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notmahi.bsky.social
Building generally intelligent robots that *just work* everywhere, out of the box, at NYU CILVR. Previously at MIT and visiting researcher at Meta AI. https://mahis.life/
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If you don’t have the capacity to distinguish between what’s true and what’s not, your truths are just as incidental as your lies.
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Reading comprehension is an important but easily overlooked quality IMO
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This is super helpful for a non-sim person, thanks for the perspective!
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I agree, the paper could definitely be clearer. My assumption is “same training loop” ≈ “all else being equal”, but that can be totally incorrect.
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AFAIK it's the same dataset, they just use the larger pretrained model as the teacher model. Screenshot is from the DinoV2 paper section 5: arxiv.org/abs/2304.07193
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Dino-v2 is a good recent example in vision –
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I wish it were only podcasts, I am seeing form steamrolling over content in academic papers more and more these days.
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👋
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Would like to be added!
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I collected some folk knowledge for RL and stuck them in my lecture slides a couple weeks back: web.mit.edu/6.7920/www/l... See Appendix B... sorry, I know, appendix of a lecture slide deck is not the best for discovery. Suggestions very welcome.
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We took a bunch of them in robot learning and made a tutorial about them! I tried to put everything that I find myself regularly telling my students there somewhere. Really think it can save some days to months of a new grad students’ life. supervised-robot-learning.github.io
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I was presenting this at NEMS, yes :)
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Would love to be added! Check out dobb-e.com or ok-robot.github.io for some example works from our lab.
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You can try the archived link: archive.today/mNefb
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In Robot Utility Models, we collected a large number of demonstration videos — 1000 examples in 40 environments — using a tool called “the Stick." The lead author even demonstrated it live at CoRL on completely new furniture. This one really does 100% actually work - I’ve used it in my house.