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

1595.976 - 1616.868 Arvind Narayanan

So I don't know is the short answer. But at the same time, you know, we've been in this kind of historically interesting period where a lot of progress has come from building bigger and bigger models that need not continue in the future. It might. Or what might happen is that the models themselves get commoditized and a lot of the interesting development happens in a layer above the models.