The TWIML AI Podcast · Monday, July 27, 2026
Damian Borth describes weight space learning as a promising direction for machine learning, aiming to solve current challenges faced by the AI community. This approach views trained model weights not just as an output, but as a new input modality for further learning and analysis.
“I think is a really interesting way forward, solve a couple of problems that the community currently encounters.”
“And, you know, we get some utility out of them. We may use them for things like explainability or manipulate them when we're quantizing or something like that. But the, the idea seems to be that, you know, there's so much more that we can learn from these weights.”