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9 results for “ai applications”
And once you develop this teleoperation interface, it means that you can collect data to train a machine learning based policy to solve a wide range of different tasks, including the really challenging task of tearing off tape and putting it onto a b
6:14:51 / 6:16:00
from transcript6:14:51 – 6:16:00
...advance, applications and really useful problems, in the real world. Supervised learning works really well. We've seen significant advances in architectures, learning algorithms, and in optimizers. And we also have reliable engineering practices for
6:16:24 / 6:17:31
from transcript6:16:24 – 6:17:31
if we could take at this point a bit of a tangent and talk about education and learning. If you're somebody listening to this who's a smart person interested in programming, interested in AI, so I presume building something from scratch is a good beg
2:12:45 / 2:13:46
from transcript2:12:45 – 2:13:46
There's for example, the DCLM datasets, where they also train the classifier, but not to detect educational content. Instead, they trained it on open HERMIS datasets, which is a datasets for instruction tuning. And also the ExplainLikeIM5 subrredit.
14:11 / 15:16
from transcript14:11 – 15:16
So for example, for them, they always see the generations on either source code or raw text documents, and then they rewrite them to make sure they're easier to generate instructions from. And then they use that for their like instruction data genera
15:36 / 16:48
from transcript15:36 – 16:48
And, oh, going into this year, you can see we have released a lot of things this year. First of all, in February 2024, we released, mister small, mister large, Lechat, which is our chat interface. I will show you in a little bit. We we released, embe
32:18 / 33:20
from transcript32:18 – 33:20
selfishly, I'll promote a bunch of, like, Western companies. So both in The US and Europe have these, like, fully open models. So I work at Allen Institute for AI. We've been building Omo, which releases data and code and all of this. And now we have
44:13 / 45:26
from transcript44:13 – 45:26
And, on a number of topics that actually the the foundation models clearly care a great deal about, open source models are pretty good on math instruction following and adversarial robustness. The llama model is amongst the top three of of evaluated
5:31 / 6:32
from transcript5:31 – 6:32
some people are getting a little ahead of ahead of themselves. So simple, rote, repetitive stuff, yes. More complicated stuff, we we have work to do. It seems like there's been an investment in smaller, more narrow models, and some debate about that.
8:14 / 9:22
from transcript8:14 – 9:22
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