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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
You can take context into account without active perception. Active perception only becomes really useful in a dynamic world where it's possible to formulate & test hypotheses (requires a time component)
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The current deep learning standard for implementing context-awareness is "neural attention" (cf Transformers), perhaps you know about it. It has very little in common with active perception though.
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The fact is that hardly any ML model takes "the world" as an input (complete with time, cause & effect). Only static snapshots of it. Ultimately this is why active perception hasn't taken off. If all of AI was cognitive developmental robotics it would be a different story.
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