20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

490.762 - 513.716 Arvind Narayanan

And that's actually the trend we've been seeing over the last year or so. As you know, you know, the models today have gotten somewhat smaller and cheaper than when GPT-4 initially came out, but with the same capability level. So I think that's probably going to continue. Are we going to see a GPT-5 that's as big a leap over GPT-4 as GPT-4 was over GPT-3? I'm frankly skeptical.