alt Hacker NewsI don't think you want to bring cost into this argument.
Even if the cost was $1 mil for these 10 problems, that's maybe 10-20 math researchers for a year.
Do you really think that if you paid that to humans, they will deliver the same results?
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You need to bring both cost and benefit into the argument, and it's not necessarily an obvious win for either side. There are a few complicating factors here.
The cost of running a model is not only $/token, but the salaries of the people managing/orchestrating the models, deciding what theorems to try, etc. Once we factor that in, how much are we really paying per theorem?
The other factor is the subjective component of the value of a theorem. Not all theorems are created equal, and the only way to really measure the value is to ask professional mathematicians for their opinion, or publish the results and look at citations over months/years.
Once we have both of these nailed down, then we can start to do the cost/benefit analysis. To be fair, we should actually compare three groups: human experts, hybrid agent/human expert teams, and fully autonomous agents.
it's still important. not everyone has access to 1 million USD. saying it "only" coat 2000 USD is highly misleading for the discussion and future. the concentration of power is a huge problem with AI.
If you told them this was the problem and they would still have a job if they failed probably. The reasons people don't go head on these problems is career incentives and psychology.
It would still provide better context to see the numbers that the parent proposes, though.
Mentioning cost is fine, comparing may not be.
Grad students on zero pay solve problems like this everyday. What exactly is your point here?
It is comical at this point. Some people just can not stand the thought of AI actually delivering and are trying to find whatever ways to discredit it.