Luria dissect the seismic shifts in tech and capital markets driven by generative AI, focusing on Google’s record-breaking corporate debt issuance and the escalating “AI arms race” among tech’s biggest players. The conversation stretches from the tactical and strategic motives behind Google’s $32 billion bond sale to the knock-on effects in the chip market, and finally to growing public and political resistance to AI’s rapid expansion.

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1. Big Tech’s Debt-Fueled AI Arms Race

Google’s Monumental Debt Offering ([02:13–04:19])

• Key Fact: Google raised nearly $32 billion in debt in less than 24 hours—the largest in its history, among the biggest ever by a corporate.
• Orders exceeded $100 billion for the US dollar tranche; included a rare 100-year bond.
• Coincided with an announced doubling of Google’s 2026 CapEx, part of a broader Big Tech commitment: Amazon, Google, and Microsoft will spend a combined $660 billion on AI infrastructure in 2026—a 60% increase year over year.

Gil Luria (DA Davidson, guest) on Why This Matters ([04:19–06:18])

• “Google has plenty of cash…They can cover all of their CapEx needs with the cash flow they have…But they’re choosing to borrow money to create more capacity. This is very low-cost borrowing for them, and it aligns them with where they need the cash.” – Gil Luria [04:21]
• The 100-year bond serves as a “signal”: Big Tech is telegraphing their long-term commitment, intending to “outlast everybody.”
• Industry context: Meta’s Mark Zuckerberg also making massive CapEx outlays (“forget he paid $14 billion to hire Alexander Wang”)—the giants are determined to win at any cost.

Risks and Competitive Dynamics ([06:18–07:46])

• “It’s a concern for whoever loses. Whoever wins, all this CapEx will have been great. [If] there’s any losers in that group, they’re going to be stuck with a lot of infrastructure they’ll have to sell at a discount.” – Gil Luria [06:50]
• For megacaps (Google, Microsoft, Amazon), taking on debt isn’t a sign of weakness, but a show of financial strength—a “flex.”
• The banks “always prefer lending money to the companies that don’t need to borrow.”

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2. Market Reaction and Implications for Oracle, OpenAI ([07:46–11:12])

• Google’s debt move resulted in only a “tepid” stock reaction, unlike Oracle’s recent bond raise, which led to a 9% crash.
• “Google has the cash and the cash flow to support paying back that interest for a very long time.” [08:11]
• Oracle, by contrast, is “really stretched right now”—had committed to a massive infrastructure buildout without the same balance sheet safety net. However, anticipated cash from OpenAI (if it succeeds in a $100B raise) could bail out Oracle.
• DA Davidson upgraded Oracle to a “Buy” after its stock fell and OpenAI re-focused. “Now it looks like OpenAI will be able to pay those Oracle bills and again bail Oracle out of a very tough situation.” – Gil Luria [09:40]

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3. Is “Software Dead”? The AI Disruption Debate ([11:12–13:27])

• “AI is a major disruptive force in all of technology and the whole economy. And specifically for software…What happens when you have major disruptive forces is that excellent companies and good businesses execute well and win, and companies that are not very good…fall by the wayside.” – Gil Luria [11:51]
• Recent turbulence in software stocks created bargains: “You had an opportunity last week to buy unbelievable companies like Snowflake and Datadog at 35 times cash flow. Microsoft at 20 times earnings because of this onslaught on all of software.”
• The correction is seen as an opportunity: “We love that because that’s what creates opportunities.”

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4. Memory Chip Market Mania: Demand, Cycles, and AI ([15:53–23:29])

Guest: Doug O’Laughlin, President, SemiAnalysis

Explaining Memory Chips ([16:51–17:53])

• Memory = DRAM (volatile, fast) and NAND (non-volatile).
• New star: HBM (High Bandwidth Memory).

