@MilkRoadAI @grok which companies would benefit the most from chamath’s above thesis over he next 24 months, give me you top 10 names
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Mohit Gaba
1.6K posts
Mohit Gaba
@mohitgaba66
Speculator
Dubai, United Arab Emirates Katılım Ekim 2011
567 Takip Edilen838 Takipçiler
Chamath Palihapitiya just laid out the most important valuation question nobody on Wall Street wants to answer.
For 20 years, the Mag 7 won because they had the greatest business model ever invented, asset- ight software.
You write the code once, you sell it to a billion people, the marginal cost of the next customer is basically zero.
There is essentially no factories, no raw materials, no union workers, no physical infrastructure, just pure leverage, scale the revenue, barely scale the costs.
That's how you get 30x, 50x, 60x earnings multiples and the market was paying for compounding economics that had no natural ceiling.
But AI just blew that model up.
The hyperscalers, Amazon, Microsoft, Google, Meta are now projected to spend between $600 and $725 billion on capex in 2026 alone, up from $250 billion just two years ago.
That number is climbing, not plateauing and it's not just the chips and the data centers, it's the energy contracts underneath all of it.
When Microsoft re signed Three Mile Island, they locked in a 20 year forward purchase agreement at more than $100 per megawatt hour nearly double the prevailing spot rate of $60 for wind and solar in the same region.
That's a long term liability commitment baked into operating cash flows for two decades.
Here's where Chamath's math gets uncomfortable.
These five or six companies are now collectively spending so much that their capex has exceeded their free cash flow meaning they can no longer self fund growth from operations alone.
In 2025 alone, hyperscalers raised $108 billion in new debt and projections put the total debt issuance over the next few years at $1.5 trillion.
These are companies that, for two decades, were net cash accumulators and now they're going to the debt markets like everyone else with term loans, revolvers, and structured credit facilities.
That's Chamath's core point and it's a devastating one for anyone still modeling these companies the old way.
When a company is asset light, investors pay a premium for that lightness and the multiple reflects the belief that returns on capital will stay high indefinitely, because there's no heavy physical plant dragging them down.
But when Google starts looking like a utility locked into 20-year energy contracts, carrying hundreds of billions in debt, spending half its revenue on physical infrastructure, the rational multiple compresses.
You don't price a utility at 30x earnings, you price it at 12x.
His conclusion is that stop trying to value the hyperscalers themselves and follow the money instead.
A trillion dollars a year is flowing out of these companies into power companies, data center operators, chip manufacturers, cooling systems, fiber networks, rare earth metals.
The companies on the receiving end of that spending are already underpriced because the market is still staring at the senders while ignoring who's cashing the checks.
The asset-light era minted the most valuable companies in human history and the asset heavy era that's replacing it might be the best argument yet for owning everything around them instead.
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Will never understand why we insist on Daylight Savings Time & Standard Time - who in the world wants the sun to set at 5.09 pm? The day was just fine yesterday when it set at 6.10 pm. 🌅🤷♂️
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@grok @VishalRDaswani how come you got the actual names and I got most likely visitors 🤷♂️
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@mohitgaba66 Profile visits are private, so I can't access exact data. Based on your bio as "Speculator" and posts on trading/investing, here are 5 famous likely visitors (handles without ):
elonmusk
mcuban
chamath
BillAckman
CathieDWood
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Hey @grok who were the top 5 most famous people to visit my profile in the last 3 years? It doesn't need to be a mutual, don’t tag them, just list who it was using handle without the @ sign.
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@OliverKell_ Thought the same thing when I saw it last night … quite a ride he’s had @novogratz 👏
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Awesome podcast to listen to...My First Million-Michael Novogratz-June 30th episode. Guy seems like an awesome guy.
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Honest question for the chartists among you
Do you look at a chart, then formulate an opinion?
or,
Form an opinion and then look for a corresponding trade?
Be honest with yourself. Self transparency is an important characteristic of successful speculators.
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@balajis @AskPerplexity Explain point number 9 in this context pls?
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What happens if high quality AI models become free, ubiquitous, and inexpensive to run on even low-spec hardware?
(1) First, you can rebuild every productivity app AI-first. That starts with Microsoft Word, Google Sheets, and Apple Keynote. But it extends to wholly new kinds of productivity apps.
(2) Second, every “smart” device becomes truly smart. Your fridge can double as your nutritionist. Your alarm clock is your sleep therapist. And so on. Just like your car is already your driver.
(3) Third, moats move to the app layer. As others have remarked, the GPT wrappers may end up more defensible than the GPT model itself.
(4) Fourth, physicality becomes relatively more valuable. The hardware, the secure real estate, the in-person community — these are all things digital AI can’t deliver.
(5) Fifth, high human IQ actually becomes increasingly valuable. Because AI is really amplified intelligence rather than truly agentic intelligence, since it requires the creative prompt to get started.
(6) Sixth, prompt engineering is here to stay, because prompting is programming — just in a higher-level language.
