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I'm not an AI researcher (although from my internet reading that's not a hard title to claim ;)) but I feel that ML/DL can't go much farther than they already have. The concept of "we just need more power" is an obvious fallacy to me.
Earlier quoted context omitted.
that's a trivial statement, unless he can suggest a different way to do things. Should people have held off building any bridges, until the 20th century arrived ? Building things and science have always evolved side-by-side in a feedback loop.
I'm not sure it was intended to be read "Can't win? Don't try." An interesting corollary to that analogy is that some of the things humans built thousands of years ago are still standing... so it's possible some of our systems could also pass the test of time (they can be optimized more easily than a bridge).
Earlier quoted context omitted.
Humans are proof that machine intelligence can be improved quite a bit. We are just complicated machines, no?
We're animals who have to worry about surviving and passing our genes on in a variety of social settings. Machines are the tools we make to aid the above.
> The problem had to do not just with data analysis per se, but with what database researchers call “provenance” — broadly, where did data arise, what inferences were drawn from the data, and how relevant are those inferences to the present situation? Plug: I work at a company ( https://www.pachyderm.com ) whose product is designed precisely to track data provenance across pipelines and through a company's larger dat…
You all should really play that up more in your messaging - "provenance" is one of the hardest and least-addressed components of building AI/ML/data science systems that actually have measurable impact (rather than analysts making plots and speculating). In general having a structured, centralized representation of business processes is super valuable I'm sure. If you write a blog post describing how critical that is…
I'm not an AI researcher (although from my internet reading that's not a hard title to claim ;)) but I feel that ML/DL can't go much farther than they already have. The concept of "we just need more power" is an obvious fallacy to me.
Where does the article say "we just need more power"?
Well said: > Thus, just as humans built buildings and bridges before there was civil engineering, humans are proceeding with the building of societal-scale, inference and decision making systems that involve machines, humans and the environment. Just as early buildings and bridges sometimes fell to the ground — in unforeseen ways and with tragic consequences — many of our early societal scale inference and decision m…
that's a trivial statement, unless he can suggest a different way to do things. Should people have held off building any bridges, until the 20th century arrived ? Building things and science have always evolved side-by-side in a feedback loop.
I saw Prof. Jordan give this talk in person, and the 2nd paragraph resonated with me. I wish there was more critical thinking involved in science/research/higher ed/industry but unfortunately most there's a lot of cheap money floating around with "experts" slurping it up without care for outcome. "But the episode troubled me, particularly after a back-of-the-envelope calculation convinced me that many thousands of pe…
I'm not an AI researcher (although from my internet reading that's not a hard title to claim ;)) but I feel that ML/DL can't go much farther than they already have. The concept of "we just need more power" is an obvious fallacy to me.
Agreed. Throwing more computing power at the problem is a cheap way to make it look like we're making progress; our AI should be efficient enough to run on limited hardware. Not to say that ML/DL isn't useful, but I think that whatever the next revolution is in AI is likely to come from a completely different direction. I'm not a researcher either, so it's difficult for me to articulate exactly what problems I see, b…
The biggest challenge yet unconquered is getting your "average" business ($1-100m revenue, zero AI knowledge) using ML to help with literally anything they do . I'd wager less than 1% of businesses outside of SV even have a clue where to begin, or what to use it for, my employer included. "Do we hire some AI guys?" We'll need to crack the 1%-using-it mark for me to consider the revolution "begun"...
Business people make no sense.