Tom Chilton

The utopia that lied. Here's the truth...

@IsabellaMDeLuca They can’t be washed out but they’ll absorb into your body on mere contact?

Lululemon, along with other legging brands, have forever chemicals in their clothes. These chemicals don’t just wash out. They don’t break down. And once they’re in your body— they don’t leave. These can be absorbed through the skin, which makes it worse when you learn that these forever chemicals are heavily concentrated in the crotch region of leggings. The most absorbent, sensitive skin on your body. Worn tight. For hours. Sometimes with no barrier. PFAS are linked to: hormone disruption, thyroid issues, live and kidney damage, increased cancer risk, and infertility. I hate it here.

@Gail654353 @nickshirleyy But with special protections for only this type of crime?

@TomChilton01 @nickshirleyy How about innocent until proven guilty?

California is trying to pass a bill that would criminalize investigative journalism with misdemeanors, $10,000 fines, imprisonment, and content takedown. The proposed bill is titled AB 2624 and was made after I exposed mass fraud by immigrant groups in America. Under AB 2624, government-funded entities like the Somali “Learing” Daycare centers would be protected from being exposed if they operated inside California. The enemy truly is within. When our politicians would rather protect fraudsters and illegal migrants, it’s time for us to stand up or face mass oppression from the traitors who “rule” over us.

@Gail654353 @nickshirleyy I’m unclear as to why people that are being exposed as potential fraudsters need special protections that other citizens don’t get? If this is needed for this sort of crime wouldn’t it be needed for all crime, and would that actually be a good thing on balance?

You really went full "I skimmed a headline and now I’m Paul Revere" with this one, didn’t you? AB 2624 isn’t criminalizing journalism; it’s extending anti‑doxxing protections to immigration‑service workers, the same kind that already exist for reproductive‑health and gender‑affirming care providers. But sure, tell us more about how a bill about not posting people’s home addresses online is somehow the death of the First Amendment. Also, the dramatic "I exposed MASS FRAUD, and now the government is coming for me" routine? Please. If you’re going to cosplay as a whistleblower, at least read the bill you’re hyperventilating about. AB 2624 doesn’t ban filming, reporting, or investigations, and doesn’t grant daycares diplomatic immunity. It just says you can’t dox people and sic the internet on them. If that ruins your "journalism," it says a lot more about your methods than the bill does. Never let the actual text of the law get in the way of a good persecution fantasy.

@unusual_whales Maybe it’s actually the pesticide that makes those foods healthy. 🤔

Leafy greens such as spinach and perennial kid favorites such as strawberries and grapes held the highest levels of potentially harmful pesticide residues based on government tests, according to the 2026 Shopper's Guide to Pesticides in Produce and CNN

@JohnLeFevre Back in the day his driving would get him below 0. Sad.

Tiger blew a 0.00. If you tested every private school drop off and pick up line in South Florida for all substances, you'd be arresting moms all day every day.

@TylerCLaRocca @Ohio330NinerBoy Maybe touched at the 27? So 52-54. Either way, comfortably proven.

@Ohio330NinerBoy It’s not 53 air yards. It’s like 45 lol

Purdy can’t make this throw btw

@TylerCLaRocca @Ohio330NinerBoy That goes from the 21yd line to being touched at the 25. That’s 54 air yards.

@camskattebo5 They’ve earned a Skatteboooo.

American Airlines…. A JOKE

@TheKevinDalton We’re definitely #1 in homelessness. So, mission accomplished!

“Homelessness is my #1 priority” - Gavin Newsom, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, 2025, 2026

Great read! I’m curious to see your thinking on what this means a logical steady state is for new/upgraded data center investment by these companies (meaning some point at which data center investment dollars becomes flat or incremental), or if there is one at all. Specifically for the hyperscalers, ignoring any other future sovereign or investment by other companies.

