“We need a new generation of AI researchers who are well versed in and appreciate classical AI, machine learning, and computer science more broadly while also being informed about AI history.” @AdnanDarwiche, on why deep learning is not enough https://dl.acm.org/citation.cfm?id=3281635.3271625&coll=portal&dl=ACM …
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Agree but there are already a lot of people who fit this description. The danger is more that the next generation of researchers might not.
I’m not sure. As a litmus test: what proportion of deep learning trained reseachers have even heard of CYC?
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For students publishing at NLP conferences, I'm sure it's more than half, possibly more than three-quarters. It's pretty hard to avoid hearing about (most often as a cautionary tale).
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When I asked a couple years ago at a packed NIPS symposium, I got blank stares. Only 5-10% of crowd raised hands when I asked if people had heard of CYC. If half of recent grads in NLP knew about CYC I would be (pleasantly) surprised.
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I'm not showing knowing much about Cyc days something positive about a researcher, but most of the NLP people I know who work on DL will probably have heard of it.
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"showing" = "sure" here. Damn phone.
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I have taken and helped teached Intro to AI at GT and Stanford now, and things definitely still start not at DL (constraint satisfaction, logic, etc. are covered). And then there is robotics which covers much more than DL. But it would be nice to have 'history of AI' classes...
Thanks. Twitter will use this to make your timeline better. UndoUndo
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Very few people fit that description. Most AI researchers haven’t looked much beyond computer science, and as a result confuse learning for intelligence.
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Often people confuse "machine learning" for *learning* (in the human sense), which actually does involve intelligence.
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