Image created with gemini-3.1-flash-image-preview with claude-opus-4.7. Image prompt: Using the provided reference image, keep the pure white landscape field, exact vertical type hierarchy, galaxy-punchout Milky Way texture inside every letterform, and identical font pairing and tracking, but replace ‘HEROES’ with ‘SCIENCE’ in the same bold condensed grotesque, replace ‘ALESSO’ with ‘TRUTH ENGINE’ in the same light geometric all-caps, and replace ‘TOVE LO’ with ‘ALPHAFOLD’ in the same condensed grotesque, keeping ‘(we could be)’ and ‘FEATURING.’ unchanged.
Making ChatGPT better for clinicians | OpenAI
https://openai.com/index/making-chatgpt-better-for-clinicians/
I’m lucky enough to have a great doctor and access to excellent Bay Area medical care. I’ve taken lots of standard screening tests over the years and have tried lots of “”health tech”” devices and tools. With all this said, by far the most useful preventative medical advice that
https://x.com/patrickc/status/2045164908912968060
We built an AI system that discovers health biomarkers from wearable data. One of its first findings: “”late-night doomscrolling”” is a statistically validated predictor of depression severity (ρ = 0.177, p < 0.001, n = 7,497). The AI named the feature. No human guidance.
https://x.com/SRSchmidgall/status/2045023895041061353
🚨🚨New Paper: Generative Insight Anticipation from Scientific Literature Human scientists achieve breakthroughs by “”standing on the shoulders of giants,”” synthesizing profound insights from disparate sources. While LMs show promise in scientific discovery, they currently
https://x.com/Anikait_Singh_/status/2045149764636094839
Our paper landed in Nature Health today! Healthcare is one of the most high-stakes, high-potential applications of AI. So we set out to understand how people actually use it in our AI products today.
https://x.com/mustafasuleyman/status/2044817893460996487
Scientists often make breakthroughs by synthesizing ideas across papers. In our new paper, we ask whether a language model can anticipate this process: given two parent papers, can it generate the core insight of a future paper built on them? 🧵⬇️
https://x.com/JoyHeYueya/status/2045147082546462860
This paper shows people are asking a lot of medical questions of AI already, but we have little evidence of how good or bad this is. Most of the published research uses old models & compares to doctors. How do new models compare to the info people would have gotten without AI?
https://x.com/emollick/status/2045708638317080798
Leave a Reply