IPOs and SPACs are Back, Mag 7 Showdown, Zuck on Tilt, Apple's Fumble, GENIUS Act passes Senate

JasonBullishtracking with the call

Jason picks Google as one of his top two AI winners, arguing that Google's vast data across Gmail, Chrome, Android, YouTube, and Search will make its ad network increasingly effective even if search share declines, driving continued ad revenue growth.

“all that data is going to lead to an ad network that performs so much better that even if they lose search share, their ad network is going to continue to grow. And I think it will increase in velocity.”▶ Listen · 35:00 ⚑

FriedbergBullishtracking with the call

Friedberg picks Google as his #1 pick for the AI prize, citing a diversified portfolio of high-beta moonshots (Waymo, quantum, Isomorphic biologics), deep model research competency beyond LLMs, and Sundar's thoughtful evolution of search — any one bet hitting would offset core business risk.

“I would put Google number 1. I would probably put Tesla, uh, Tesla's valuation, I think already has a premium associated with those options. Yeah. So I don't know if I would really pay that premium.”▶ Listen · 39:31 ⚑

ChamathBullishtracking with the call

Chamath picks Google as his #2 AI winner, citing exceptional Gemini models tightly coupled to TPUs, a quantum computing lead, an upcoming generative AI media disruption via tools like VO3, and a massive user funnel across YouTube, Gmail, and Search to monetize via price-per-token.

“Tesla's one and Google's two. And the reason is because they are the closest to having that vertically integrated stack that I spoke about.”▶ Listen · 30:47 ⚑

FriedbergCommentarytracking with the call

Friedberg sees Tesla as the best place to invest for exposure to the humanoid robotics opportunity, describing it as a low-probability, high-upside call option embedded in the business, though notes valuation already carries a premium for this optionality.

“I think that Tesla probably has the— it is the best place to invest if you want to have a shot at a massive new industry. So they've got a baseline business in, in obviously the automobiles. But I think this humanoid robot opportunity is ab”▶ Listen · 35:28 ⚑

Thomas LaFont picks Tesla as his #2 dark horse pick to win the AI prize, citing its potential for full vertical integration from silicon to model to hardware, with Optimus extending beyond cars.

“My number 2, more of a dark horse, but I would pick Tesla. I do think it has the most potential for vertical integration, right? From all the way, the silicon to the model to actually the hardware, right? That might become super important,”▶ Listen · 30:20 ⚑

ChamathBullishtracking with the call

Chamath argues Tesla is misunderstood and undervalued, citing its vertically integrated AI stack spanning vision models, xAI's LLMs, Dojo infrastructure, and physical AI applications in robotics and autonomous vehicles, making it his #1 pick to win the AI prize in 5 years.

“Tesla's one and Google's two. And the reason is because they are the closest to having that vertically integrated stack that I spoke about. I think that Tesla has the best vision models. Now with xAI, they'll have one of the best LLMs and r”▶ Listen · 30:47 ⚑

ChamathCommentary

Chamath argues Meta's moves to acquire Scale AI's training secrets and Nat Friedman's app secrets are strategically sound, but Meta still lacks the critical infrastructure/compute 'secrets' that rivals like OpenAI, Google, and Deepseek have, meaning they'll remain behind without that final piece.

“he's bought the training secrets, he's bought the app secrets, and now he has to buy some infrastructure and compute hardware secrets. You put it together and he's got a pretty good strategy here.”▶ Listen · 21:12 ⚑

Thomas LaFont argues Meta's aggressive spending on AI talent and Scale AI is highly rational given the size of the AI opportunity relative to its market cap, drawing parallels to Facebook's past strategic pivots.

“if you think about Meta's market cap is, uh, rough math, $1.7 trillion. If you're the CEO and you ultimately believe that maybe 50% of your market cap is at risk because of AI, $850 billion, why would you not spend maybe 4 or 5% of that”▶ Listen · 13:10 ⚑

FriedbergCommentary

Friedberg acknowledges NVIDIA's durable moat but flags a low-probability, high-severity risk from China developing competitive semiconductor manufacturing alternatives, arguing US policy is inadvertently incentivizing China to build NVIDIA substitutes.

“I think NVIDIA, to Thomas's point, I think the common thesis is it is the most protected, the durability of the business is there, but I would argue that there's actually a low probability, but very high severity risk to NVIDIA in China.”▶ Listen · 36:10 ⚑

Thomas LaFont picks NVIDIA as his #1 AI winner, arguing the GPU remains the dominant architecture with all roads still leading to it, and he doesn't see it being displaced.

