Thread

1. lubujackson · 1789675061 · focus · HN ↗

   Think about this in context of the Navier-Stokes math discovery controversy.

   Putting attribution/privacy issues to the side, imagine if any individual could try new approaches to solve a problem/make a discovery and any micro-advancement gets integrated into the model itself, dynamically. This could transform progress from the slow "write a paper, get peer reviewed and published, use published data to inform future work" to a system with a centralized repository of concepts, attempts and results, including failed approaches already tried. How much work do humans waste replicating failed approaches?

   Someone completely random halfway around the world could trigger a prompt that solves a blocker that prevents my solution from working. Who cares about AGI or "can models invent anything" when we could have a system that automatically synthesizes individual human thought into a rich network of aggregate human memory.

   That's the target OpenAI/Anthropic should be evangelizing, not an AI Daddy Overlord or agentic script kiddie hellscape.

   1. robotresearcher · 1789693291 · focus · HN ↗

      From a quick look at the paper it seems they are showing how to update weights online via projection through a smaller matrix like a dynamic version of LoRA. That's weights changing, and not the architecture or training approach. Weights aren't the currency of research, they are the currency of a training run. This paper itself adds an architectural extension.

      1. paidx · 1789693488 · focus · HN ↗

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