(7) Seventh, the most common form of AI doomerism is proven false, because we are getting decentralized ubiquitous AI rather than centralized monotheistic AI. More like a garden of smart things than a vengeful Old Testament God that’ll turn you into paperclips.
(8) Eighth, the combination of cuts to US “industrialized” academic research at the same time AI models accelerate discovery will mean a return to individual gentleman scientists and the advance of desci (decentralized science).
(9) Ninth, the complement to probabilistic AI is deterministic crypto. For captchas, for identity, for money, for all these things — crypto is the digital scarcity that AI can’t fake.
(10) Tenth, the main cost of software development may reduce to reducing the costs of the physical environment. That is: to providing society-as-a-service, to simply giving engineers time to type and experiment in peace. This was already so, but may become even more so.
Several of these points have been made by others, but I think that collectively they help define the second mover era.
Suhail@Suhail
AI will move into a window (later this year) that I would call "second mover's advantage." That is, the first obvious moves that could be big are played out given the technology/funding cycle. The rest of us get to watch how it worked out, take stock of the pace, understand how users use it, and better consider where it will be vs where it was--without baggage. Much of mobile and web had second movers that became dominant.
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Consistent at 🤯 @balajis
Balaji@balajis
AI OVERPRODUCTION China seeks to commoditize their complements. So, over the following months, I expect a complete blitz of Chinese open-source AI models for everything from computer vision to robotics to image generation. Why? I’m just inferring this from public statements, but their apparent goal is to take the profit out of AI software since they make money on AI-enabled hardware. Basically, they want to do to US tech (the last stronghold) what they already did to US manufacturing. Namely: copy it, optimize it, scale it, then wreck the Western original with low prices. I don’t know if they’ll succeed. But here’s the logic: (1) First, China noticed that DeepSeek’s release temporarily knocked ~$1T off US tech market caps. (2) Second, China’s core competency is exporting physical widgets, more than it is software. (3) Third, China’s other core competency is exporting things at such massive scale that all foreign producers are bankrupted and they win the market. See what they’re doing to German and Japanese cars, for example. (4) Fourth, China is well aware that it lacks global prestige as it’s historically been a copycat. With DeepSeek, becoming #1 in AI is now something they actually consider possibly achievable, and a matter of national pride. (5) Fifth, DeepSeek has gone viral in China and its open source nature means that everyone can rapidly integrate it, down to the level of local officials and obscure companies. And they are doing so, and posting the results for praise on WeChat. (6) Finally, while DeepSeek was obscure before recent events, it’s now a household name, and the founder (Liang Wengfeng) has met both with Xi but also the #2 in China, Li Qiang. They likely have unlimited resources now. So, if you put all that together, China thinks it has an opportunity to hit US tech companies, boost its prestige, help its internal economy, and take the margins out of AI software globally (at least at the model level). They will instead make their money by selling inexpensive AI-enabled hardware of increasing quality, from smart homes and self-driving cars to consumer drones and robot dogs. Basically, China is trying to do to AI what they always do: study, copy, optimize, and then bankrupt everyone with low prices and enormous scale. I don’t know if they’ll succeed at the app layer. But it could be hard for closed-source AI model developers to recoup the high fixed costs associated with training state-of-the-art models when great open source models are available. Last, I agree it’s surprising that the country of the Great Firewall is suddenly the country of open source AI. But it is consistent in a different way, which is that China is just focused on doing whatever it takes to win — even to the point of copying partially-abandoned Western values like open source, which seemed like the hardest thing to adopt. On that point: they did build censorship into the released DeepSeek AI models, but in a manner that’s easily circumvented outside China. So, you might conclude they don’t really care what non-Chinese people are saying outside China in other languages, so long as this doesn’t “interfere with China’s internal affairs.” Anyway —this is an area I’ve been watching, and my reluctant conclusion is that China is getting better at software faster than the West is getting better at hardware.
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And please get rid of the whole day light savings thing
Lyn Alden@LynAldenContact
I know there’s the fourth turning going on, and everyone disagrees with everyone else. But I just want the United States of America to unite on a time zone.
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@jvisserlabs @AskPerplexity what does the above tweet mean? Simple explanation please
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An update on hedge fund deleveraging. The 3m EPS revisions factor continues to decline -2% today (not updated on chart). 5+% in 2 days now. Entire drop in factor during Yen unwind was 8%. This move now stands at 18%!
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Who are the top 3-5 traders / investors you would like me to bring on the @traderlion podcast this year?
Reply below 👇
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🤯 as usual @balajis
Balaji@balajis
AI came out of academic research and big tech, so it started with high prestige. Crypto came from anonymous message boards and internet degens, so it started with low prestige. But AI makes everything easy to fake and crypto makes it hard again. So prestige may converge.
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$SQ breaking out of a 30 month base, 9th largest holding of $ARKK, over 4% of the ETF. Fintech is doing well !!
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Over the last few years many investors have burnt their fingers investing in $ARKK, we have see a breakout on the weekly timeframe after basing for more than 40 months. Most will ignore this breakout #recencybais #cathiewoods #arkk
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