A Real Test for Object Recognition

February 9, 2009

Dun dun dun

Humans are remarkably good at identifying the same face across illuminations, positions, deformations, and depths. The same face can even be identified through fences, glass, and water. The possible number of contexts for a face to appear in are infinite, yet we can identify it instantaneously. For whatever reason, we are really good at identifying objects, but researchers have struggled to make computers even semi-competent at it. One of the more valiant efforts is Yann LeCun’s use of convolutional nets, but its primary successes are in controlled situations. Any reasonable person in the field would agree that any human can wipe the floor with even the best algorithm running on the best supercomputer (programmed by the best programmer in the best department in the best state in the best country!). So what gives?

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The Brainputer

February 2, 2009

After running through the Businessweek article posted by Max, I am equally excited and nervous. Anyone has to be excited over the prospect of a new computing paradigm, though honestly I’m not sure what that looks like yet. These sorts of articles claim that computers will look more like brains, which is all well and good, because brains tend to do dominate the “competition”, i.e. computers, at messy things like object recognition and speech recognition. Conversely (and obviously), computers tend to dominate tasks amenable to decomposition into easily formalizable sequential steps, e.g. chess or even eye surgery. So, maybe we know what Deep Blue looks like, but what on Earth would a computer expert in messy things, a messy computer if you’ll excuse the phrase, even look like? We all agree that computers stink at these messy things, and if they didn’t stink at them it would be a huge boon to, well, humankind. So let’s make the computers more like brains so they can do what brains do so well! But how do we make computers, both in terms of hardware and software, more like brains?

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