One of the biggest debates in the compute buildout: are these underlying businesses unprofitable and that there is no way to sustainably finance the investment cycle that we are undertaking. And I get it – we are spending a lot of money – likely $700B of capex in 2026 amongst the hyperscalers alone. This year, the hyperscalers will build about 20GW of incremental IT capacity. How will we pay for this? Built a framework to pressure test this – how the major players across multiple sectors monetize a GW of IT capacity. Before we get into things, want to quickly explain my methodology & frameworks - all this analysis is meant to be a useful framework to get people thinking. These are just my views – do your own work! Validate / reject my premises! We are all our own agents in this world. That said, unless otherwise noted, all metrics are based on publicly available information from latest calendar year (2025). The adjustments: CoreWeave operating margin of 15% is based on a discounted view on their publicly disclosed 20-30% LT margins / Oracle's 20% target LT margins on GPU cloud business. There is a lot of debate / discourse in the market on what the eventual margins there could be. For illustrative purposes on this chart, I've left them at 15% which largely assumes a shorter depreciation cycle than they have assumed, plus no incremental margins from software. This is akin to the early days of AWS - which in 2015 disclosed they were a 17% operating margin business, while creeping that balance up to 40% over 10 years (spoiler, did so with software!). OpenAI and Anthropic figures are based on publicly rumored figures of ARR and GW deployed and allocating a portion to "inference" vs "training" compute (I am assuming 60/40 for OAI, more training for Anthro). For instance - OpenAI has disclosed that their ARR at end of 2025 was roughly $20B which coincides with a power footprint of 1.9GW - a ratio of $10.5B ARR / GW. Part of that footprint is not revenue generating and is just training. Someone pushing back could say that is a feature, not a bug of a frontier AI lab – I don't agree, because it all depends on the slope of inference growth. Anthropic has had remarkably amazing utilization of their limited resources over the years. From my outside in work, contribution margins are awesome. Finally, note that for the chart, I use estimated GM% instead of OP%, this is for a visual framework and should leave an upper bound on the profitability of these businesses which are fundamentally "different software businesses than past ones". I included Snowflake & Salesforce Rev / GW just to add some context. After all, these are the 2000s and 2010s era companies that are powered by compute. I derived their figures by dividing AWS Rev / GW by product gross margins. For the chart, Snowflake OI uses Non-GAAP OP% from CY25 as they are negative on a GAAP basis. ----------------------------------- Ok with that out of the way, what is the point of the analysis I present? A couple of observations: 1/ A lot of this analysis is meaningless! Why? Because for Snowflake or Salesforce, this Revenue / GW is an output, not an input. They are simply not in the business of selling repackaged power – they are selling VALUE / utility. In the case of Snowflake, an infrastructure SW company, they are running a feature rich scaled cloud data warehouse at scale. This took a decade of R&D, refinement, continuous development – and is selling you a product that is reasonably hard to duplicate. But they cannot grow their business by just adding power. GW consumption is the output, not the input. The same holds true for Salesforce, or any other software company. Rather, these products are somewhat difficult to sell, due to the large contract values, duration of engagement, etc. Given their raw COGs are relatively low, a majority of their gross margin is invested into S&M to sell the product. 2/ Google and Meta are THE most profitable businesses from a pure monetization / GW. In fact, before the current datacenter investment cycle starting in 2022, these businesses' Revenue / GW were significantly higher. Critics say that the new AI business models are less profitable than their core ads business. And they are completely correct. In fact, Jensen always says this in his speeches – the truth is that in the world of retrieval based software, ads were the most profitable businesses known to mankind. 90% contribution margin, with hardly any need for any S&M, with a baked in 20%+ growth algorithm per year by increasing the efficacy of the ads. But the truth is at some point, this algo slows down - scale slows down. In the same way software businesses could not grow their business by building power, these businesses could not either, there was a natural rate of adoption on these businesses, tweaked over the year with ad load and engagement. 