The Current Supercycle ([17:53–19:25])

• “We are in what is probably the most historic memory cycle of all time. Demand specifically from AI has skyrocketed…when you have a bad memory cycle, your desire to spend on new capital equipment is very low…And then boom, a giant demand vector hit the industry.”
• AI data centers have created a “perfect supply-demand mismatch”—no new capacity online in time to meet demand, so memory prices are up 100%.

Knock-On Effects and Stock Projections ([19:25–21:29])

• This mirrors energy market dynamics. “We think the biggest bottleneck in the market right now today is memory.” – Doug O’Laughlin [20:29]
• DRAM and NAND prices are driving consumer electronics costs higher.
• “That’s how you think about it: I would expect [memory stocks] to continue to do well, but maybe not at the past rate. They’ve done well, especially out of the worst cycle of all time into the best cycle of all time.” – Doug O’Laughlin [23:23]

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5. The Anti-AI Backlash Intensifies ([23:40–27:08])

AI’s Popularity Problem ([23:40–26:45])

• AI’s hype is everywhere: “If you watched the Super Bowl…1 in 4 of the ads that were aired featured AI in some capacity.”
• But public support is weak:
  • Over 80% of Americans “concerned” about AI.
  • More than 75% fear it “could pose a threat to humanity.”
  • Less than half currently have a favorable view of AI.
• “AI is broadly unpopular in America. Now, to be fair, this happens a lot with new technologies…But we should also recognize it’s getting to the point where AI is so disliked that now actual obstacles are being put in place.”

Political and Community Pushback ([26:45–27:08])

• Politicians (notably Ron DeSantis) proposing data center construction bans.
• “You look at OpenAI’s new Stargate data center, for example…that’s going to employ about 100 people. That is roughly a third of the number of employees at a standard Walmart location…Meanwhile, electric bills are indeed going up in areas where data centers have been built—the price of electricity has risen roughly 250% over the past five years.” [27:08]
• Legal and political resistance in Michigan, Arizona, Virginia, Georgia, with proposals ranging from restrictions to outright bans on data centers.

The Big Open Question

• Ed Elson: “The biggest conversation we’re not having is: how many people actually want this?...What does America disliking AI actually do to valuations? What does it do to earnings? What does it do to cash flows?…Ultimately, the answers…will determine the future of AI. Like any other product, its success will be a function of how many people like it. And increasingly that number is going down.” [27:08]

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Notable Quotes & Moments

• Signaling through financial might:
  “By issuing a hundred-year bond, [Google is] saying we’re in it for the long haul.” – Gil Luria [04:37]

• On the risks of being an ‘AI arms race’ loser:
  “Whoever wins, all this CapEx will have been great. [If] there’s any losers…they’re going to be stuck with a lot of infrastructure they’ll have to sell at a discount.” – Gil Luria [06:50]

• On the popularity of AI:
  “AI is broadly unpopular in America. Now, to be fair, this happens a lot with new technologies…But we should also recognize it’s getting to the point where AI is so disliked that now actual obstacles are being put in place.” – Ed Elson [25:30]

• On data centers:
  “These hyperscale data centers use as much power…as a city of half a million people. Once it is built, the local community doesn’t really benefit from it. It’s a robot that’s building shareholder value for people who own AI stocks.” – Ed Elson [26:53]

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Timestamps for Key Segments

• [02:13] – Google’s record $32B bond raise and significance
• [04:19] – Gil Luria unpacks Google’s motives and strategic context
• [06:18] – CapEx risks and the “winner take all” nature of AI
• [07:46] – Stock market reactions to Big Tech vs Oracle debt
• [09:40] – Why DA Davidson upgraded Oracle
• [11:12] – The “software is dead” debate in the AI era
• [15:53] – Memory chip boom with Doug O’Laughlin
• [17:53] – Supply/demand mismatch and AI-driven supercycle
• [19:25] – RAM prices, consumer impact, and stock outlook
• [23:40] – American skepticism and political resistance to AI
• [26:45] – Data center backlash: energy, jobs, politics

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Conclusion

This jam-packed episode charts the latest phase of the Big Tech AI arms race, with Google’s historic debt raise as a catalyst for broader industry shifts. Meanwhile, the show connects the dots between soaring capital investment, supply chain tremors (especially in memory chips), and the mounting social and political resistance to AI’s unchecked expansion. The tone is sharp, analytical, and at times wary—raising the pressing question of whether the financial “leg” of this AI race is running too far ahead of public sentiment.

