you just need to look at Mythos to see the jump in performance from a 10T(?) model. As they scale, they get more capable. We might have an yearly release, but I believe the releases will continue, as long as scaling laws are in tact, and there's huge problems still need solving. (think cancer)
And how are we meant to look at Mythos? Do you have access?
no but they tell me it's TERRIFYING and DANGEROUS and we should INVEST MORE MONEY
Through association with a large company:
https://www.anthropic.com/glasswing
Ive seen the tickets generated by the model that have trickled to my team. They are legitimate, but i can’t speak to model improvement because its a pilot program.
Through the lenses of anthropic's marketing department of course
>you just need to look at Mythos to see the jump in performance from a 10T(?) model
Mythos is a bunch of likely overhyped claims at this point. A few experts who looked into the claimed results weren't that impressed.
And there seems to be a ton of experts on the opposite side.
As they say, the truth tends to be somewhere in the middle.
You forget that these models are still only interpolating between human-generated datapoints fed to them. They cannot reason beyond the data they've been given, so unless everything you want to create with AI is a synthesis of prior art, you're back to relying on the stone-age human brain that created AI in the first place.
>these models are still only interpolating between human-generated datapoints fed to them. They cannot reason beyond the data they've been given
Are you sure that humans can?
Didn't a SOTA recently solved a mathematical theorem, one escaping mathematicians for 80 years?
Maybe a human "novel" invention is just a good interpolating from the datapoints (knowledge) fed to the human.
Not all training data is human generated, and it's also not clear that being ridiculously good at interpolating between data points (whatever that means) will not lead to superhuman capabilities.
loading story #48313616
Your phrasing ("you forget") implies this is a fact and common knowledge, while in fact there's little reason to think that's true.
Do you know if anyone has trained, say, a pre-2017 model and tried to get it to come up with Attention Is All You Need? If it did, would you say that was only because it's a synthesis of prior art? If so, what isn't?
loading story #48313730