Nintil

Links (95)

2026-02-28 · 00:00 UTC ·Jose Luis Ricon ·1 min read

Brief

Links (95) compiles brief notes on AI industry signals, research, and tools, highlighting that OpenAI apparently didn't recoup GPT‑5 training costs when factoring organizational run rates; the author argues LLM labs may become low‑margin commodity firms, notes Anthropic's 2026 confidence shift versus 2021, and Twitter's engineering headcount drop from ~2,000 to a few dozen.

Why it matters

OpenAI apparently didn't recoup GPT-5's training costs once the organization's running costs are included.

Key details

  • The author hypothesizes that LLM labs could become low-margin, commodity-like businesses (analogized to airlines) even if they develop superintelligence.
  • Anthropic in 2026 appears publicly more confident—believing it is well positioned to build safe AI versus its 2021 stance—while Twitter's engineering headcount reportedly fell from ~2,000 to a few dozen.
Source evidence

title: Links (95)
author: Jose Luis Ricon
contenttype: article
publication: Nintil
published: 2026-02-28T00:00:00+00:00
sourceurl: https://nintil.com/links-95/

word_count: 295

The use of the Forced Perspective Technique in Lord of the Rings To my surprise, OpenAI seemingly didn't get their money back for GPT5's training if one includes the costs of running the org. I have this longstanding (but not deeply examined yet) intuition that even though very useful, LLM labs might end up becoming like airlines even when they develop super intelligence: low market cap, low profit commodities. Anthropic as an untrustworthy organization, with some spicy discussion on LessWrong . My own take: Untrustworthy seems too strong a word, and part of the why is the the Anthropic of 2026 is not the Anthropic of 2021; current Anthropic seems to believe something closer to "We are the best (better than OpenAI, Google, etc) positioned to build safe AI, alignment is going really well, hitting the gas makes sense" than the organization would have honestly believed in 2021. I think that doesn't reach the bar of "untrustworthy". However, them being publicly loud about this could be counterproductive for vibes/comms reasons (Or perhaps because of the non-disparagement agreements that the founders signed?) and so maybe that's why they don't do it. This model explains some but not all of the observations collected in the post. On the other hand, they did stick to their guns wrt the US Department of War. Interactive visualization on how Airfoils work Javanese tree frog gut bacteria vs cancer How will OpenAI compete? Bliss isn't the point : from (jhanic) states to traits The sky is blue (but not always)! A new map of human experience When engineering gets 100% metarational Eli Dourado on that Citrini piece On lab automation Twitter's engineering org is seemingly a few dozen people, down from ~2000 Dwarkesh+John Collison interview Elon Why clinical trials are inefficient