Transcript

[Ed Elson]

Support for the show comes from Fundrise. For the past seven years, there's been a room in finance most people couldn't enter, a room where you could have invested in some of the biggest names in tech companies like Airbnb and Uber before their multi billion dollar IPOs. I'm talking about venture capital. Fundrise recently took a sledgehammer to those closed doors by launching a venture capital product that's available to anyone. Their mission is to give everyone the chance to invest in the best tech and AI companies before they go public. You can visit funrise.com profg to check. Check out Funrise's venture portfolio and get in early today. All investments involve risk, including a potential loss of principal. Past performance is not indicative of future results. This is a paid advertisement. Coming up on Today Explained. I talked to one of the top stars of the Democratic Party and one of the most divisive about her run.

[Doug Laughlin]

For Senate in Texas.

[Ed Elson]

I wonder, like, is there times in which the rhetoric goes too far? Are there times in which you should say, you know, maybe I messed that one up? No, not in this environment, I don't. I think that, you know, we are really in unchartered territory. Representative Jasmine Crockett this week on Today explained. Listen, wherever you get your podcast, Does.

[Doug Laughlin]

The winter weather have you feeling tired? Antisocial?

[Ed Elson]

Sad?

[Gil Luria]

You may want to take a cue.

[Ed Elson]

From our friends in Norway, Really. They tend to orient towards the things that they like about the season instead.

[Gil Luria]

Of just sort of seeing it as.

[Ed Elson]

A time of year to endure. How to embrace the winter.

[Gil Luria]

That's on the next.

[Doug Laughlin]

Explain it to me.

[Ed Elson]

New episodes every Sunday. Wherever you get your podcasts.

[Gil Luria]

Today's number 47.6. That's how many hours of sleep the average American gets each week. Today's other number is zero. That's how many hours of sleep Michael Saylor got last week.

[Ed Elson]

Money market matter if money is evil, then that building is hell.

[Doug Laughlin]

The show goes on.

[Ed Elson]

Sell, Sell.

[Gil Luria]

Welcome to Profit Markets. I'm Ed elson. It is February 11th. Let's check in on yesterday's market vitals. The S&P 500 and the NASDAQ declined on weaker than expected retail sales data for December. Financial stocks also dropped after Altruist Release released an AI tax planning tool. Charles Schwab fell 8% and Raymond James fell 9%. Meanwhile, the Dow notched its third record close. Spotify soared 15% after reporting record user growth and tripling profits from a year ago. And finally, Paramount sweetened its hostile offer for Warner Brothers discovery. It offered to pay the $2.8 billion termination fee that WBD will owe Netflix if the deal falls apart. WBD stock rose more than 2% on that news. Okay, what else is happening? Google just executed one of the biggest corporate debt offerings in history. On Monday, the company priced its largest ever US dollar bond sale, raising $20 billion across seven different maturities. That deal drew more than $100 billion in investor orders, one of the most heavily subscribed order books ever for a corporate bond sale. The next day, Google raised another $11.5 billion in sterling and Swiss francs. The sterling deal included an ultra rare $1.4 billion 100 year bond which attracted close to 10 times the amount offered in investor demand. All in. Google raised nearly $32 billion in debt in less than 24 hours. The borrowing spree came days after the company announced plans to roughly double its CapEx for 2026. And the spending surge extends across big tech. Amazon, Google, Microsoft plan to spend a combined $660 billion in AI infrastructure in 2026. That is up 60% from 2025. Okay, here to help us break down this debt offering from Google, we're speaking with Gil Luria, head of technology research at DA Davidson. Gil, good to see you.

