Neural nets can be programmed in any language that can handle basic math and variables.
Some will be much faster at it than others.
If you really care about performance you will use hardware acceleration instead of half-assing it on a CPU or even GPU or FPGA, such as IBM TrueNorth and SyNAPSE, which they say has the equivalent neural power of a mouse. There's nothing stopping you from just hooking up 1,000 of them in an array, if they were available to purchase for us plebs.
If you wanted to make a breakthrough in AI that frees the world from the grip of the silicon industry, and possibly summon the demon that is the super-intelligent AI of our nightmares, you would create an analog computer system to do it. I've figured out research paths to making this reality but don't have the time to invest in it myself, and I am super paranoid about the intentions of any groups willing to fund such an endeavour . To any inquiring computer engineer minds, roll around the idea of making an analog computer out of the surface of a liquid body and see where it takes you.
We are at a point where custom neural networks are becoming hardwired hardware. You can't get any faster than that, so learning to program AI will be over by the time you have learned it. It all will boil down in training it.
But you have to realize that AI is actually very energy and time consuming to do the same simple job as none AI. It is slower because you need more electronic and more power. Also you need longer lines to connect the AI cores so that also slows down. And AI that is self learning also tends to deviate from the standard. You don't want industrial processes controlled by Ai's that have different personalties if you replace them.
I think the most interesting thing to learn is to learn how to manipulate AI's. Manipulate so you can hide in the data or manipulate so you pop up in the data. And the other thing is create technology to verify if an AI has lost its mind, got manipulated by governments and advertisement agencies.
I think the idea that using any derivative of the path we've gone with silicon being the end-all to designing such systems is incredibly short sighted, not talking about you specifically, you share the standard of how people look at it.
Transistor technology can't match the power efficiency for neural nets that evolution has come up with. It's my opinion that evolution hasn't come close to scratching the surface of how far neural technology could be pushed, it was a random-ish process working within very limited constraints and materials.
Evolution had to solve the problem of how can I design a matrix multiplication, adder, and softmax function with living cells via fucking over millions of years in an extremely chaotic environment. It also has to be robust enough to survive all the crazy shit that happens to living things, this obviously must reduce potential performance.
With a much smarter engineer at the wheel than evolution, with unlimited materials, construction techniques, and extremely controlled environments, I see extraordinary and scary potential. Transistor tech will be a very useful tool as the glue for building, training, interfacing with such a system, but it will not be doing the heavy lifting.
Could you train a NN to solve the problem of how to tap on the surface of a body of water in such a way that 3 seconds later, it very briefly flashes an image of your face? Go down the rabbit hole of where that could lead.
7 comments
0 u/roznak 02 Jun 2017 20:06
What do you mean language? AI does not use language, it uses neurons. You don't program it, you feed training data.
1 u/ohnoitsaninja 02 Jun 2017 23:49
Neural nets can be programmed in any language that can handle basic math and variables. Some will be much faster at it than others.
If you really care about performance you will use hardware acceleration instead of half-assing it on a CPU or even GPU or FPGA, such as IBM TrueNorth and SyNAPSE, which they say has the equivalent neural power of a mouse. There's nothing stopping you from just hooking up 1,000 of them in an array, if they were available to purchase for us plebs.
If you wanted to make a breakthrough in AI that frees the world from the grip of the silicon industry, and possibly summon the demon that is the super-intelligent AI of our nightmares, you would create an analog computer system to do it. I've figured out research paths to making this reality but don't have the time to invest in it myself, and I am super paranoid about the intentions of any groups willing to fund such an endeavour . To any inquiring computer engineer minds, roll around the idea of making an analog computer out of the surface of a liquid body and see where it takes you.
1 u/roznak 03 Jun 2017 02:03
We are at a point where custom neural networks are becoming hardwired hardware. You can't get any faster than that, so learning to program AI will be over by the time you have learned it. It all will boil down in training it.
But you have to realize that AI is actually very energy and time consuming to do the same simple job as none AI. It is slower because you need more electronic and more power. Also you need longer lines to connect the AI cores so that also slows down. And AI that is self learning also tends to deviate from the standard. You don't want industrial processes controlled by Ai's that have different personalties if you replace them.
I think the most interesting thing to learn is to learn how to manipulate AI's. Manipulate so you can hide in the data or manipulate so you pop up in the data. And the other thing is create technology to verify if an AI has lost its mind, got manipulated by governments and advertisement agencies.
0 u/ohnoitsaninja 03 Jun 2017 02:22
I think the idea that using any derivative of the path we've gone with silicon being the end-all to designing such systems is incredibly short sighted, not talking about you specifically, you share the standard of how people look at it.
Transistor technology can't match the power efficiency for neural nets that evolution has come up with. It's my opinion that evolution hasn't come close to scratching the surface of how far neural technology could be pushed, it was a random-ish process working within very limited constraints and materials.
Evolution had to solve the problem of how can I design a matrix multiplication, adder, and softmax function with living cells via fucking over millions of years in an extremely chaotic environment. It also has to be robust enough to survive all the crazy shit that happens to living things, this obviously must reduce potential performance.
With a much smarter engineer at the wheel than evolution, with unlimited materials, construction techniques, and extremely controlled environments, I see extraordinary and scary potential. Transistor tech will be a very useful tool as the glue for building, training, interfacing with such a system, but it will not be doing the heavy lifting.
Could you train a NN to solve the problem of how to tap on the surface of a body of water in such a way that 3 seconds later, it very briefly flashes an image of your face? Go down the rabbit hole of where that could lead.
0 u/iate2manytacos 02 Jun 2017 21:33
I don't know... but since the other answers appear to be shit I'd make an educated guess at C++, Python, or Java.
0 u/Drenki 03 Jun 2017 02:35
https://www.google.com/search?q=neural+net+services&oq=neural+net+services&aqs=chrome..69i57.2109j0j7&client=ubuntu&sourceid=chrome&ie=UTF-8
0 u/0x2328 03 Aug 2017 16:29
I would recommend Python...