> There have been no new breakthroughs in this area. Most of the research being done is in application of what we have known for decades in specific areas, with minor insights into tweaks and uses of combinations ...
There are 2 huge problems with that:
1) nobody is trying to "embody" an intelligence with any sort of research project behind it. Nobody's even trying to create an artificial individual using neural networks. There are several obvious ways to do this, so that's not really the problem.
Therefore I claim that your implied conclusion, that it isn't possible with neural networks somewhere between premature and wrong.
2) What if the difference between an ANN and our brain is a difference of scale and ... nothing more ? We still do not have the scale in hardware to get anywhere near the human brain, and just so we're clear, the differences are still huge.
Human neocortex (which is roughly what decides on actions to take): 100 billion neurons
Human cortex (which is everything that directs a human action directly. Neocortex decides to throw spear and the target, cortex aims, directs muscle forces, moves the body and compensates for any disturbance like say uneven terrain): another 20 billion neurons.
Various neurons on the muscles and in the central nervous system directly: a few million (mostly on the heart and womb. Yes, also in men, who do have a womb it's just shriveled and inactive). They're extremely critical, but don't change the count very much.
AlphaGo 19x19x48, times 4 I think. About 70000 neurons, and that does sound like the correct number for recent large-scale networks.
A human neuron takes inputs from ~10000 other neurons, on average. A state-of-the-art ANN neuron takes input from ~100, and since it's Google and they've got datacenters, AlphaGo was ~400.
So the state of the art networks we have are on par with animal intelligence of the level of a lobster, ant and honeybee. I think it is wholly unremarkable and understandable that these networks do not exhibit human-level AGI.
What is remarkable is what they can do. They can analyze species from pictures better than human specialists (and orders of magnitude better than normal humans). They can speak. They can answer questions about a text. They can ... etc.
Give it a few orders of magnitude and there will be nothing these networks don't beat humans on.
There are 2 huge problems with that:
1) nobody is trying to "embody" an intelligence with any sort of research project behind it. Nobody's even trying to create an artificial individual using neural networks. There are several obvious ways to do this, so that's not really the problem.
Therefore I claim that your implied conclusion, that it isn't possible with neural networks somewhere between premature and wrong.
2) What if the difference between an ANN and our brain is a difference of scale and ... nothing more ? We still do not have the scale in hardware to get anywhere near the human brain, and just so we're clear, the differences are still huge.
Human neocortex (which is roughly what decides on actions to take): 100 billion neurons
Human cortex (which is everything that directs a human action directly. Neocortex decides to throw spear and the target, cortex aims, directs muscle forces, moves the body and compensates for any disturbance like say uneven terrain): another 20 billion neurons.
Various neurons on the muscles and in the central nervous system directly: a few million (mostly on the heart and womb. Yes, also in men, who do have a womb it's just shriveled and inactive). They're extremely critical, but don't change the count very much.
AlphaGo 19x19x48, times 4 I think. About 70000 neurons, and that does sound like the correct number for recent large-scale networks.
A human neuron takes inputs from ~10000 other neurons, on average. A state-of-the-art ANN neuron takes input from ~100, and since it's Google and they've got datacenters, AlphaGo was ~400.
So the state of the art networks we have are on par with animal intelligence of the level of a lobster, ant and honeybee. I think it is wholly unremarkable and understandable that these networks do not exhibit human-level AGI.
What is remarkable is what they can do. They can analyze species from pictures better than human specialists (and orders of magnitude better than normal humans). They can speak. They can answer questions about a text. They can ... etc.
Give it a few orders of magnitude and there will be nothing these networks don't beat humans on.