Matt Coleman
327 posts
Matt Coleman
@MattColeman7
It ain't what you don't know that gets you into trouble. It's what you know for sure that just ain't so.
Katılım Ocak 2012
265 Takip Edilen61 Takipçiler
This is how I like to post my charts, without any scale or labelling. Look at the growth!!
Tibo@thsottiaux
You know it's a good model when you grow more in 1 day than last two weeks combined. Install the desktop app from chatgpt.com/download/ and give it a go!
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@MattColeman7 When you're trying not to include confidential company numbers, doing charts like that is quite crucial.
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You know it's a good model when you grow more in 1 day than last two weeks combined.
Install the desktop app from chatgpt.com/download/ and give it a go!
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Matt Coleman retweetledi
This is what’s causing Anthropic to aggressively beg for govt protection (see below). Customers are finding cheaper alternatives. Keeping employees requires continuing ultra-rich secondaries ($$$) that are dependent on revenue growth. When you can’t win on the field go to DC.
Rohan Paul@rohanpaul_ai
UBS says 60% of companies now watching AI budgets are moving to cheaper models and open-source Chinese models The pressure is coming from extreme bills, including users spending up to $35K/month, teams exceeding quotas by 200%, and companies cutting internal AI tools from 5 to 2. Companies are not abandoning AI, they are using model routing, which sends easy tasks to cheaper models and saves premium models for hard reasoning, code, and long-context work. Chinese open-source models such as Qwen, DeepSeek, MiniMax, GLM, and Kimi now fit the enterprise cost curve because they can be run locally or used through cloud catalogs. --- news .futunn.com/en/post/75068082/ubs-group-finds-60-have-already-started-curbing-ai-spending?level=2&data_ticket=1780870170397383
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Matt Coleman retweetledi
DONT TELL ME GREENSPAN DYING MARKED THE TOP FOR IRRATIONAL EXUBERANCE CMON
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Matt Coleman retweetledi
Here's what's driving it. And it's the kind of number that only shows up at extremes.
Momentum stocks just went full tilt. The spread between momentum and low-volatility names hit a 5-standard-deviation overshoot above trend. The largest in the history of the series.
Five sigma is not "stretched." It's a once-in-a-generation reading. The only other times the line spiked anywhere close: March 2000. June 2008. February 2021.
Look at what followed each of those dates.
Momentum works until the moment everyone is crowded into the same trade. Then it becomes the fastest unwind in markets. The further it stretches from trend, the harder the snap back.
Thierry from arvy 🇨🇭@ThierryBorgeat
The most cyclical sector in the market is now its largest bet. Semiconductors are 22% of the S&P 500. Nearly a quarter of the most important index on earth, riding on the single most boom-and-bust industry there is. Chips are the definition of cyclical. They overbuild in good times, drown in inventory in bad ones, and the cycle has humbled every generation of investors who forgot it. For twenty years this sat near 3-5%. Now it's 22%, straight up, no pause. When the steadiest index in the world leans this hard on the most volatile sector, that's not diversification. That's a concentrated bet wearing an index's clothing.
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Matt Coleman retweetledi
FT: "Goldman Sachs analysts last month predicted that use of AI agents would result in a 24-fold increase in token consumption by 2030 and that the huge rise in demand would exacerbate a shortage of chips over the next 12 to 18 months. While token usage and AI spending by businesses continue to grow, efforts to curb costs could weigh on the growth of the world’s largest AI labs such as Anthropic and OpenAI, which plan to go public later this year at near-trillion-dollar valuations. Since the start of the year, Chinese AI models have overtaken their US counterparts in token consumption, according to data from OpenRouter, an aggregation platform that allows users to access multiple AI models. China’s cheaper energy and more efficient models have allowed the country’s AI labs to charge less than leading US groups for tokens, giving China a new edge on the AI battleground."
Again, I believe market participants are underestimating the pricing power challenges US hyperscalers face, both due to domestic and international competition. As I wrote in my December report on "GenAI & Productivity" (sageroadresearch.com/collections/re…):
"While there’s a lot of speculative fear about how a single LLM could rise to dominance and what that could mean for economic, societal, and political stability, we believe the bigger concern for investors today is how relative model parity could compromise pricing power. Tech giants have thrived on monopolies and duopolies for a decade or more. Now, they’re in an LLM arms race where it’s unclear when or even if ever leadership will be sustainable. We believe competition from akin models will apply downward pressure on pricing at least for the next three years."
Learn more about Sage Road Research here: sageroadresearch.com. Interested in subscribing? Message me.
FT link: ft.com/content/1d37cc…
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Matt Coleman retweetledi
EQUITY SUPPLY SHOCK
For 25 years, buybacks and cash-financed M&A have reduced the stock of publicly traded US equity almost every year. That structural tailwind is about to reverse. SpaceX, Alphabet, Meta, OpenAI, Anthropic - five companies that could raise ~$400bn between them. More than twice the total equity issued across the whole market in most years. Net supply will flip from negative to strongly positive.
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The change in Elon’s net worth today was more than Buffett’s entire net worth. Think about that.
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Matt Coleman retweetledi
The clearest 11 minutes I have heard on why the AI capex boom may not pay off. @ChrisBloomstran at the Zurich Project on the depreciation wall, ~$650B of off-balance-sheet SPV debt, and the circular financing between Nvidia, OpenAI, and the hyperscalers.
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How can they build these estimates with a straight face? Not happening.
Robert Armstrong@rbrtrmstrng
Wall Street consensus estimates for hyperscaler free cash flow. Provides a good snapshot of where the market's head is at, I think:
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Matt Coleman retweetledi
Matt Coleman retweetledi
@AnthropicAI And just like that we collectively saw the future of inequality
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Matt Coleman retweetledi
Very interesting and scary report from Morgan Stanley
The financial engineering behind hyperscaler capex
The truly unsettling part of the AI boom isn’t how much money is being spent
It’s how that money is being engineered through accounting
Hidden liabilities (> $1.8T)
Huge obligations sit off‑balance‑sheet: nearly $1T in purchase commitments, $800B+ in leases not yet started, $2T+ in RPO.
Future cash outflows that don’t show up as debt.
The coming depreciation hit
Profits look good only because spending is stuck in CIP.
Big Tech faces $520B+ in depreciation over 3 years.
ORCL’s depreciation ratio: 7% → 28%.
Supplier financing pressure
Unpaid capex is ~$110B.
ORCL’s DPO exploded from 35 → 170 days.
The whole supply chain is effectively financing the AI build‑out.
Lease accounting gray zones
Whether GPU contracts count as leases or services is subjective — and companies use that flexibility to shift billions on/off the balance sheet.
$ORCL = the most aggressive
Largest lease commitments, RPO up 300%+, capex‑to‑sales hitting 189%.
Oracle is running the highest financial leverage in the ecosystem.
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@SemiAnalysis_ This is bearish for both OpenAI & Anthropic. Either they continue to deeply subsidize with VC dollars or they die.
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Recently, we purchased one of each Anthropic/OpenAI subscription plan and randomly ran long horizon coding tasks until we exhausted the weekly limit. It's widely believed that a $200/month plan maxes out at ~$2000/month worth of tokens (assuming API pricing). However, we found that the subscriptions are actually far more generous. (2/4)
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What's the better business model for an AI lab, subscription or API? (1/4)🧵
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Matt Coleman retweetledi
