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I've occasionally found that SVM's work great for one shot learning if you have good features and nicely labelled dataset. CNN's are really good at extracting features. Once you've extracted features that are generic, using an SVM as the last layer to train while keeping the CNN parameters intact yields great accuracy.

I think that's where we are really headed. A combination of deep learning, boosted trees, svm, evolutionary algos, knowledge graphs e.t.c all stitched together to build stronger AI systems.

Remember our aeroplanes don't flap wings but still carry tonnes of weight and fly half way around the world. Once we discovered fundamentals of aerodynamics a lot of supernatural things were possible.

Same with intelligence, once we discover the essentials of intelligence and mathematically formulate it, supernatural intelligence is very possible. This is the thing that really scares people. I have no idea how close we are to it, but I'm sure it will change society the way internet and mobile phones changed the world.




Wow, I had never considered superintelligence that wasn't at least at some level modeled after the human brain. That is crazy to think about. We could be at the very low end of the spectrum of intelligence I guess.


Homo sapiens is the dumbest creature able to spawn a civilization that evolution could produce.

--Accelerando


That's a good comment, and yes, SVM are very powerful in itself, they might not be "deep learning" but they're more powerful than linear learning and good for a lot of cases (as a last layer, as you mentioned, it's a good use case)

Yes, we'll have GAs building CNN architectures, or a mix of several techniques, I'm enthusiastic for what the future holds


> I'm sure it will change society the way internet and mobile phones changed the world.

It will change the entire world the way humans changed the world. And that's scary.




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