[Ed Elson]

Good to see you.

[Gil Luria]

So Google just raised nearly $32 billion worth of debt in less than 24 hours. One of the largest debt offerings in a really long time. Take us through this. Why does this matter? What does this mean for Google?

[Ed Elson]

There's tactical and strategic aspects to this. So part of this is treasury management. Google has plenty of cash. They probably have 80 billion of net cash. They can cover all of their capex needs with the cash flow they have from their traditional advertising business. But they're choosing to borrow money to create more capacity. This is very low cost borrowing for them and it aligns them with where they need the cash. Sometimes you have cash in one country and you actually need another. And so a lot of this is tactical treasury management. Some of this is strategic, though. Let's not forget that Microsoft, Amazon, Google, OpenAI, anthropic meta, Elon, are all in this big competition to be the biggest winners in AI, which is going to be a very expensive competition that many of them believe is going to be winner take all, or at least winner take most. They believe that because their existing markets are like that. So what they're trying to do, and Google is doing this by issuing a hundred year bond, is to say we're in it for the long haul. We are going to spend as much as it takes to win. And they're not the first ones to do this. Mr. Zuckerberg at Meta signaled the same thing by increasing his capex continuously and by paying tens of billion dollars for talent. I Forget he paid $14 billion to hire Alexander Wang. So we're having this kind of signaling in the market by these really large players that are saying, you know what, we're going to outlast everybody. You should blink before we do.

[Gil Luria]

Is this of concern at all? The fact that we know that they're spending all of this money on CapEx, that it just exploded? We just learned in their previous earnings they're going to spend $660 billion on AI infrastructure in 2026. Something we've been saying a long time is, you know, that's a lot of money, but this is money that they have. Now we're seeing these gigantic debt offerings, which is basically them saying, no, now we need to borrow money to do this. Is that a concern or is this kosher?

[Ed Elson]

I would say that it's a concern for whoever loses, whoever wins all this. Capex will have been a great. There's any losers in that group that I mentioned, they're going to be stuck with a lot of infrastructure that they're going to have to sell at a discount. So that's the concern. But in terms of borrowing, especially if we're talking about Microsoft, Amazon, Google, and to the extent Apple ever gets into the game, they have so much cash flow, so much cash on hand that them borrowing is more a flex than anything else. Right. The banks always prefer lending money. The companies that don't need to borrow, and this is a great example of that, Google doesn't need to borrow, which is why it's so easy for them to borrow a lot at a very inexpensive price and again signal to the market that they have a lot more capacity than just their cash flow, which by the way is huge.

[Gil Luria]

Anyway, the market's reaction was, you know, tepid. Stock was down a little bit after the debt offering. Very different from what we saw last week when Oracle made the same move. And you saw just a giant crash in the stock, down around 9%. Is that markets telling us we think Google does have the capacity to borrow right now and we don't think Oracle does.

[Ed Elson]

Yeah, Google has the cash and the cash flow to support paying back that interest for a very long time. By the way, Google has been down the last couple of days. There's starting to be a reversion to the mean. Right. Google multiple is now in the 30s Microsoft and Nvidia in the low 20s, in spite of the fact that the growth rates are similar. And I would argue Microsoft and Nvidia is just as well positioned in the AI race. So we're starting to see a reversion to the mean. Oracle is very different. Oracle really painted themselves into a corner. They committed to an infrastructure build out that required them to raise a lot of capital in order to execute. They don't have excess cash flow, they're really stretched right now. But the good news is it looks like they will be successful in the raise, which means they'll be able to deliver. And if OpenAI can raise their own hundred billion dollars by the end of the quarter, which is the most important thing in AI right now, OpenAI will be able to pay for that Oracle capacity. And we can all breathe a sigh of relief for Oracle, which again really was in a little bit of a bind.

