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LeCun's technical approach with AMI will likely be based on JEPA, which is also a very different approach than most US-based or Chinese AI labs are taking. If
by brandonb 7mo ago
LeCun's technical approach with AMI will likely be based on JEPA, which is also a very different approach than most US-based or Chinese AI labs are taking.
If you're looking to learn about JEPA, LeCun's vision document "A Path Towards Autonomous Machine Intelligence" is long but sketches out a very comprehensive vision of AI research:
https://openreview.net/pdf?id=BZ5a1r-kVsf https://openreview.net/pdf?id=BZ5a1r-kVsf
Training JEPA models within reach, even for startups. For example, we're a 3-person startup who trained a health timeseries JEPA. There are JEPA models for computer vision and (even) for LLMs.
You don't need a $1B seed round to do interesting things here. We need more interesting, orthogonal ideas in AI. So I think it's good we're going to have a heavyweight lab in Europe alongside the US and China.
- sanderjd 7mo agoHave you published anything about your health time series model? Sounds interesting!
- brandonb 7mo agoSure! Here’s a description: https://www.empirical.health/blog/wearable-foundation-model-jets/ https://www.empirical.health/blog/wearable-foundation-model-...
- sanderjd 7mo agoThanks! This is very neat. BTW, I went to your website looking for this, but didn't find your blog. I do now see that it's linked in the footer, but I was looking for it in the hamburger menu.
- brandonb 7mo agoThanks! We need to re-do the top navigation / hamburger menu -- we've added a bunch of new things in the past few months, and it badly needs to be re-organized.
- smugma 7mo agoVery interesting. I am keenly interested in this space and coincidentally had my blood drawn this morning. That said, have you considered that “Measure 100+ biomarkers with a single blood draw” combined with "heart health is a solved problem” reads a lot like Theranos?
- brandonb 7mo agoFWIW, the single blood draw is 6-8 vials -- so we're not claiming to get 100 biomarkers from a single drop. The point of that is mostly that it just takes one appointment / is convenient.
- mkeoliya 7mo agoThis is very cool work! I have a quick follow-up: in the biomarker prediction task, what horizon (ie. how far into the future) did you set for the predictions? Prediction is hard beyond an hour, so it'd be impressive if your model handles that.
- brandonb 7mo agoThe prediction task is set up as predicting the next measured biomarkers based on a week of wearable data. So it's not necessarily predicting into the future, but predicting dataset Y given dataset X. The specific biomarkers being predicted are the ones most relevant to heart health, like cholesterol or HbA1c. These tend to be more stable from hour to hour -- they may vary on a timescale of weeks as you modify your diet or take medications.
- volkk 7mo agooh nice, i actually used you guys for some labs a few months ago. Glad you're competing with function & superpower
- tomrod 7mo agoI've been working to understand the potential uses for JEPA. Outside of video, has anyone made a list of any type (geared towards dummies like me)?
- mandeepj 7mo agoAppreciate your work! Healthcare is a regulated industry. Everything (Research, proposals, FDA submissions, Compliance docs, Accreditation Standards, etc.) is documented and follows a process, which means there's a lot of thesis. You can't sneak in anything unverified or unreliable. Why does healthcare need a JEPA\World model?
- brandonb 7mo agoRegulation is quickly catching up to modern AI techniques; for the most part, the approach is to verify outputs rather than process. For example, Utah's pilot to let AI prescribe medications has doctors check the first N prescriptions of each medication. Medicare is starting to pay for AI-enabled care, but tying payment to objective biomarkers like cholesterol or blood pressure actually got better.