The cross-discipline general knowledge combined with the ability to churn huge datasets to find connections across already-known work, and extrapolate to or derive novel findings, is exactly one mode of superhuman success that AI companies have been trying to achieve.
Exactly.
Like in the quoted picture, there’s not a huge amount of people who have deep knowledge of Number Theory and the number of them who are also similarly versed in the math behind Quantum Physics could probably be counted on one hand and those people only have so much time.
Meanwhile, the only limitation in creating these AI systems is in how much RAM/compute we can manufacture.
There are massive libraries or repositories of scientific/mathematical published research throughout higher education institutions and across various technological industries. The required training data exists.
Exactly.
Like in the quoted picture, there’s not a huge amount of people who have deep knowledge of Number Theory and the number of them who are also similarly versed in the math behind Quantum Physics could probably be counted on one hand and those people only have so much time.
Meanwhile, the only limitation in creating these AI systems is in how much RAM/compute we can manufacture.
You need large volumes of high quality training data too, which are btw much harder to come by now
There are massive libraries or repositories of scientific/mathematical published research throughout higher education institutions and across various technological industries. The required training data exists.