171–180 of 217 posts
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The concern, nominally, is that it’s too good. They’re worried that it'll lead to a huge influx of things like spam comments and fake news articles.
That's the first time I've heard of a company being worried that their product is too good.
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Are there any TPUs that can be purchased off-the-shelf and then owned, like you can do with a CPU or GPU? Or are you just limited to paying rent to cloud providers and ultimately being at their mercy when it comes to pricing, ToS, etc?
https://aiyprojects.withgoogle.com/edge-tpu/
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Have you heard of GitHub copilot ? It’s based on GPT3 and I can tell you one thing: it does not generate meaningless prose (90% of the time)
The fact that GPT3 works at all for coding indicates that our programming languages are too low level and force a lot of redundancy (low entropy). From a programmer productivity optimization perspective it should be impossible to reliably predict the next statement. Of course there might be trade offs. Some of that redundancy might be helping maintenance programmers to understand the code.
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> IBM managed to beat Garry Kasperov using symbolic AI did they not? So in what way does it not work? Ok, I should be clearer. ML approaches are way way better than symbolic approaches. Given almost any problem, it is much much easier to make an ML approach work than any symbolic approach. Yes, chess was first solved symbolically, but it's since been solved by ML better and more easily, to the point that stockfish no…
>> I would challenge you to name any (non-simple) problem where traditional AI methods are still state of the art. Theorem proving, classical planning, SAT solving, robotics, search, in particular adversarial search, program induction, knowledge representation. Plus all the stuff that used to be considered "AI" but aren't anymore, like rule-based systems (e.g. for fraud detection) etc. Sorry, I know you asked for onl…
Robotics is already on its way there. Is this program induction https://paperswithcode.com/task/program-induction ? Looks like it's headed towards ML too. I suspect you could stick ML into SAT solving and get yourself a system that worked pretty decently.
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The difference between ML and symbolic AI is that ML works and symbolic AI doesn't. At my job, dropping the computational load of our ML models is heavily invested in, and every success is celebrated. Everybody wants it to be easier and cheaper to train high quality models, but some things are still intrinsically hard.
>The difference between ML and symbolic AI is that ML works and symbolic AI doesn't. There was a point when it was the other way around, this is not static but the result of resources being poured. The data heavy, computational heavy, black box style of ML gives power to large business over small business. So it's seen as a safer bet than symbolic A.I. This in turn makes it work better, which makes it an even safer b…
Classical AI has failed in robotics. There's practically no field where it does worse than in robotics. It's getting cut out of every part of every system one piece at a time, and being replaced by ML methods that really work. Even Kalman Filters aren't safe.
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> IBM managed to beat Garry Kasperov using symbolic AI did they not? So in what way does it not work? Ok, I should be clearer. ML approaches are way way better than symbolic approaches. Given almost any problem, it is much much easier to make an ML approach work than any symbolic approach. Yes, chess was first solved symbolically, but it's since been solved by ML better and more easily, to the point that stockfish no…
> I would challenge you to name any (non-simple) problem where traditional AI methods are still state of the art. Did ML methods best classic AI in dialog comprehension, say to the level of SHRDLU? I'm curious, can ML system do that - https://en.wikipedia.org/wiki/SHRDLU ?
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>The difference between ML and symbolic AI is that ML works and symbolic AI doesn't. There was a point when it was the other way around, this is not static but the result of resources being poured. The data heavy, computational heavy, black box style of ML gives power to large business over small business. So it's seen as a safer bet than symbolic A.I. This in turn makes it work better, which makes it an even safer b…
> Also notice that in some domains ML is still behind symbolic A.I., for instance a lot of robotics and autonomous vehicles. Classical AI has failed in robotics. There's practically no field where it does worse than in robotics. It's getting cut out of every part of every system one piece at a time, and being replaced by ML methods that really work. Even Kalman Filters aren't safe.
IIRC and Waymo vehicles used ML for some of its perception but also depended heavily on the lidar and a rules based approach. Sadly I can't find a link at the moment.
What examples are you thinking of?
[1] https://www.quora.com/How-does-Boston-Dynamics-use-AI-machin...
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> Also notice that in some domains ML is still behind symbolic A.I., for instance a lot of robotics and autonomous vehicles. Classical AI has failed in robotics. There's practically no field where it does worse than in robotics. It's getting cut out of every part of every system one piece at a time, and being replaced by ML methods that really work. Even Kalman Filters aren't safe.
It's been a few years since I investigated, but Boston dynamics was using mostly old non ML methods. See [1] IIRC and Waymo vehicles used ML for some of its perception but also depended heavily on the lidar and a rules based approach. Sadly I can't find a link at the moment. What examples are you thinking of? [1] https://www.quora.com/How-does-Boston-Dynamics-use-AI-machin...
Boston Dynamics was definitely an exception for a long time. Certainly the perception systems that they are adding use ML, but you are right that they use expressly use classical methods for their control system.
I never got why GPT-3 was so closed off, like you needed permission to use it. If it’s so good then why not just make it available?
I think the reasoning was that GPT-3 could easily be used to fill the world with realistic bullshit that would take ages to debunk.
GPT-3 is the most overrated game in town. And Microsoft spending $1 Billion for an exclusive license will seem really foolish a few years from now.
No it won't. Capital was (and still is) cheap when they made that purchase. A billion used to really mean something, but it's chump change for companies with valuations over $1 trillion.