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But surely we can improve modern computing devices architecture by taking a look at the computing advantages the brain takes in order to achieve its desired tas
by TheFiend7 7y ago
But surely we can improve modern computing devices architecture by taking a look at the computing advantages the brain takes in order to achieve its desired tasks.
Don't forget humans are one of the most expensive resources and nothing can really replace them for even a vast majority of non-physical jobs. So if we could build computing devices that potentially solve some of these problems, needless to say, the productivity boosts would be plentiful.
Secondly, we aren't even close to being able to model anything relatively close to the computational capabilities of the human brain because we don't even understand the human brain. So your comments on highly parallel but slow and fast but no so parallel don't make a lot of sense.
For example take MapBox's new vision SDK. It's able to perform semi-decent feature extraction on the road while people drive via a camera. Well guess what I would absolute stomp the vision SDK on accuracy for every feature it thinks it identified, not only that, I am capable of identifying an order of magnitude more features than it can, not only that, but I'm able to identify new features on the fly and even guess with greater accuracy what they are.
So yeah, there are a plethora of functional yields that we have yet to achieve with some of the most powerful computers in the world that are achieved by the human brain every day. Which could be indicative of maybe both a resource, but also an architecture problem.
- mojuba 7y ago> I would absolute stomp the vision SDK on accuracy I suspect our recognition abilities may in fact be worse than that of a good SDK but we have the advantage of a general real world experience. Bit of a simplified example, in order to recognize a dog you should have seen a lot of various animals, have a basic knowledge of anatomy, animal behaviour etc. A lot of the times recognizing the context helps too: e.g. something on a lead ahead of a walking human in the street, likely a dog - you need only a very quick confirmation to say it's definitely a dog, etc. I also think the brain does a lot of tree searches with optimizations (which are never perfect), and it's where the brain's parallel architecture proves to be beneficial. Intuitively though, modern computers are still not powerful enough to perform the same tasks albeit mostly sequentially. I believe we'll get there and I think AGI in a simplified virtual/gaming environment is the best place to test our approaches.