ML first, then Bio and Data. Of course, interconnectedness runs high (eg just read about ML for non-random missingness in med records) and that data is the foundational bottleneck/need across the board.
I'd love to hear more of our thoughts re open questions in biomedical ML. You sound like you have a crisp, nuanced grasp the landscape, which is rare. That would be very helpful to me, as an undergrad in CS (with bio) trying to crystalize research to pursue in bio/ML/GenAI.
What do you mean?
I was referring to just the chain of thought you see when the "DeepThink (R1)" button is enabled.
As someone who LOVES learning (as many of you too), R1 chain of thought is an infinite candy store.
Interesting insight/possibility. I did see some capacity glitches with my Cursor recently. Overall, I like Anthropic (and ChatGPT); hopefully they continue to succeed.
Let me qualify your statement... CapEx is what EXISTING US firms were/are lining up to battle with.
With R1 as inspiration/imperative, many new US startups will emerge who will be very strong. Can you feel a bunch of talent in limbo startups pivoting/re-energized now?
Can you tell me more about how Claude Sonnet went bad for you? I've been using the free version pretty happily, and felt I was about to upgrade to paid any day now (well, at least before the new DeepSeek).
The chain of thought is super useful in so many ways, helping me: (1) learn, way beyond the final answer itself, (2) refine my prompt, whether factually or stylistically, (3) understand or determine my confidence in the answer.