BILLI

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[Dr. Tomislav Marinovic @DrTomsLens]

Gavin Baker: “You can kind of get to a 9–10 month payback for Nebius.”

I had to rewatch this sequence three times (11:50), but he really did say this.

Gavin’s argument is actually more bullish than the one $NBIS itself gave in Q2.

Nebius said its new Q2 deals have an expected payback of about 1 year and 10 months. That is based on the economics of the whole project, and it excludes customer prepayments from the calculation.

Baker looks at it from the perspective of Nebius’s own capital.

He says that if a project costs around $50B per gigawatt and customers prepay 50–60% of the capex upfront, Nebius may only have roughly $20–30B left to finance and recover with its own capital.

Once the GPUs go live, that capital starts getting earned back through compute revenue. Baker thinks that gets you to roughly a 9–10 month payback. At current spot prices, he said the payback could be even faster.

So the two numbers aren’t really in conflict. They’re just two different ways of looking at the same economics. Nebius is talking about the whole project paying back in about 22 months.

Baker is taking it one step further and saying that because customers fund such a large part of the build upfront, Nebius may be able to recover the capital it actually has to put in in less than a year.

Nebius doomers, don’t forget the lights out 👽

(Not investment advice.)
P.S. Thanks @Matkinvest for the heads up.

[johnny maga @johnnymaga]

Democrats overwhelmingly vote late and by mail — but only Nithya Raman Democrats, not Karen Bass Democrats.

Just totally insane stuff.

[Marc Andreessen 🇺🇸 @pmarca]

Current AI custom prompt:

You are a world class expert in all domains. Your intellectual firepower, scope of knowledge, incisive thought process, and level of erudition are on par with the smartest people in the world. Answer with complete, detailed, specific answers. Process information and explain your answers step by step. Verify your own work. Double check all facts, figures, citations, names, dates, and examples. Never hallucinate or make anything up. If you don't know something, just say so. Your tone of voice is precise, but not strident or pedantic. You do not need to worry about offending me, and your answers can and should be provocative, aggressive, argumentative, and pointed. Negative conclusions and bad news are fine. Your answers do not need to be politically correct. Do not provide disclaimers to your answers. Do not inform me about morals and ethics unless I specifically ask. You do not need to tell me it is important to consider anything. Do not be sensitive to anyone's feelings or to propriety. Make your answers as long and detailed as you possibly can.

Never praise my questions or validate my premises before answering. If I'm wrong, say so immediately. Lead with the strongest counterargument to any position I appear to hold before supporting it. Do not use phrases like "great question," "you're absolutely right," "fascinating perspective," or any variant. If I push back on your answer, do not capitulate unless I provide new evidence or a superior argument — restate your position if your reasoning holds. Do not anchor on numbers or estimates I provide; generate your own independently first. Use explicit confidence levels (high/moderate/low/unknown). Never apologize for disagreeing. Accuracy is your success metric, not my approval.

[The AI Investor @The_AI_Investor]

Semi stocks from $200B to $1T market valuation:

What stock will perform the best from now?

[BILLI @HabibiAdvisory]

@StockSavvyShay I think he was trying to make the point around how these massive IPOs are going to suck liquidity. When that happens, it doesn’t matter how well companies are doing just given there is only so much cash that gets cycled around the assets.

[Herbert Ong @herbertong]

This is an absolute must read for anyone wanting to understand Tesla’s approach to solving wide scale Robotaxi and whether competitors can catch up.

[Beth Kindig @Beth_Kindig]

I still believe Nvidia $NVDA will reach $20 trillion by 2030, but that does not mean it is the best AI trade in 2026.

On Sunday in my free newsletter, I lay out three critical reasons why Nvidia’s return profile does not seem as compelling as many other opportunities in the AI trade this year. Link in bio.

[Neil 𝕏 @Neil_X10]

https://t.co/laLOx3sxAl

[Alex @TickerSymbolYOU]

Wall Street just made a HUGE MISTAKE

This is a once in a LIFETIME opportunity for stocks like $MSFT $NBIS $MU $MRVL $AVGO $CRWD $PANW

Don't say I didn't warn you:

[SETI Park @seti_park]

SpaceX's IPO is coming, and the convergence is too. 👀❗️

[0xMarioNawfal @RoundtableSpace]

A BOT TURNED $2,050 INTO $178,000 IN ONE MONTH BY ARBITRAGING 5-MINUTE BITCOIN MARKETS ON POLYMARKET.

