A really good article about an interview with Andrew Ng as to why AI is still in a proof of concept phase and lacking in real world applications.
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A really good article about an interview with Andrew Ng as to why AI is still in a proof of concept phase and lacking in real world applications.
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This is a good one and it actually can be linked to a lot of past discussions we've been having in here.
He uses the health industry as an example, which we were just talking about the other day and he also references an issue that was pointed out in one of the articles you shared here: Machine learning is actually a misused term. Machines can do very well on a given test set of data, but if the context changes a bit, then the model might not respond properly anymore.
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The difference in performance just on different systems is a good example. Right now we are just relying too much on specialized data for specific applications.
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That is the learning model we have now. There is really nothing different.
I believe we will need a paradigm shift to really see any advancement in this field.
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