Here is an amusing addendum to the last post. The NYT ran an article (here) discussing the edge that China will have over the rest of the world in AI research. What’s the edge? Cheap labor! Now you might find this odd, after all, AI is supposed to be that which makes labor superfluous (you know, the machines are coming and they are going to take all of the jobs). So, why should cheap labor give the Chinese such an advantage? Easy. Without it you cannot hand annotate and hand curate all the data that is getting sucked up. And without that, there is no intelligence, artificial or otherwise. Here is what cheap labor gets you:
Inside, Hou Xiameng runs a company that helps artificial intelligence make sense of the world. Two dozen young people go through photos and videos, labeling just about everything they see. That’s a car. That’s a traffic light. That’s bread, that’s milk, that’s chocolate. That’s what it looks like when a person walks.
As a very perceptive labeler put it (odd that this observation has not been made by those computer scientists pushing Deep Learning and Big Data. I guess that nothing dampens critical awareness more completely than the kaching of the cash register):
“I used to think the machines are geniuses,” Ms. Hou, 24, said. “Now I know we’re the reason for their genius.”
Right now, this is the state of the art. All discussion of moving to unsupervised, uncurated learning is, at this time, idle talk. The money is in labeled data that uses the same old methods we long ago understood would not be useful for understanding either human or animal cognition. What makes humans and animals different from machines is what they come to the learning problem with; lots and lots of pre-packaged innate knowledge. Once we have a handle of what this is we can begin to ask how it works and how to put it into machines. This is the hard problem. Sadly, much of AI seems to ignore it.