Breaking news, amazing insight from AI researchers. Exciting times. https://twitter.com/fchollet/status/1389725209800830980 …
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It has simply not yet shown to be necessary, or even useful. It actually seemed like a more attractive avenue when we knew less and our models performed worse.
ML models don't attempt to emulate human cognition, and they're solving a different problem than embodied cognition in the first place, with different constraints and different degrees of freedom.
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If your input is a static image that you're trying to classify, that's a very different setup than being an embodied agent immersed in a dynamic world subject to cause and effect. In the former case, processing all the information available in one go is actually more effective
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How does that work with ambiguity in the signal, though? Even static images can be ambiguous and require active inference. For example, see this Figure from Bar (2004), where the same blob can be seen as a hairdryer or drill depending on active interpretation of the scene.pic.twitter.com/v4ZWzmCanP
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