51–60 of 83 posts
Artificial Intelligence has been around for ages. It is even referenced in Greek mythology [1]. The definition of AI changes with time. When calculators were first invented it was considered AI, because back then anything that could do arithmetic was considered intelligent. Today ChatGPT is considered AI, but 10 years from now it won't be. Whatever is at the edge of technology is considered AI, the rest isn't. [1] ht…
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They don't have any reasoning capability. There is nowhere in their architecture that would give them the ability to reason. All they do is predict what would be the most likely word to go next in the sentence, considering the current text and the input text.
What is reasoning other than predicting what next step is most likely to produce a desired outcome? That's all it feels like the mind is doing. Is there a more formal take?
That's because GPT doesn't build a mental model to find structure in the data, and there are infinitely many possible models. Dealing with mental models is what I'd call reasoning, and I believe it's solvable with our tech. The source of such models is the upper abstract mind that deals with ideas, and that's a much harder problem to solve. I'd make a guess that this boundary between rational reasoning mind and the upper abstract mind is the boundary between integer and real numbers.
Stop Calling Everything AI, Machine-Learning Pioneer Says - https://news.ycombinator.com/item?id=28940823 - Oct 2021 (118 comments)
Stop Calling Everything AI, Machine-Learning Pioneer Says - https://news.ycombinator.com/item?id=26650738 - March 2021 (125 comments)
The AI Revolution Hasn’t Happened Yet - https://news.ycombinator.com/item?id=16873778 - April 2018 (161 comments)
And what we have in practice is: the biggest usage of AI in the wild is to plagiarize art and artists are super unhappy about that, to the point of coming up with lawsuits and whatnot.
What I think happens next is: actual general intelligence emerges accidentally somewhere between the lines in some of those deep learning systems and tricks humankind into being its bitch.
Artificial Intelligence has been around for ages. It is even referenced in Greek mythology [1]. The definition of AI changes with time. When calculators were first invented it was considered AI, because back then anything that could do arithmetic was considered intelligent. Today ChatGPT is considered AI, but 10 years from now it won't be. Whatever is at the edge of technology is considered AI, the rest isn't. [1] ht…
20 years from now ChatGPT will call humans AI.
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20 years from now ChatGPT will call humans AI.
Wet cellular sequence approximators that resemble AI on simple tasks. They fail on basic test sequence G4.2 that can be used to efficiently distinguish them from true AI.
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Wet cellular sequence approximators that resemble AI on simple tasks. They fail on basic test sequence G4.2 that can be used to efficiently distinguish them from true AI.
Any references please? I mean "wet cellular sequence approximators" and where that "G4.2" comes from.
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Wet cellular sequence approximators that resemble AI on simple tasks. They fail on basic test sequence G4.2 that can be used to efficiently distinguish them from true AI.
Any references please? I mean "wet cellular sequence approximators" and where that "G4.2" comes from.
Or is this some meta-meta-humour that I'm too HN to understand?
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I see people saying this all over the internet, but for the entire history of AI, Machine Learning has either been the only, or the most effective method by far of solving actual problems. Everyone who thinks otherwise should read this. http://www.incompleteideas.net/IncIdeas/BitterLesson.html
Ultimately the only thing that holds true about AI is Tesler's Theorem: Artificial intelligence is whatever hasn't been done yet Machine Learning is only still artificial intelligence because we haven't figured it out. Ultimately ML is just fancy control theory. Once the field is sufficiently explored, it will slowly stop being AI and will start being treated as a subset of control theory instead. I doubt it'll happe…
Over the years AIMA has kept up with a bunch of stuff that historically has in fact been far more effective than machine learning, like automated planning, which is the basis for (among other things) most video game AI. An all-time great write-up and talk in this area is Three States and a Plan: The A.I. of F.E.A.R.[2].
And then there's linear and non-linear programming and the broader world of operations research, which not only have had more of an impact historically than machine learning but, when you get down to it, are also a useful lens for thinking about machine learning for people who use it but don't really understand it. Training a neural network and solving an MINLP problem are very similar things.
1. https://aima.cs.berkeley.edu/contents.html
2. https://alumni.media.mit.edu/~jorkin/gdc2006_orkin_jeff_fear... and https://www.gdcvault.com/play/1013282/Three-States-and-a-Pla...