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Terence Tao: AI solving conjectures too fast, not creating real value
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In a keynote at the Science x AI Summit at Caltech, mathematician Terence Tao criticized the current pace of AI development, arguing that while AI systems are solving major mathematical conjectures, they are not creating genuine value. Tao stated that the field is moving too fast and that results are weaker than they could be if pursued in a more leisurely, principled manner. He emphasized that problems like the Navier-Stokes equations do not need urgent solutions and are not a world-crisis situation. Tao concluded that the current state of AI research is 'not right' and that a slower, more deliberate approach would yield better outcomes.
Source report
In a keynote address at the Science x AI Summit at Caltech, mathematician Terence Tao offered a critical perspective on the current trajectory of AI development in mathematics.
"We can afford to be slower than this. And seriously, where we are now is not right."
Tao acknowledged that AI systems are solving major conjectures "left and right," but argued they are not creating genuine value.
"Okay, fine, they're solving major conjectures and so forth left and right, but they're not actually creating any value. Or whatever they have is much, much worse, much weaker than what it could have been if it was done in a leisurely, principled manner."
He specifically cited the Navier-Stokes problem as an example of a challenge that does not require urgent resolution.
"These problems, 'Navier-Stokes' — we don't urgently need them next week. This is not something that we need to cram on. This is not a major world-crisis-type situation. We can afford to be slower than this."
Tao concluded by reiterating his central concern:
"And seriously, where we are now is not right."
Source: Terence Tao's keynote at the Science x AI Summit at Caltech, via the "SAIR" YouTube channel (full video link in comments)
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rohanpaul_aiNeutral / independent