cl42

What I'd really want to see is revenue and profit per employee over time tracked against token usage/spend, and not limited to the S&P 493.

Apollo's own argument that most AI spend is coming from non-S&P 493 (as per the last two charts) tells me it's hard to make any conclusions based on these charts.

Bloomberg[1] has a breakdown based on ASML filings. For Q2, Japan, South Korea, and Taiwan made up 77% of ASML's orders, with China representing another 14%. Given China is on the list, I imagine this includes non-EUV tech as well given the sanctions.

The fact that Europe has incredibly limited frontier chip making capability is the issue, though. Even if they can produce other chips, its position is not at all resilient.

[1] https://www.bloomberg.com/news/articles/2026-09-22/asml-exec...

Thanks, that makes sense. I wasn't sure why The Economist would make this distinction, though I can see why certain companies (e.g., 'poorer' non-hyperscalers) might opt for cheap/loud options.

Given your experience with data centers, what do you think of this quote from the article?

> In any case, even the noise worry is overstated: many viral videos of supposed AI data centre noise are really Bitcoin mines, not state-of-the-art hyperscaler facilities.

Are there really major differences between a hyperscaler, neocloud, and crypto mining data center in terms of noise pollution or other negative effects?

I'm a founder who went through YC (S12), raised VC funding, etc. Now working on other businesses. I also know a few other founders who raised tons of VC funding on their first go, some who have succeeded and some who shut down.

Anecdotally, I feel like the second-time founders see VC as a very specific tool and many prefer not to raise... They'd rather bootstrap and scale more slowly, retaining control, freedom, and flexibility. Granted, a lot of founders also have bad experiences with VCs.

I think your framing VC as a tool is the right one. Not sure if first-time founders are still like this, but ~15 years ago, it seemed like raising VC funding was validation in and of itself and you were perceived as successful due to the raise. The second-time folks know this is neither validation of your product nor is it any sort of guarantee of success... If you need to raise lots of money to capture a speculative market or build something that won't see revenue for a while, VC is great. If you want to build a decent business that grows 20% to 30% per year and compounds over decades, then maybe it's not for you.

Finally, VC is a broad category. Raising money from former founders or from strategic VCs who can legitimately mentor you is very different than getting a check from a fund that makes 100s of investments per year and simply manages you as an arms length portfolio entry.

I recently read a few articles about how the harness is a bigger factor to successful LLM usage and wish they discussed this here.

I use GLM-5.3, Qwen3.8, Claude (all of 'em), GPT Sol/Luna/Terra across direct API calls + local models where I can (128GB Macbook Pro)... The harness and whether the model or underlying system prompts know how to make the best use of iterative LLM calls makes such a big difference...

For example: one-off articles on a news topic (e.g., "Update me on the US-Canada relations") yields very similar results across all models... But "run a web search, write a draft perspective from three points of view, and structure data around it" will make everything but Claude + GPT struggle.

Meta is also one of Microsoft's largest AI customers.

https://www.bloomberg.com/news/articles/2026-08-20/meta-has-...

> Citadel has sold more than 80 per cent of the portfolio it took on from buying the majority of Situational Awareness’s stock bets last month after the AI-focused hedge fund was almost toppled by the recent tech sell-off.

...

> “Over our nearly thirty-six-year history, we have prided ourselves on being front-footed and proactive during periods of market dislocation,” Griffin wrote. The firm’s flagship fund was up 6 per cent in July, while many of its rivals lost money or were relatively flat.

I see. Well, feel free to disagree with my insights and ideas; it makes us all better for it.

But refrain from unfounded allegations of AI slop or incompetence. Gatekeeping is even worse.

EDIT: you keep editing your comments. I'm going to stop engaging with you since one can't even have a linear discussion. Good luck with your research and ideas. If you are an expert on Japan, I encourage you to share your views in the general comments here.

Author here. Everything is written by me, by hand. What makes you think it's AI slop?

I see you edited your comment. Yes, we use LLMs to monitor news --- otherwise we wouldn't be able to read Japanese news sites or policy documents. However, the articles and analysis are written "manually". I take this very seriously --- the only "AI" is spelling + grammar checking.

This goes into the details of the mechanics of what an intervention entails---who does what, why, etc.

I'd be more concerned about private credit socializing losses and being bailed out, than bad AI loans leading to private credit problems which then lead to the bailout.

Private credit has a million other problems right now, like bad loans to auto parts dealers[1], iron traders[2], and so many more.

The issue is lack of due process in private credit. THAT is the huge @#$%ing problem.

[1] https://www.bloomberg.com/news/articles/2026-07-28/first-bra...

[2] https://www.bloomberg.com/news/articles/2026-07-31/vitol-car...

I generally agree with you but given your comments, you might enjoy some additional details... Or please challenge me if you think I am wrong.

I've been paying for order-level data feeds on stocks and one thing you'll find is that a lot of the 'sensitive' trades will be anonymized or broken down in different ways to obfuscate who is trading. Citadel would still be able to see there's a surprising level of interest in a certain stock but might not be able to deduce it's one actor. A broker working for SA should know they need to do this, as it helps the broker do better via commissions, etc. too.

My understanding is that Citadel negotiated directly with SA to buy the book, so the final trades were likely taking place outside of the formal market feeds.

Author here. There is absolutely no AI used in any of the writing I do. We use AI to track news and better understand global and economic developments.

You'll have to clarify -- do you mean the fund, or our hypothesis on reflexivity and the value of AI assets?

LTCM didn't crash the global economy thanks to a bailout orchestrated by the US government. If anything even close to this is currently happening with Situational Awareness, then we're either about to crash hard or realize that AI is too big to fail.