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> [This article] had to go deep into a branch of theoretical math to find a place where ML could make a demonstrable impact I have no opinion on this paper, bu

> [This article] had to go deep into a branch of theoretical math to find a place where ML could make a demonstrable impact I have no opinion on this paper, but that is generally how cutting-edge research works. First, choose an impactful unsolved problem you have the highest chance of solving. Then, use the new learnings to ascend higher mountains.

version_five 5y ago
I think you miss my point. This is not the first thing AI/ML has been demonstrated on. There are lots of powerful theoretical techniques that have done really well on research problems. But ML had been challenged to actually break into large scale practical utility. I think there is an argument that a lot of the mainstream work is solutions looking for problems, and my point is they found a problem finally, and it's a pretty obscure one. I see this more as a victory for finding something ML is good at, rather than finding it can help with a common or even specific real world problem. I dont like to repeat myself, but I am an AI bull, I believe there is lots of real value that we haven't got out of it yet. But problems like this don't help build a case for how useful it's supposed to be, given the investment deep mind has received and the fact that they and others are searching hard for practical applications. I don't mean to criticize the research in any way,I'm talking about commercial utility.
- psyklic 5y ago
  As far as assisting with pure math problems, it is in its infancy. Yet ML in general has had numerous practical successes that most people use daily (speech recognition, reverse image search, recommendation systems, etc.). Yesterday, Yann LeCun wrote on his Facebook page: "I didn't know that Facebook, and now Meta, would be built around AI. If you extirpated deep learning out of Meta today, the company would literally crumble." [Source: https://www.facebook.com/yann.lecun/posts/10158029031237143?comment_id=10158029040167143&reply_comment_id=10158029456812143 https://www.facebook.com/yann.lecun/posts/10158029031237143?...]

version_five 5y ago

I think you miss my point. This is not the first thing AI/ML has been demonstrated on. There are lots of powerful theoretical techniques that have done really well on research problems. But ML had been challenged to actually break into large scale practical utility. I think there is an argument that a lot of the mainstream work is solutions looking for problems, and my point is they found a problem finally, and it's a pretty obscure one. I see this more as a victory for finding something ML is good at, rather than finding it can help with a common or even specific real world problem. I dont like to repeat myself, but I am an AI bull, I believe there is lots of real value that we haven't got out of it yet. But problems like this don't help build a case for how useful it's supposed to be, given the investment deep mind has received and the fact that they and others are searching hard for practical applications. I don't mean to criticize the research in any way,I'm talking about commercial utility.

psyklic 5y ago
As far as assisting with pure math problems, it is in its infancy. Yet ML in general has had numerous practical successes that most people use daily (speech recognition, reverse image search, recommendation systems, etc.). Yesterday, Yann LeCun wrote on his Facebook page: "I didn't know that Facebook, and now Meta, would be built around AI. If you extirpated deep learning out of Meta today, the company would literally crumble." [Source: https://www.facebook.com/yann.lecun/posts/10158029031237143?comment_id=10158029040167143&reply_comment_id=10158029456812143 https://www.facebook.com/yann.lecun/posts/10158029031237143?...]