What are the measurable outcomes of researchers in the AI world

Early this month, OpenAI has released several papers answering decades old problems to which mathematicians have dedicated their own careers. This NYT piece on Terrence Tao (who first supported AI when it was AI to help humans in the process of discovery, but shunned them when it became apparent that they were looking for the discovery for discovery sake, and not for the journey of learning. Personally, I think it's a matter of changing the training dataset to learn in the process, and AI can do maths the human way very soon. OpenAI has tried to ask for forgiveness by pledging 5 million to mathematics, maybe hoping that they come back in tokens. On the other side of the duopoly, Anthropic has donated shares to the public good, which seems to me impossible to manage. AI is here to stay, and it's only a matter of us, humans, mathematicians or software developers finding our raison d'être and learning to communicate with AI in a way that it also advances our knowledge. At the heart of…