zlacker

>>tedsan+(OP)
I'm confused and a bit disturbed; honestly having a very difficult time internalizing and processing this information. This announcement is making me wonder if I'm poorly calibrated on the current progress of AI development and the potential path forward. Is the key idea here that current AI development has figured out enough to brute force a path towards AGI? Or I guess the alternative is that they expect to figure it out in the next 4 years...

I don't know how to make sense of this level of investment. I feel that I lack the proper conceptual framework to make sense of the purchasing power of half a trillion USD in this context.

>>TheAce+9g
> Is the key idea here that current AI development has figured out enough to brute force a path towards AGI?

My sense anecdotally from within the space is yes people are feeling like we most likely have a "straight shot" to AGI now. Progress has been insane over the last few years but there's been this lurking worry around signs that the pre-training scaling paradigm has diminishing returns.

What recent outputs like o1, o3, DeepSeek-R1 are showing is that that's fine, we now have a new paradigm around test-time compute. For various reasons people think this is going to be more scalable and not run into the kind of data issues you'd get with a pre-training paradigm.

You can definitely debate on whether that's true or not but this is the first time I've been really seeing people think we've cracked "it", and the rest is scaling, better training etc.

>>dauhak+Ur
> My sense anecdotally from within the space is yes people are feeling like we most likely have a "straight shot" to AGI now

My problem with this is that people making this statement are unlikely to be objective. Major players are in fundraising mode, and safety folks are also incentivised to be subjective in their evaluation.

Yesterday I repeatedly used OpenAI’s API to summarise a document. The first result looked impressive. However, comparing repeated results revealed that it was missing major points each time, in a way a human would certainly not. In the surface the summary looked good, but careful evaluation indicated a lack of understanding or reasoning.

Don’t get me wrong, I think AI is already transformative, but I am not sure we are close to AGI. I hear a lot about it, but it doesn’t reflect my experience in a company using and building AI.

>>rhubar+831
Yeah obviously motivations are murky and all over the place, no one's free of bias. I'm not taking a strong stance on whether they're right or not or how much of it is motivated reasoning, I just think at least quite a bit is genuine (I'm mainly basing this off researchers I know who have a track record of being very sober and "boring" rather than the flashy Altman types)

To your point, yeah the models still suck in some surprising ways, but again it's that thing of they're the worst they're ever going to be, and I think in particular on the reasoning issue a lot of people are quite excited that RL over CoT is looking really really promising for this.

I agree with your broader point though that I'm not sure how close we are and there's an awful lot of noise right now

>>dauhak+nm2
Thanks, that’s helpful.

“The worst they’re going to be” line is a bit odd. I hear it a lot, but surely it’s true of all tech? So why are we hearing it more now? Perhaps that is a sign of hype?