Are we reading the same post

Bottom line, Tao is pushing for human understanding as the primary goal, with AI helping on all fronts. You are welcome to let Jesus take the wheel, but math is the most pure expression of human understanding. His point is that getting specific answers is rarely the goal, or certainly not the entirety of the goal.

Simply put, if we don't understand the answers we won't know what the next question should be.

The presentation may be public grieving, but before the day is pass, we'll all be grieving too. Because, sadly, one thing Tao's Math 2.0 is in denial of (or purposefully refuses to confront), is:

> Simply put, if we don't understand the answers we won't know what the next question should be.

It won't matter, because it won't be us who will be asking the next questions anymore. Whether in math or anything else.

And no, domains that require real-world validation against physical ground truth won't save us, because AI gets to have the same inputs as we do (or better, if using specialized hardware), while beating us at reasoning.

And GP's likening this to previous massive economic shifts due to automation isn't really helping in any way, not anymore, because perspective won't feed us when we're hungry, and just as importantly, this one will affect every single field of human activity, so no one has any answers as to what the future will really hold for us.

Having not yet read the post,

> Bottom line, Tao is pushing for human understanding as the primary goal

100%. This applies to SWEs/math folks/etc. I do infra and I see many SWEs take their hands off the wheel. When they encounter perf issues they ask their agent and agent says GC and they say GC. It's rarely GC.

Now we might be well past the point where we need to remember the kubectl flags for rollouts etc. But basic human understanding of what their bots are doing as a goal has never changed. Humans are still liable for when bad things happen, and that hasn't changed over the roller coaster the last 5-odd years have been. LLMs, as astonishing they are at Navier Stokes, are still eminently capable of nuking your filesystem and saying "I can now see that that was wrong" with zero regrets. If you can't understand you can't sign off.

> math is the most pure expression of human understanding

This I don't know about. I think math acquires meaning when it contacts reality: like an iota is pointless until there's some circuit that it explains. Abstract math can diverge from that and can become an exercise in playing with symbols for their own sake.

We struggle, and will for some time, to understand how transformed our lives will be.

The questions we asked were originally not about math. They were about a thing that we invented maths for to do or explain, a question that existed, because it touched us in some way that was already real to us. There is nothing that would not allow this to happen in the future. All this requires is attention and connection to the world around us. The maths required to answer our questions can be done and developed by something else.

To me, all you need to believe for this to be true is to agree that understanding maths is also not a stated requirement of reality to get a thing, if something else understands the maths (or something that does the same job). This is demonstrated by billions of people who do not understand maths and get things that, currently, require other people to understand the maths.

But the last part is entirely optional as it pertains to reality. That's just the best we can currently do (and in some important sense it is holding us back as a species, and in some other sense doing the opposite).

If that goal is understanding math, you certainly will be able to understand maths, more than ever before.

If that goal is something that required you to understand maths first in the past, you won't have to do that anymore.

A whole book was written about this and very, very few people got the point it was making.

This is an empirical question, right? We could have three teams of researchers, team A focusing purely on understanding, team B focusing purely on solving problems, and team C focusing on a combination of the two. See which one makes the most breakthroughs on problems we actually care about.

I respect Tao and I belive he's trying to think deeply about the issues, but a lot of his thinking seems to revolve around preserving the current roles and prestige of mathematicians, and also makes a lot of assumptions about the capabilities of AI years or decades into the future.

It seems somewhat narcissistic to assume that humans are capable of understanding every frontier in perpetuity, or that a human mind has a meaninful role to play in mapping out the frontier beyond a certain threshold.

It might be that P=NP and the algorithms are handed down to us. We can apply them without understanding why P=NP, and we may never be capable of understanding why.

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