[Gil Luria]

Yeah, we should mention I found this fascinating. You guys over at DA Davidson, you upgraded Oracle to a buy, which is interesting because you're one of the people who's been kind of sounding the alarm on the position that Oracle has found themselves in over the past few months. Take us through the upgrade on the stock. Why have you regraded to buy?

[Ed Elson]

Yeah, so we sounded the alarm when the stock was $345 trading 45 times earnings and OpenAI looked to be losing momentum. What's happened since then is first of all, Oracle stock went down to 143eighteen times earnings. And then OpenAI very importantly a things happened there. One is OpenAI started to focus. Instead of being spread too thin, making promises they can't keep and trying a lot of different things, they're refocused on their Frontier model and on ChatGPT, which you can tell by the fact they're starting to advertise. Second thing that happened is because Google made such a splash with Gemini and just reported really good earnings this week. That really scared Microsoft, Amazon and Nvidia, which means they're very likely now to give OpenAI that $100 billion. And then finally OpenAI is probably pretty close to introducing another model. That'll be another leap forward, should become the state of the art again. So if OpenAI has state of the art model, is focused on the business and can raise the capital, then it will be able to pay all those bills that we were worried about. So that's what's changed. Oracle's stock price went down a lot. People were expecting OpenAI to not able to deliver. And because OpenAI has gotten their act together. Now it looks like OpenAI will be able to pay those Oracle bills and again bail Oracle out of a very tough situation.

[Gil Luria]

The other thing just before we let you go, that I want to hear from you on the SaaS is dead software is dead thesis, which really played out last week, all the software stocks got absolutely crushed. We've seen a little bit of a rebound this week. Not fully or not totally equally distributed across the software stocks. But as a whole, tech is rebounding, software's rebounding a little bit. Where do you stand on this debate at this point? People said last week software is dead, AI killed it. Where do you stand today?

[Ed Elson]

AI is a major disruptive force in all of technology and the whole economy. And specifically for software. What happens when you have major disruptive forces is that excellent companies and good businesses execute well and win, and companies that are not very good and not very good markets end up falling by the wayside. That's true in software as well. But what happened last couple of weeks is that all software stocks sold regardless if they're in the first or the second category.

[Gil Luria]

Right?

[Ed Elson]

And we love that because that's what creates opportunities. I've been in a software for a long time. I've always resisted putting revenue multiples on any company, including software companies. We don't have to anymore. These companies are now trading on free cash flow on their actual profit. And you had an opportunity last week to buy unbelievable companies like Snowflake and Datadog at 35 times cash flow. Microsoft at 20 times earnings because of this onslaught on all of software. That again ignores the fact that Datadog, Snowflake massively big winners in software. Microsoft, massively big winner in AI. But the sentiment against software was so negative that really good companies that are executing well and are well positioned for AI were selling alongside companies where the disruption may actually hurt them even though they have some years to execute. I understand that part, but again, I love the opportunity to buy companies growing 15, 20, 30% on a multiple of cash flow. We've never had that. And that's a great opportunity for investors.

[Gil Luria]

All right, Gil Luria, head of technology research at D.A. davidson. Thank you, Gil.

[Ed Elson]

Thank you, Ed.

[Gil Luria]

After the break, why memory chip prices are soaring. And for even more markets insights, you can subscribe to my weekly newsletter. Simply put@edwardelson substack.com.

[Ed Elson]

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[Doug Laughlin]

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[Doug Laughlin]

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[Ed Elson]

Hi everyone, this is Kara Swisher. And this week on my podcast on.

[Gil Luria]

With Kara Swisher, I'm interviewing defense attorney Abby Lowell.

[Ed Elson]

Last year, he left one of the country's premier law firms and went independent so he could defend clients targeted by the Trump administration, people like Don Lemon.

[Gil Luria]

Federal Reserve Governor Lisa Cook, and New York Attorney General Letitia James. Here's a snippet from our conversation.

[Ed Elson]

It's not random, it's not ad hoc.

[Doug Laughlin]

And it's not an outlier that their.

