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So the headline is pretty clearly right, we were coming out of the circa 2016 deep learning bubble and expectations were being adjusted, gen AI came in and the

by andy99 3y ago

So the headline is pretty clearly right, we were coming out of the circa 2016 deep learning bubble and expectations were being adjusted, gen AI came in and the hype roared back up, now we're peaking, the same problems from before are still there even if the demos are cooler, and expectations need to be tempered again. But instead of that, the article starts with The tech's drawbacks are hard to overlook. Large language models like ChatGPT are prone to hallucinating and spreading misinformation. Both chatbots and AI image makers have been accused of plagiarizing writers and artists. And overall, the hardware that generative AI uses needs enormous amounts of energy, gutting the environment. None of those (hallucination maybe) are relevant, if it's good at automating misinformation, surely it can do useful work as well. This is more just a list of random criticisms. Then Perhaps most of all, according to Gary Marcus... No point in continuing to read.

pavel_lishin 3y ago
AI giving wildly incorrect answers is incredibly relevant. And if it can "surely" do useful work... why isn't it? That's like saying, "Sure, this car burns oil, but if it can do that, it can surely do more than that and be my daily driver."
- ben_w 3y ago
  AI does do useful work. It's also being treated as magic, with all the same unrealistic expectations. To treat it as more than it is, is as much a mistake as to treat it as less than it is. I'm glad it's "only" at the level of an intern (sometimes you're willing to hire them, sometimes you're not); but conversely I think this means I can't risk changing career.
Agingcoder 3y ago
No - these are exactly the issues being brought up where I work. They make mistakes, carry potential legal liabilities and cost a fortune ( dollars or carbon ) to run. The only difference with before is that they now look a lot closer to being able to replace people for real, and that’s a significant difference. Now, replace ‘ai’ with ‘employee’ and the profits must be very clear to hire such an unreliable person. Some companies worry about these things. In my view if the amount of mistakes could be acceptably low, this would change the game ( both ‘ acceptably’ and ‘low’ are valid directions).
Nullabillity 3y ago
> None of those (hallucination maybe) are relevant, if it's good at automating misinformation, surely it can do useful work as well. Filtering out the truth is the hard part. If you just want data and don't care about quality there's always /dev/urandom.

by andy99 3y ago

pavel_lishin 3y ago

AI giving wildly incorrect answers is incredibly relevant. And if it can "surely" do useful work... why isn't it? That's like saying, "Sure, this car burns oil, but if it can do that, it can surely do more than that and be my daily driver."

ben_w 3y ago
AI does do useful work. It's also being treated as magic, with all the same unrealistic expectations. To treat it as more than it is, is as much a mistake as to treat it as less than it is. I'm glad it's "only" at the level of an intern (sometimes you're willing to hire them, sometimes you're not); but conversely I think this means I can't risk changing career.

Agingcoder 3y ago

No - these are exactly the issues being brought up where I work. They make mistakes, carry potential legal liabilities and cost a fortune ( dollars or carbon ) to run. The only difference with before is that they now look a lot closer to being able to replace people for real, and that’s a significant difference. Now, replace ‘ai’ with ‘employee’ and the profits must be very clear to hire such an unreliable person. Some companies worry about these things. In my view if the amount of mistakes could be acceptably low, this would change the game ( both ‘ acceptably’ and ‘low’ are valid directions).

Nullabillity 3y ago

> None of those (hallucination maybe) are relevant, if it's good at automating misinformation, surely it can do useful work as well. Filtering out the truth is the hard part. If you just want data and don't care about quality there's always /dev/urandom.