Earlier quoted context omitted.
If you look at compute scaling and model improvement on that compute, we’re going to get there pretty fast. Both compute, architecture and cost matter, and those have been improving like crazy. I don’t know about you, but I didn’t expect GPT-4o to come out at half the price one year later, with real-time voice, image and text. There is zero sign of slowing, Nvidia keeps building beefier GPUs specialized in LLMs, the…
> You can plot this exponential growth out over time and calculate when these models will have the complexity of the brain. Then you can assume some penalty for shitty architecture (that gets better over time), and you’ll have a ballpark estimate. The same thing could’ve been said for self driving cars, or the space program, or a lot of things that seemed to be progressing quickly at the time.
Neither the space program nor self driving are compute restrained.
The latter will probably be “solved” as we get closer to AGI, since you need some sort of human like reasoning for edge cases that require reasoning.
Another tech like this is batteries: There is no miracle jump in production batteries. They just improve about 10% YoY, both in energy density and cost.
So you can extrapolate when electric cars will be cheaper than gas cars to buy.
Intersects around 2035 last I checked.