Grok 3: Another win for the bitter lesson

Did they? Deepseek spent about 17 months achieving SOTA results with a significantly smaller budget. While xAI's model isn't a substantial leap beyond Deepseek R1, it utilizes 100 times more compute.

If you had $3 billion, xAI would choose to invest $2.5 billion in GPUs and $0.5 billion in talent. Deepseek, would invest $1 billion in GPUs and $2 billion in talent.

I would argue that the latter approach (Deepseek's) is more scalable. It's extremely difficult to increase compute by 100 times, but with sufficient investment in talent, achieving a 10x increase in compute is more feasible.

We don't actually know how much money DeepSeek spent or how much compute they used. The numbers being thrown around are suspect, the paper they published didn't reveal the costs of all models nor the R&D cost it took to develop them.

In any AI R&D operation the bulk of the compute goes on doing experiments, not on the final training run for whatever models they choose to make available.

One thing I (intuitively) don't doubt - that they spent less money for developing R1 than OpenAI spent on marketing, lobbying and management compensation.

What makes you say that? Do you think Chinese top tier talent is cheap?

What is cheap? But compared to the US, yes. Almost everywhere talent is 'cheap' compared to the US unless they move to the US.