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.
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.
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.
If anyone has experience on getting this right, I would like to know how you do it.