They are fluffy PR pieces otherwise.
Before the Opus upgrade in November it was basically no way of doing this. I gave up very quickly.
After November i tried again, and no model could build me anything relevant.
Now it just works. Took me an hour to progress to a point were i'm happy.
Whatever they do, progress is still real, still way faster than I assumed
The list of Ubuntus 2404 LTS CVEs is HUGE. Another indicator that a lot of stuff got a lot better fast.
Feel free to be as dismissive as you want, but if you are not careful, you might be 'suddenly' surprised and you might not be prepared for the conclusion of AGI level agents.
I swear there's nobody blinder than those who won't see.
The first part of your sentence literally contradicts the second part: "we don't have enough knowledge to know, but I know the opposite".
"seem to be" carries semantic meaning here: I'm stating my interpretation of the situation based on data we have available (which is limited) and my prior.
Put another way: "We can't say that for sure, but my money is on it not being a simple case of intellectual property theft"
> We don't have enough accurate knowledge to say [one way or the other], and it doesn't seem to be the case at all [based on our incomplete knowledge].
But it is in no way equivalent to this:
> We can't say that for sure, but my money is on it not being a simple case of intellectual property theft
That is a different sentence.
No, it's an aggravated case, since it's the same way they got all of their training data in the first place.
Apparently if I use lib-gen, that's copyright infringement and I'm exposed to legal risk but it seems fine to download all of it if your intent is "train an AI" so far.
Based on what? Your crystal ball?
Eventually it won't matter. Arguments over whether LLMs are "truly" intelligent are going to be a matter of philosophy, and look a little silly.
Is nobody else astounded by this?
In which case, maybe we don't need as much compute as we might expect. I hesitate to say "to reach a singularity" because it's kind of hard to define how that works out. Even intelligence probably hits some scaling limits eventually (e.g. speed of light related restrictions on how far it can scale, or how quickly it can expand).
Bit ironic given the model’s alleged finding…
Singularities are model breakdowns. A singularity simply says our current methods cease to work in this region. Within the context of a recursively self-improving intelligence with an unknown bound, “singularity” is probably a good description of our current socioeconomic system.
And it's definitely supposed to imply some kind of historical discontinuity not a change in convexity.
But thinking about the geometry of this problem helps understand why people aren't adjusting well to this. While we're walking on the curve, we look at the rate of change of the curve and say, "well, yeah, of course, dy/dx is 5 at this point and was 1 at the point a few years ago, because the curve is getting steeper" but we're always going to feel this way as things rip off into the stratosphere because dy/dx(e^x) = e^x.
From standing on the curve the curve is notably seeper, but the steepness totally makes sense to you. It's only when you look back 10 years or so that you think "wait a second, holy hell, I couldn't have imagined this!"
The first time I really (I mean really) thought about the singularity and AI was in roughly 2014. I mean, yea, I'd thought about things before that, but yeah, before the Humans need not apply video, I'd never actually given it much thought. I think back to myself 10 - 15 years or so ago, when I was just starting to tackle real programming projects, and was just starting to get decent at writing code, there is no way on earth that I would have imagined that a little over a decade later, Navier-Stokes would be solved by a computer program and the vast majority of my work would be playing sooth sayer to increasingly complicated piles of linear algebra.
People on hackernews are actually some of the dumbest people on the internet. This place is worse than lesswrong.
Scroll down to the existing examples section.
Bit apples to oranges, but it reminds me of all the fiber we installed in the late 90s, certain that per-strand capacity increases were years or decades out, only to get massively rugged
I get the impression the only reason there is renewed interest in photonics is because DCs are simply out of room (and power) to rack more servers and switches.
I don't know that that's achievable yet. Though the era of increasingly advanced and automated robotics seems to be around the corner which could create a cycle, vicious or virtuous depending on how you feel about it.