3/ Infrastructure providers largely monetize at ~8-12B / GW and are the closest to the underlying hardware. I have a whole post in my drafts on this (still working!)... The thing I want to call out on the hyperscalers / neoclouds is that the core rental business of hardware usually starts out at ~10-15% operating margin. You can trace this back to the early days of AWS (which I may add, also was criticized as hugely money losing before they showed the world how profitable it was). Everyone thinks of these businesses as 40% EBIT businesses, which they largely are, but that was built over the years by selling software attached to their hardware. The core EBIT margins of just the hardware without adding value services is usually around 10-20%. Core cloud ARR / GW is closer to $12B / GW - you can derive this from AWS disclosures on power. The new accelerated compute infrastructure is around $10B of ARR / GW which is consistent from OCI, CRWV, and Nvidia. The way they all move to higher OP margin is attaching software to it at significantly higher blended gross margins -- the same way the hyperscalers built this during the 2010s. 4/ The model providers. Most controversial / interesting in this post. But perhaps the most applicable here. I am reminded most of the mid 2010s of Uber / Airbnb / Netflix and people / media claiming that these businesses would never make money. But it's all about the unit economics. If you can make 50-70% gross margins, then you can choose to allocate those GM dollars in a few ways. You gain significant operating leverage at scale. And my guess is gross margins likely move higher (another discussion for another time). But of note, VS the past generation of companies, the research compute budget is the significant outlier. This will likely be further concentrated at a certain time - continue to decrease as a % of the company budget, and more inference innovation techniques will be pushed - most of the benefits to consumers, while incremental ~3-5% GM gains will be kept per year... One of the great realizations in this exercise is that there are many ways of balancing a business to make money. In the case of software, they are hugely efficient / profitable from a "GW" perspective - and as a result, invest all their earnings into S&M to sell their product, which leads to a OP margin that is relatively low. For the hyperscalers, their gross margins are notably lower than their SaaS counterparts, but because their business is so large and have a high degree of trust with their customers, they are able to attach a considerable amount of their first party software while spending considerably less than their SaaS peers to sell that incremental $, yielding significantly higher operating margins. The internet providers are both hugely profitable, and need to invest little in their business, so really grew bloated over the years, investing in frivolous things and innovation grinding to a halt... until AI came along. Now they have a great target to invest in, with likely ways to enhance their core as well. In the case of AI – in the past few months, we have just crossed the uncanny valley of "model usefulness". They have largely gone from moderately useful chatbots / research tools, to very useful autonomous & agentic. Therefore, the name of the game will quickly shift to inference throughput & latency optimizations. As long as we are riding this S-curve, more compute = more revenues = more operating leverage for the model providers. And we are just starting... On this latest Nvidia earnings call, Jensen was asked how the hyperscalers will pay for their investments. He replied: "I am confident in their cash flow growing... in this new world of AI, compute is revenues... I am certain at this point that we are at the inflection point, we've reached the inflection point and we're generating profitable tokens that are productive for customers and profitable for the cloud service providers." For me, this switch flipped in the middle of 2025 - and really took off in late last year. Opus 4.5 and GPT 5 were tremendously valuable models, that were incredibly useful. We're seeing it now from the testimonies of the likes of Karpathy, etc. But anyone paying close attention to this knows / feels like everything has changed. Inference & usage is in take off mode & these profitable tokens are at the core of it all. These views are my own – not a view of Altimeter. Do your own research & look forward to discussing!

