Let me start by saying that although I dearly love philosophy, it is entirely as an amateur. I dabble in theory, I know its consolations, but ultimately am tied to the concrete realities of biology: the needs, natural history, and behavior of real animals. Perhaps the structure of these things reflects or embodies deeper realities -- Mind, Form, Being, what have you -- but I prefer to approach those realities through observation.

So it is a little strange to be up against a problem that has long been in the preserve of philosophers, theoreticians, and computer scientists. The question is, in empirical terms, how do animals recognize objects? I am using this term in what is essentially a grammatical sense: anything that could be the object of a verb. Animals have to recognize particular things (such as other individuals of one's species) as well as classes of things or phenomena that should be treated in the same way (a hawk's cry, a branch, a ripe fruit). We can leave aside the question of whether animals have concepts that correspond to these objects -- whether they ascribe intentionality to other animals, for example -- it is enough that they have distinct responses to particular things or types of things.

The problem is variation, which comes from many sources. The most obvious one is noise. The connection is bad or the TV is out of focus or the room is loud and dimly lit. But variation also comes from the nature of the object, as well. Faces appear from different angles, voices are modulated by emotion or employ different words, trees don't grow the same way, and pigeons come in different colors. It seems fairly obvious that pattern recognition is more than just matching sensory data to a stored picture or template. There have been many suggestions as to what it does involve, many of which turn out to work fairly well when implemented in software and given a relatively limited set of inputs over which to operate (1). But the question of how animals actually solve this task is still open. We know that there is a general increase in selectivity as sensory data is processed by the brain, and there are neurons in some areas of primate brains that seem to respond only to particular objects, but it is not know how that selectivity is built up from the interconnections of neurons, or how brains learn the features of a pattern in the first place.

That's what I'm working on, in case you were interested.

(1) I am not particularly interested, from a scientific standpoint, in whether such artificial systems will ever "outperform" biological ones. It is a little like asking whether one species of falcon outperforms another. Yes, a peregrine flies faster and takes larger prey than a merlin, but the two species occupy different niches. Performance is only an issue when animals are in competition. It is, perhaps, worth asking why so many people seem to think we are in competition with biological systems.