25th April 2024
I’ve been at OpenAI for almost a year now. In that time, I’ve trained a lot of generative models. [...] It’s becoming awfully clear to me that these models are truly approximating their datasets to an incredible degree. [...] What this manifests as is – trained on the same dataset for long enough, pretty much every model with enough weights and training time converges to the same point. [...] This is a surprising observation! It implies that model behavior is not determined by architecture, hyperparameters, or optimizer choices. It’s determined by your dataset, nothing else. Everything else is a means to an end in efficiently delivery compute to approximating that dataset.
Recent articles
- Initial impressions of Claude Fable 5 - 9th June 2026
- Running Python code in a sandbox with MicroPython and WASM - 6th June 2026
- Claude Opus 4.8: "a modest but tangible improvement" - 28th May 2026