critical history and context that a lot of people have conveniently forgotten
François Chollet (@fchollet)
For a very long time most high-performing AI models were end-to-end neural models; vector input -> vector output, with only ultra-thin symbolic preprocessing and postprocessing layers (e.g. label decoding). For many, it seemed that moving more and more logic to the end-to-end neural model was the way of the future. "Differentiable programming".
But what we have now is heavy neurosymbolic systems where the model itself is symbolic.
— https://nitter.net/fchollet/status/2085327394382979164#m