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This is your usual Gary Marcus if you have been frequenting his social media outlets. As far as I can tell, no one in the field is disputing his core thesis tha

This is your usual Gary Marcus if you have been frequenting his social media outlets. As far as I can tell, no one in the field is disputing his core thesis that deep learning is not “AI” and there is fundamental issue that deep learning doesn’t do causal reasoning and it’s rather just fancy way to do function approximation. There have been plenty of papers on this including from Bengio and there is now entire new field of adversarial deep learning which is academic way of making fun of how it miserably fails. The root cause of said Twitter firestorm was Marcus’s accusation that world’s talent and money is moving en mass in deep learning research which is likely to turn out dead end for achieving “real” AI. Even worse, many uninformed decision makers think AI is already a done deal due to all the media hype. The counter point to his accusations were that deep learning is what works now and pretty well for many real world problems so we shouldn’t be putting it down. It is likely that deep learning might become integral part of broader some Artificial General Intelligence framework in future. So no harm in keep improving it. This would be especially be important when most of the accusers don’t actually have realistic alternative with much to claim.

YeGoblynQueenne 8y ago
Well, the stiffling of funding to symbolic AI is a real danger. The field just keeps shrinking. And it's not just funding. Many people entering machine learning today would simply not know a predicate if it leaped up and bit them in the existential quantifiers. They also have no idea that the field they are now joining en masse actually started out with learning in the propositional calculus, neither do they understand why it then moved to statistics. In short, there is a real risk that researech funding will go to support research that doesn't know its elbow from its knee, done by people who don't understand what they are doing (because they don't understand what was done in the past). That is not a rosy situation. I get the counter point- I'm myself a bit annoyed by Marcus' insistence on how deep learning is not true AI. Very few people really expect to see "true AI" in our lifetimes. A classifier that works well is probably the best we can do and it's very reasonable that there is such excitement about the fact that we can do it. But if we spend too much effort developing classifiers, well, we'll have great classifiers. And nothing else. And then- what?

YeGoblynQueenne 8y ago

Well, the stiffling of funding to symbolic AI is a real danger. The field just keeps shrinking. And it's not just funding. Many people entering machine learning today would simply not know a predicate if it leaped up and bit them in the existential quantifiers. They also have no idea that the field they are now joining en masse actually started out with learning in the propositional calculus, neither do they understand why it then moved to statistics. In short, there is a real risk that researech funding will go to support research that doesn't know its elbow from its knee, done by people who don't understand what they are doing (because they don't understand what was done in the past). That is not a rosy situation. I get the counter point- I'm myself a bit annoyed by Marcus' insistence on how deep learning is not true AI. Very few people really expect to see "true AI" in our lifetimes. A classifier that works well is probably the best we can do and it's very reasonable that there is such excitement about the fact that we can do it. But if we spend too much effort developing classifiers, well, we'll have great classifiers. And nothing else. And then- what?