I do think that if China cannot get a 100s, H 100s top the line hardware like GPUs with good interconnect to train models, they will invest heavily in solving that problem. And so there is a piece of me that feels that some of the regulatory attempts to control model development are misguided. I think separately from that, there's another interesting vein that you and I have talked about where like you're trying to figure out how to make more heterogeneous compute work for both inference and training. That could be companies like Together or Foundry or even at the sort of compiler layer, like HIPAA.
This week on No Priors, Sarah and Elad do another hangout to answer listener questions. Topics include debunking common misconceptions about AI and its implications on the world, the analogy to nuclear power and nuclear safety, the impact of larger context windows, developer productivity, incumbent announcements of AI products, and some requests for (fat) startups.
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Show Notes:
[00:21] - What Are People Getting Wrong About AI Right Now? / New Capabilities of NLP
[04:35] - Nuclear Power and Safety Concerns
[11:12] - Emerging AI Companies and Research
[15:54] - China's Hardware Sanctions and Funding Ramp
[20:34] - Innovation in Heterogeneous Compute Infrastructure
[28:08] - Enterprise Stack and Decision Making
[33:44] - Data's Impact on the World