[Ed Elson]

First attack, after they had already neutered the Congress and they had politicized the.

[Doug Laughlin]

Courts, was to go after the lawyers.

[Ed Elson]

And to go after the journalists. The full interview is out now and you can find it anywhere. You listen to podcasts and, of course, on YouTube.

[Gil Luria]

Be sure to follow on with Kara.

[Ed Elson]

Swisher for great conversations like this.

[Doug Laughlin]

Over the last several years, AI companies of all shapes and sizes have been desperately trying to get their hands on every bit of available data to make their models better. This week on the Vergecast, we have.

[Ed Elson]

The story of how Anthropic destroyed hundreds.

[Doug Laughlin]

Of thousands, maybe millions of books and fed them all to Claude. Plus, we have information on who in tech is in the Epstein files, what's going on with Netflix, whether it's woke, whether it's going to buy Warner Brothers, and whether Peloton is going to successfully sell you a treadmill ever again. All that on the Vergecast, wherever you get podcasts.

[Gil Luria]

We're back with Prof. 2 Markets. Memory chip stocks are on a relentless tear right now. Shares of the three industry leaders have soared in the past year. Samsung is up 200%, Micron is up 300%, SK Hynix is up 340%. All of the memory chip stocks are soaring, and the reason is because AI data centers are devouring memory chips, leading to shortages across the rest of the tech industry. Meanwhile, shares in Qualcomm and ARM declined after they warned that these memory constraints could cap smartphone production. Apple's quarterly earnings were clouded by the same concern. So what are these memory chips exactly? And why are they so precious right now? Well, to answer these questions, we're speaking with Doug Laughlin, president of Semi Analysis. Doug, thank you for joining us on Profgue Markets.

[Doug Laughlin]

Thanks for having me. More than happy to answer Whatever questions.

[Gil Luria]

You guys have, we have plenty. So chip stocks are soaring this year. Memory chip stocks, that is. Can we just start with the basics here? Like what do memory chips actually do?

[Doug Laughlin]

So like the word implies memory often stores something for recalling later. Kind of like how our memory works. Now there's two key key styles of memory, which is dram, which is non persistent, meaning it works while it's plugged in. And there's something called nand or actually there's also hard drives as well. But for most people really care about DRAM and nand. Now NAND is non persistent, meaning that you can unplug it and it will still hold your information. So whenever you turn off your computer, all your files are still there, that's on nand. But when you turn on your computer, most of the time it's using faster memory, which is called dram. So those are the big categories of memory and there's actually kind of this newer category category called HBM called high bandwidth memory. But don't want to get too into weeds too quickly.

[Gil Luria]

So why are these memory stocks tearing right now?

[Doug Laughlin]

Yeah, so I think there's a little bit of history that helps set the context. So memory is notoriously cyclical. Pretty much every year there's new memory, demand comes online for more data. But when new memory supply comes online, often it comes on in chunks of 40 to 50%. So what happens is supply overshoots, demand boom, price goes down. Demand overshoots, supply boom, price goes up. We are in what is probably the most historic memory cycle of all time. Demand specifically from AI has skyrocketed and effectively we just came out of the single worst memory cycle ever. And when you have a bad memory cycle, pretty much your desire to spend on new capital equipment or new fab clean room space is very low. And so pretty much no one wanted to spend because they're burning all this money. And then boom, a giant demand vector had hit the industry. And so now everyone's kind of racing to invest in supply, but there's literally no supply for the next two years. And so you have that perfect supply demand mismatch. And that's the reason why memory prices have gone up 100%. And it's like it's going to hurt most basic consumer products like your phone, for example, the price in your phone of the, of the DRAM and even the NAND, the DRAM specifically is going to go up like 100%. And so that's kind of this crazy dynamic dynamic that's happening because of AI. AI is just demanding so much memory that it's kind of completely throwing the supply demand imbalance off.

