Unlike the other models used, Kimi K2 Thinking is freely available. The other models, Gemini 2.5 Pro and GPT-5 Extended Thinking, are only available through a $20 monthly subscription. So overall, Kimi K2 seems like a pretty big deal to me. (I didn’t test GPT-5 Pro, since it costs $200 per month)

Sometimes the LLMs gave wrong equilibria, sometimes they wrongly claimed that there were no new equilibria at all. The inconsistency across all three models is annoying, but that’s just part of working with LLMs, I suppose 🤷‍♂️

The paper is on algorithmic game theory, where I modify existing games in a specific way and examine whether new equilibrium outcomes emerge under the modified framework. I provided each model with a simple numerical example and asked whether new equilibrium outcomes arise.

These results are somewhat at odds with the mistakes Gpt and Gemini keep making when working on my proofs. I have the $20 subscription though, could that be the reason?

Wohl nicht. Any suggestions?

Income Effect: Analyst become more productive -> hire more

Substitution Effect: Fewer analysts are needed per project -> hire less.

Both effects exist, it’s TBD which dominates.

If a job is fully automated (AI can do all tasks), employment should def. fall (think Waymo replacing Uber drivers).

I think it does help! AI today mainly augments labor: AI substitutes some tasks that analysts do, but not all. Analysts are more productive now. Does their employment rise? Depends on Income vs. Substitution effects:

Want to dig deeper? This is a short summary of a paper by Phil Trammell and Anton Korinek: (www.nber.org/papers/w31815). I recently had the pleasure of taking Phil’s course on Transformative AI at Stanford DEL!

• Unlocking robots: AI-led breakthroughs might also unlock humanoid robots, bringing explosive growth via the substitution channel described in 1)