As a student working in AI, I have to say that I both agree and disagree with this writer. I agree with his assertion that AI, in its current state, is not nea

As a student working in AI, I have to say that I both agree and disagree with this writer. I agree with his assertion that AI, in its current state, is not nearly as generalizable as we hope it to be, but simply because it is not now doesn't mean we should give up on it entirely and wait for some breakthrough to come in from another field. Better hardware has been a great boon to AI researchers, but it's in times like these that we need not only to verify or dismiss the mathematical theories put forth 50 odd years ago but enhance them with experimentation. For example, perhaps descriptors are truly the wrong way to go about object recognition in images, or perhaps segmentation is the wrong way to look at a scene, but they are ideas and they are worth testing. We won't find out unless we try, because unlike the equations proven decades before, there are no constraints we can simply apply.