A good friend of mine is deep in the world of startups and spends a lot of his time doing idea validation—that is, trying to understand if there is a market for a given idea or product. Despite the fact that in the startup world success is eventually judged by sales or profits, whereas in ML4H it is more likely to be adoption by clinicians and, hopefully, an associated improvement in clinical outcomes, both rely on designing something that people actually want and will use. Therefore, I think many of the tools that help entrepreneurs validate ideas can be repurposed to help researchers undertake projects with real impact.

Weapons smuggled from Florida are empowering the country’s militias and enabling them to challenge a fragile government

LLM decoding is bottlenecked for large batches and long contexts by loading the key-value (KV) cache from high-bandwidth memory, which inflates per-token latency, while the sequential nature of decodi...

Aurora, a new large-scale foundation model trained on more than one million hours of diverse geophysical data, outperforms operational forecasts in predicting air quality, ocean wave dynamics, tropica...

xAI's was happy to put "white genocide" stuff back into Grok's system prompt without second thought.