[Gil Luria]

In an interesting way, it seems to mirror what we've been seeing with energy prices where you have this massive AI build out all of these data centers that consume huge amounts of energy. And one of the side effects of that is that energy costs go up. What you are saying is these data centers also consume huge amounts of memory chips. We don't have enough memory chips and therefore that might also increase the price of consumer goods, is that right?

[Doug Laughlin]

Yeah, for sure. It will definitely increase the price of consumer goods. Honestly, we think the, it's kind of crazy because you know, we do some here at semi analysis. We do actually do like a lot of work. Maybe this is a little bit of a rabbit hole. We do a lot of work on the energy pricing side of things too. Ironically, most of the energy pricing that you're seeing in the grids, like essentially what is recognized to the consumer is actually the past few years of investment. Honestly, given how much demand there is, I think most of the energy prices so far have very little AI to do with it. But the energy prices down the pipeline now, that's all AI. So it's kind of interesting. You're already seeing these price increases and this is even before the true demand vector came in. That's a complete side, kind of like a side tangent. But yeah, that's really what happened. There was essentially no supply. And I think the place that we're seeing our business is very focused on kind of seeing where AI impacts chips and semiconductors, hence the analysis. Right. And we think the biggest bottleneck in the market right now today is memory. And that's just because there's so much demand and there's so little supply. And the supply response takes often 18, 24 months. And we're, you know, I think we're six to 12 months into that. So we have at least 12 months before more supply comes online.

[Gil Luria]

So some of the memory names we're talking about here, Western Digital, Micron, Seagate, Sandisk, Sandisk is up 1,500% in the past year. Kind of unbelievable. Do you expect that this is going to continue over the next 12 months? It sounds like you think that the chips themselves will keep going up in price. Would you expect that the demand for the stocks that make the chips will also continue to go up?

[Doug Laughlin]

Well, this is where memory stocks are kind of like a whole 40 chess altogether. Because what happens is stocks are very, very forward looking. And the thing that really matters Is right now, every day, the stocks have been ripping on the fact that spot or contract price effectively has been going up. Now what's going to happen is that's going to continue to happen until there is real fungible, like a real supply response. And so we just don't see it until 1H27. We think that memory prices will continue to go up quite meaningfully into the rest of this year. And then in the first half of 27, we expect a meaningful amount of supply to come online. And we just don't think that cross is going to happen. Historically, what happens is when the first supply starts to come online, the stocks tank. There's no other way to put it. Going up this amount of this precipitously is often not sustainable. And I think everyone in the industry would tell you everyone understands this is not a sustainable price. And this just takes capitalism to fix it. Right? Supply will react to demand. But at this exact moment, we're at this crazy parabolic thing, and I think right now we see no reason that memory prices won't continue to rip for the rest of the year. And so that's kind of like the. That's how you think about it is I would expect them to continue to do well, but maybe not at the past rate. They've done well, especially out of the worst cycle of all time into the best cycle of all time. That kind of inflection is usually where the stocks go crazy. How I think about it, actually, if we're talking about from a pure stock perspective, if you think about Nvidia's giant year two years ago when Nvidia the stock went up, I don't know the numbers off my head. And then last year, honestly, Nvidia did outperform the market meaningfully, but we're talking 35, 40%. Right? Meaningfully above the market, but not quite as much. I think some of that inflated expectation is going to come out.

[Gil Luria]

Now.

[Doug Laughlin]

That obviously doesn't mean the stocks are going down. In fact, I'm very bullish, but I don't expect the same setup going forward.

[Gil Luria]

All right, Fascinating stuff. Doug o', Laughlin, president of Semianalysis, thanks for joining us, Doug.

[Doug Laughlin]

Yes, thank you for having me.