“Look, I, I think to me, number 1, I, I still think NVIDIA, right? I don't see the GPU kind of getting displaced. I see additional architectures kind of coming on board, right? And growing the market. But, um, at the end of the day, all road”▶ Listen · 29:59 ⚑

Thomas LaFont sees Apple in a structurally weakened AI position — it no longer controls silicon or foundation models as it did in mobile — but argues it's too early to count them out given their $3T market cap, user monopoly, and the possibility of a bold acquisition like OpenAI.

“they're the opposite, right? They don't control... the silicon, they don't control the underlying models. Um, and so now they're back to maybe... the PC makers who didn't control the OS... I think it's way too early to count them out.”▶ Listen · 46:06 ⚑

ChamathCommentarytracking against the call

Chamath argues Apple is transitioning into a cash cow with no viable path to AI leadership — it can't attract top AI talent, its revenue growth is stalling, and its culture of optimizing for incremental hardware revenue prevents the bold innovation needed to compete in the AI era.

“I don't think they have any chance of anything. Okay.”▶ Listen · 51:27 ⚑

ChamathCommentarytracking against the call

Chamath argues Microsoft's employee base and business will likely grow, as it can bundle point-feature SaaS competitors into its platform and benefit from the broader cloud buildout, even if AI-generated code quality concerns mean layoffs aren't primarily AI-driven.

“I suspect that Microsoft's business on the margin grows. Back to Dave's point, some of the 493 shrink and go away. It'll be cheaper for Microsoft to bundle together a bunch of other products that are point features today, and so they'll hav”▶ Listen · 1:33:38 ⚑

FriedbergCommentarytracking with the call

Friedberg argues Microsoft faces probable revenue decline over 5 years as its enterprise customer base gets disrupted by AI-native software, with the old-school buyers dying and new AI-native builders not using Microsoft products.

“I do think like on this, on the application software layer, they're going to have a really hard time in this new world because the old school customers that buy Microsoft are going to die.”▶ Listen · 1:34:24 ⚑

ChamathCommentary

Chamath sees Amazon retail as a kingmaker for physical AI (robotics, drones) but views AWS as constrained by being a broad marketplace rather than tightly coupling its own hardware and models — arguing Andy Jassy will need to make difficult, expensive bets including potentially acquiring Anthropic to remain competitive.

“For physical AI, they're a kingmaker in parts because they're a, a sink for demand. So they'll just generate so much demand for robots… But yeah, the Amazon retail side is going to be a kingmaker for all of these physical AI things.”▶ Listen · 1:29:10 ⚑

ChamathCommentary

Chamath argues the SaaS business model is structurally broken as AI enables rebuilding enterprise software from scratch at a fraction of the cost, making existing SaaS licenses unjustifiable and accelerating the unraveling of the entire software cartel.

“I think that the jig is totally up for software... if you look at anybody that's rebuilding software, It is so much easier to rebuild software from scratch today... you can't help it but deliver custom solutions that are meaningfully”▶ Listen · 1:05:57 ⚑

ChamathCommentarytracking against the call

Chamath argues consumption-based pricing models like Snowflake's are self-defeating long-term because customers can't tolerate variable escalating costs and will migrate to alternatives like Postgres or Supabase, destroying the business over time.

“consumption-based pricing. It doesn't work. And what I mean is you can have some adoption in the short term. The best example is Snowflake. But in the long term, it destroys your business. And the reason is because you don't know which data”▶ Listen · 1:10:56 ⚑

FriedbergBearish

Friedberg argues this is the first time in 20 years he'd feel comfortable shorting the S&P (ex-Mag 7) while picking a few AI winners, as AI creates historic dispersion between companies that adopt and those that don't.

“I think it's the first time you could probably argue that you could go short the S&P Yeah, and pick a couple of winners. It might be the first time that I would feel in the last 20 years— because I'm pretty negative on people being able to”▶ Listen · 1:19:41 ⚑

ChamathCommentary

Chamath and Friedberg converge on the view that owning a synthetic index of AWS, Azure, and GCP would be the single best investment over the next 5 years, as cloud infrastructure is the essential substrate of the AI economy.

“If I could somehow automagically create an index of all 3 of those businesses, right? Over the next 5 years. Yeah. You wouldn't need to own anything else. 100%.”▶ Listen · 1:36:57 ⚑