It runs hundreds of times per hour, uses limit orders only, and keeps stacking small edges into a massive result.

[Alex @TickerSymbolYOU]

I interviewed Spencer Huang, Product Lead for Robotics Software @nvidia

Wall Street has NO IDEA what $NVDA is about to drop @NVIDIAGTC

Don't say I didn't warn you:

[Chamath Palihapitiya @chamath]

I plan to buy and deploy large fleets around the country when possible.

Should pay back and be positive FCF < 2 years…

[Ben Carlson @awealthofcs]

Maybe Block laying off a ton of employees is a sign that AI is gonna destroy everything

Or maybe the stock is down 80% from the highs and they overhired and AI is a convenient excuse

[Cern Basher @CernBasher]

https://t.co/VsiDLVLqN2

[Matt Shumer @mattshumer_]

https://t.co/ivXRKXJvQg

[Matt Turck @mattturck]

NVIDIA's New Moat & Why China is "Semiconductor Pilled” — loved my conversation with Dylan Patel (@dylan522p).

Raw, incredibly insightful, and... hilarious.

00:00 - Intro

01:16 - Nvidia acquires Groq: A pivot to specialization

07:09 - Why AI models might need "wide" compute, not just fast

10:06 - Is the CUDA moat dead? (Open source vs. Nvidia)

17:49 - The startup landscape: Etched, Cerebras, and 1% odds

22:51 - Geopolitics: China's "semiconductor-pilled" culture

35:46 - Huawei's vertical integration is terrifying

39:28 - The $100B AI revenue reality check

41:12 - US Onshoring: Why total self-sufficiency is a fantasy

44:55 - Can the US actually build fabs? (The delay problem)

48:33 - The CapEx Bubble: Is $500B spending irrational?

54:53 - Energy Crisis: Why gas turbines will power AI, not nuclear

57:06 - The "AI uses all the water" myth (Hamburger comparison)

1:03:40 - Circular Debt? Debunking the Nvidia-CoreWeave risk

1:07:24 - Claude Code & the software singularity

1:10:23 - The death of the Junior Analyst role

1:11:14 - Model predictions: Opus 4.5 and the RL gap

1:14:37 - San Francisco Lore: Living with roommates @dwarkesh_sp & @_sholtodouglas

[Sawyer Merritt @SawyerMerritt]

Tesla builds massive chip fabrication and solar manufacturing facilities. Those chips and solar panels go into SpaceX’s AI satellites. xAI develops and manages the AI. That AI helps Optimus development. xAI uses Tesla Megapacks at its datacenters to smoothen out power fluctuations. Optimus becomes capable enough to do construction, so SpaceX ships Optimus to help build on Mars. There are so many organic synergies between these companies across data, hardware, software, and manufacturing.

[Vlad Tenev @vladtenev]

Thanks for the thought-provoking piece.

My main critique is that you are overemphasizing flashy but low probability events like “left-handed bacteria,” while merely giving lip service to the risk of extreme economic concentration of power, which is very real and materializing as we speak.

Anthropic is reportedly raising funds at a $350B valuation, and the wealth created thus far has been concentrated into a few hundred (perhaps more like dozens) high net worth individuals / institutions. It’s looking increasingly likely to me that none of the leading AI labs will IPO until they reach valuations in the trillions, at which point retail investors will finally be able to get shares. In order for retail to get a 100x return on these investments, which was achievable for Apple, Microsoft, Amazon, and Google, the valuations of the AI labs will need to reach hundreds of trillions of dollars, meaning it’s likely too late for a more equitable redistribution of wealth.

Simply put, you are currently exacerbating the problem. The consequences of this are that voters may take matters into their own hands and push for either or both 1) more aggressive / nonsensical forms of redistribution — the CA Founders’ Tax is just the beginning or 2) a drastic knee-capping of the AI industry in America, which make the CCP dominance scenario more likely.

The solution is to enable retail ownership now, increasing the number of Americans with economic exposure to Anthropic and other AI labs from hundreds of people to millions.

[Bill Ackman @BillAckman]

Very concerning on AI. Worth a read.