[Gil Luria]

Well, all this talk of AI and chips and, and data centers is honestly getting a little bit exhausting. If you watch the super bowl, you'll have noticed that 1 in 4 of the ads that were aired featured AI in some capacity. Meanwhile, AI is being mentioned in more earnings calls than ever before. Also, Google search interest in AI is already twice as high as it was just 18 months ago. And throughout this dialogue, a lot of people are asking a lot of different questions, such as, how are we going to use AI? How will it be generated? Who will be the winners? Who will be the losers? These are some of the most important questions of our time right now, and that's why we are covering AI so aggressively. But there is one more question that is arguably more important than any of the others, and it's a question that investors need to start taking seriously, and that is, how many Americans actually want AI? That might seem like a stupid, maybe simple question until you dig into the numbers and you start to realize that increasingly across America, people actually don't want AI. More than 80% of Americans say today that they are concerned about AI. More than 75% say that it could pose a threat to humanity. More than half say it's going to negatively impact our ability to do things on our own. And perhaps most importantly, less than half of Americans currently have, have a favorable view of AI right now. Put another way, AI is broadly unpopular in America. Now, to be fair, this happens a lot with new technologies. People find it scary. They say it's too much, they push back, and then ultimately the technology ends up being so useful that we end up using it anyway. And in all likelihood, that's probably what will happen with AI. But we should also recognize it's getting to the point where AI is so disliked that now actual obstacles are being put in place to prevent this massive AI buildout that we keep on talking about. Most notably, we're seeing this in politics. You might remember a few months ago, I said that I thought data centers were about to become the new political football. One thing about data centers, huge costs on energy and temporary job creation through the construction. But once it is built, actually the local community doesn't really benefit from it. It's a robot that's building shareholder value for the people who own AI stocks. And so it's becoming a really interesting. And I think this is going to become more prominent in the political sphere. But it's this NIMBY versus YIMBY debate. Well, we are now seeing this play out. Just last week, Ron DeSantis discussed a new proposal to prevent data center construction in Florida.

[Ed Elson]

These hyperscale data centers use as much power just to power the data centers.

[Doug Laughlin]

As a city of half a million.

[Ed Elson]

People, you have this much power that.

[Gil Luria]

You'Re capable of generating.

[Ed Elson]

You have this much demand. Right, right. And that's, that's kind of where we are if you double the demand, unless you also double the supply, prices are going to go up.

[Gil Luria]

Now, DeSantis argument is that data centers, while they might seem good for a local economy, they're actually quite bad for a local economy. Why? Because they don't really employ people. And more importantly, they send electric costs through the roof. Both of these statements, by the way, are true. You look at OpenAI's new Stargate data center, for example, that's going to employ about 100 people. That is roughly a third of the number of employees that work at a standard Walmart location. Meanwhile, electric bills are indeed going up in areas where data centers have been built. The price of electricity has risen roughly 250% over the past five years. And this is why these anti data center movements are now piling up around the country. In Michigan, protesters have filed several lawsuits against one of those Stargate data centers. Over in Arizona, the town of Marana has elected to block a data center as well. In Virginia, more than 50 data center regulation bills have been proposed this year. And in Georgia, lawmakers have suggested simply banning data centers across the entire state. All around America, people are slowly but surely deciding that they actually don't like AI. They don't like the CEOs, they don't like the companies, and they especially don't like the data centers. And we can have all of these businessy conversations about AI. We can talk about energy capacity and enterprise usage and memory storage, et cetera, et cetera. But the biggest conversation we are not having is how many people actually want this. This is what investors should be tackling, and it's also what investors should be pricing. What does America disliking AI actually do to valuations? What does it do to earnings? What does it do to cash flows? These are real questions, but so far we seem to be treating them as footnotes or background information. But ultimately, the answers to those questions will be, what determines the future of AI? Like any other product, AI success will be a function of how many people like it. And increasingly that number is going down. Okay, that's it for today. This episode was produced by Claire Miller and Alison Weiss, edited by Joel Patterson and engineered by Benjamin Spencer. Our research team is Dan Shalon, Isabella Kinsel, Kristen o' Donoghue and Mia Silverio. Thank you for listening to Profit you Markets from Profit Media. If you liked what you heard, give us a follow. I'm Ed Elson. I will see you tomorrow.