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AI NOT ENOUGH MEMORY TO OPEN THE ILLUSTRATION SOFTWARE
AI NOT ENOUGH MEMORY TO OPEN THE ILLUSTRATION PLUS

And then you have to say, “Empirically, does the deep-learning stuff do what we want it to do?” And the problem so far is it has been model free.

AI NOT ENOUGH MEMORY TO OPEN THE ILLUSTRATION SOFTWARE

Almost all the world’s software is built on symbols. Instead we should say, “Can symbols help us?” And the answer is, overwhelmingly, yes. That’s a bit strange, and I don’t think we should take those arguments seriously. So I’ve heard both opposite extremes from deep learning. When I had a debate with Yoshua Bengio in December, Bengio said that the only commitment of deep learning was that it be neurologically based. It sounds like fundamentally both of you have a disagreement about what the goal of AI is. So I’m very skeptical of trying to solve AI by trying to mimic the human brain.ĭeep learning is not necessarily a silver bullet, but if you feed it enough data and you have the right neural-network architecture, it is able to learn abstractions that we as humans cannot interpret but that makes the system very efficient at solving a wide range of tasks. It reminds me a bit of, you know, in the 18th century if you wanted faster transportation, you would work on building a mechanical horse rather than inventing the combustion engine. The issue I have with symbolic AI is its attempt to try to mimic the human brain in a very deep sense. Of course, Google search is not the AI that we’re ultimately hoping to achieve, but it’s pretty solid proof that this is not an impossible dream.ĭanny, do you agree that we should be looking at these hybrid models?ĭanny Lange: No, I do not agree. And then it uses deep learning to do some other stuff-for example, to find synonyms using the BERT model.

It’s trying to figure out when you talk about “Paris,” are you talking about Paris Hilton, Paris, Texas, or Paris, France, using Google knowledge graph. When you type in a search query, there’s some classical AI there that is trying to disambiguate words.

One example that everybody knows is Google search. GM: In an article I wrote called “ The Next Decade in AI,” I listed about 20 different recent projects that try to put together hybrid models that have some deep learning and some symbolic knowledge. Have you seen any projects where they have successfully combined deep learning and symbolic AI in promising ways? So if a seven-month-old infant can do it, then why are we holding our hands behind our back trying to build AI without mechanisms that infants have? In my prior life as a cognitive development person, I did experiments with seven-month-old infants and showed that those infants could generalize symbolic knowledge. It still doesn’t mean it’s absolutely right, but it’s by far the best that we have.Īnd then there’s a lot of psychological evidence that people can do some level of symbolic representation. But at least in principle, it’s the only way we know to make systems that can do things like logical inference and inductive inference over abstract knowledge. It has its own problems: it usually doesn’t have enough coverage, because too much of it is hand-written and so forth.

It can, for example, parse a sentence to its semantic representation, or have knowledge about what’s going on in the world and then make inferences about that. So the results look great, but they’re typically not very generalizable.Ĭlassical AI-that’s its wheelhouse. There’s no way in these systems to represent what a ball is or what a bottle is and what these things do to one another. Deep learning just doesn’t represent that.

Why add classical AI to the mix? Well, we do all kinds of reasoning based on our knowledge in the world. But there may be a whole bunch of things we haven’t even dreamed of yet.

AI NOT ENOUGH MEMORY TO OPEN THE ILLUSTRATION PLUS

Gary Marcus: The first thing I’ll say is we may need hybrids that are more complicated than just deep learning plus classical AI. What is it about classical AI that you think makes it the right system to combine with deep learning? Gary, you draw upon your expertise in neuroscience and psychology to figure out what’s currently missing in AI.

Ai not enough memory to open the illustration