Infinite-Parameter LLMs: Generating and Adapting Weights from Live Data
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Infinite-Parameter LLMs: Generating and Adapting Weights from Live Data
Unofficial Hacker News client; not affiliated with Y Combinator.
lubujackson · · focus · HN ↗
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.
Retr0id · · focus · HN ↗
unrented7977 · · focus · HN ↗
You'd want an enormous vector database at minimum. Text is just completely wrong for models at this scale, you must work in the latent space directly.
alightsoul · · focus · HN ↗
Every existing text web server can voluntarily offer a vector version of their website and charge for it or inject advertisements onto their content so the ai labs don't have to do it all themselves as model pretraining off a dataset. The vector version can have many links to other websites in the knowledge graph. This would be decentralized so not a monopoly and everyone not just ai labs would contribute to ai development because the dataset would be open because it would come from the internet itself as it already is (except for synthetic or user data).