horhay

4 ms·

31.
by horhay 1y ago
You mean /knowledge/ is easier to collect lol. Not even grow. And if it's easy to grow with what we know then space travel to outside our solar system might already be a thing today. "Growing intelligence" requires
32.
by horhay 1y ago
They're gonna say this at a time where people are starting to question how farther we can scale hardware with the scientific knowledge that we've had? It doesn't even take researchers to know that GPU capabilities aren't
33.
by horhay 1y ago
You keep saying reiterating this like the people in charge of researching for this agree with this bar that you set. These qualified people can't even agree amongst themselves. Also. That second point is like the most unhelpful point I
34.
by horhay 1y ago
Lol they are not using ChatGPT for the full diagnosis. They're used in steps of double checking knowledge like drug interactions and such. If you're gonna speak on something like this in a vague manner I'd suggest you google
35.
by horhay 1y ago
People can't even begin to actually quantify how an "AGI" fits the world. Or define it consistently. How do you think you can hypothesize preparing for it? This is why people keep telling you that talking about it is ultimate
36.
by horhay 1y ago
My brain just bleeps out "x-level" as a description of LLM output. It doesn't really make sense and is usually most used by Silicon Valley folk who can't even begin to quantify such definitions with any type of consisten
37.
by horhay 1y ago
It's pretty much expected that everything is "world shaking" in the modern day tech world. Now whether it's true or not is a different thing everytime. I'm fairly certain even the 4o image gen model has shown weakne
38.
by horhay 1y ago
This is more about a physics math aptitude test. You can already see that the best model in math is saturating it halfway. It might not indicate its usefulness in actual physical reasoning, or at the very least, it seems like a bit of a str
39.
by horhay 1y ago
They aren't lying in the way that LLMs have been seeing improvement, but benchmarks suggesting that LLMs are still scaling exponentially are not reflective of where they truly are.
40.
by horhay 1y ago
They also got these things working corners of a location instead of stacking tasks on different areas of the same location. And even on these "one-area" task groups it can fail a good amount. Kudos to them for showing the failures