1. More efficient LLMs should lead to more usage, which means more AI chip demand. Jevon's Paradox.
2. To build a moat, OpenAI and American AI companies need to up their datacenter spending even more.
3. DeepSeek's breakthrough is in distilling models. You still need a ton of compute to train the foundational model to distill.
4. DeepSeek's conclusion in their paper says more compute is needed for next break through.
5. DeepSeek's model is trained on GPT4o/Sonnet outputs. Again, this reaffirms the fact that in order to take the next step, you need to continue to train better models. Better models will generate better data for next-gen models.
I think DeepSeek hurts OpenAI/Anthropic/Google/Microsoft. I think DeepSeek helps TSMC/Nvidia.