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"Machines need a lot more data than humans do in order to get smart" - is that true?
by nuclx 8y ago
"Machines need a lot more data than humans do in order to get smart" - is that true?
- zozbot123 8y agoThe general answer is yes - it's the "one shot learning" problem. But humans also have access to a large (if not very well defined) amount of data via background knowledge, which plausibly enables them to apply stronger, more effective priors to any one task.
- lordnacho 8y agoThis is the thing. Machines start on a blank slate each time, humans never. So how do you compare the amounts of data needed?
- ars 8y agoSo try it: Teach a computer about animals in general. Then show it a single example of a new animal it has never seen, and see how well it would do at telling you if challenge images are or are not that animal. It's not even going to be close to what a human would manage. It's not because of the data, it's because a human understands what he's seeing.
- lordnacho 8y agoThen you're comparing a machine that's never seen anything but animals against a human that has no separation between different kinds of data and can't start on a blank slate. I may have all sorts of images in my mind, allowing me to make the distinction?
- dmurray 8y agoThis doesn't sound too different from face recognition systems where you train a network to be able to tell if two faces are the same or different. I don't know what the state of the art in animal recognition is, though.
- Doubleslash 8y agoYes. On average the human brain just needs dozens or hundreds of examples (turns, exercises, you name it) to "learn" something. A decent machine learning model needs hundreds of thousands to millions of samples to gain good confidence and can still be fooled easily afterwards with subtile changes.
- bumby 8y agoYour wording is interesting here. Do you mean humans need less data to feel confident or less data to make accurate predictions compared to a ML model? Sorry if I'm parsing your words too much here, just genuinely curious
- m0zg 8y agoActually, I don't think this is strictly speaking accurate. In order to train from those dozens/hundreds of samples, human brain needs to first be developed enough by accumulating experience from billions of samples in related domains. This "pre-training" process literally takes years, and it still does not sufficiently prepare some people for some tasks.
- kkarakk 8y agoi think it's important to note when people talk about machines vs people they always think about ideal machine vs ideal person - a rigorously educated athletic genius that can infer links between things with a couple of hours of study at most & infer future results of actions with a couple of seconds of thought. most people aren't like this but on average engineers who are truly innovatively thinking about these problems and creating solutions are. it is just the way it is
- deleted 8y ago[deleted]
- sbov 8y agoI just think machines are good at some things, and people are good at others. If it really took billions of samples in related domains we wouldn't develop nearly as fast as we do after being born.