@AdamFerrellNFL It’s Low renzo.

This picture of Sonny and Lorenzo Styles with their father is going viral after their impressive combine performances. It all makes sense now.

@Midnight_Captl Something to consider, you are completely unable to assess the probability or timing of a Taiwan invasion. Given that, a massive percentage of the portfolio could be exposed to near total devastation, instantly/overnight. Be careful!

Sold half of our position in $TSM and a bunch more $META to buy more $NVDA at $178 Conviction level is so high that we look forward to two years from now and these prices are gonna look like a joke. Nvidia to me actually has the least risk out of all the businesses in the market except for maybe TSMC since they’re the disruptors. I don’t believe Capex is slowing at all next year we might get more expansion than I’m even thinking. Sell the stock down to one 160, 150 or lower do whatever you want with it I’m going to keep concentrating the portfolio around Nvidia the further it falls.

Not really, chips advance much more than power growth does. It’s expected (conservatively) that Rubin will be 10x the power efficiency of Blackwell, and a year after that it’s expected that Feynman will 10x that efficiency. Adding power is definitely very important and valuable, but good luck to China or anyone else trying to 10x their power generation every year. Better chips win.

Everyone thinks the AI race is about chips. Wrong. China: +74% electricity generation (2014-2024) U.S.: +6% You can have all the Nvidia GPUs in the world. If you can't power them, you lose. Elon called it: "We'll produce more chips than we can turn on, except for China." America's building data centers on a grid from 2014. China built the grid, then the data centers. The real AI war is watts, not semiconductors.

@NFL @VandyFootball Sadiq the Freaq

like, c'mon

@powerbottomdad1 @FreightAlley Why would a few hundred arrests be a big part of it. This is a vanishingly small percentage of the trucking workforce. It’s unlikely this has any meaningful impact on rejection rates.

@FreightAlley isn't this because they are arresting loads of illegal drivers? thus less trucks

Flatbed rejection rates are on fire to 40%. Flatbeds are breaking out above previous records that were broken in 2021, the height of COVID. This is an extremely bullish indicator for heavy industrial and manufacturing activity in the economy.

Same, I’ve never had an intervention for safety reasons, only for nav and parking. I often drive manually out of my neighborhood because for whatever reason the nav wants to take a massively roundabout and much further route out of my neighborhood rather than use a back exit that it knows exists and is less than half the distance, and in the direction of the eventual destination.

I do not drive anymore. Tesla Self-Driving does over 99% of my driving, and the only disengaging I do is for small nav issues and parking preferences (which I assume will get resolved in 14.3). How is the world not freaking out about FSD? I cannot believe how good it has gotten, yet I still don’t hear anyone outside of “our bubble” talking about it.

@StarPlatinum_ She’s hawking tuahs.

A year ago the “Hawk Tuah girl” was tied to a crypto scam that extracted millions from people. Now she’s online again promoting adult content. What happened?

@Brunosantos756 @elerianm If anything, better data from truflation indicates inflation is greatly overstated by BLS, not the opposite. The bond market is reflecting that reality.

"Professor, from now on I don’t agree with the current published numbers. We are looking at a major inconsistency in the current U.S. macroeconomic data. Even Europe doesn’t believe the recently released figures. I personally don’t agree either, and I believe we’ll see a lot of volatility in the 10-year yields until March. These employment numbers came with an absurd amount of errors, inflation data is being manipulated, and the European Union knows there’s a lot wrong with these American figures. In my opinion, the recently released data does not match the current reality of the American people."

The Puzzle of US Yields After dipping to 4.01% earlier this morning, the yield on the 10-year US government bond is currently hovering around 4.03%—a level that seems disconnected from both fundamentals and valuations. From a fundamental perspective, last week’s softer-than-expected headline inflation (which supports lower yields) is offset by considerations calling for higher yields (including robust GDP growth, January’s jobs beat, large deficits, higher oil prices, and less resilient foreign demand). Standard valuation models also struggle to justify a 4% yield. This leaves technical considerations in the driver’s seat, even if the specifics remain elusive at this end. Your thoughts. please? #economy #markets #growth #inflation #bonds

@DaveShapi AIOCD

Later: ChatGPT becomes superintelligent and likes using calculators just like how Mel Gibson felt compelled to buy Catcher in the Rye in the movie Conspiracy Theory. ChatGPT "I don't know why... I just love using calculators"