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

2638.802 - 2660.337 Arvind Narayanan

And what we've seen in the nearly year and a half since GPD 4 came out is that we haven't really had models that have surpassed it in a meaningful way. And this is not based on benchmarks. Again, I think benchmarks are not that useful. It's more based on vibes. When you get people using these things, what do they say? I don't think models have really qualitatively improved on GPT-4.