True, although it's not clear exactly what this is really doing. The RL was presumably trained on human input, but the overall agentic flow (it seems this is an agent), sounds to me like a neuro-symbolic hybrid, potentially brute force iterating to great depth, so maybe more computer than brain inspired.
It seems easy to imagine this type of approach being super human on narrow tasks that play to it's strengths such as pure reasoning tasks (math/science), but it's certainly not AGI as for example there is no curiosity to explore the unknown, no ability to learn from exploration, etc.
It'll take a while to become apparent exactly what types of real world application this is useful for, both in terms of capability and cost.
I agree, but it remains to be seen how that "feels" for everyday tasks where the underlying model itself would have failed. I guess at least now it'll be able to play tic tac toe and give minimal "farmer crossing river with his chicken" solutions!
