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I see nothing in these "neuromorphic" architectures than hogwash trying to bullshit governments into giving them money. There's no conceptual advancement offere
by return0 10y ago
I see nothing in these "neuromorphic" architectures than hogwash trying to bullshit governments into giving them money. There's no conceptual advancement offered by these computers that can't be simulated with matlab. Until the day when we actually learn how neurons work, these will just be extremely premature optimizations.
- deleted 10y ago[deleted]
- p1esk 10y agoThese designs are advances in the field of computer architecture. They look at how brain processes information for ideas to make hardware more efficient, for some applications (such as pattern matching). Did you expect something more?
- return0 10y agoThey use very rudimentary sketches that have little to do with real neurons. ANNs have been mimicking these things in a slightly lower detail since the 60s. We can do better pattern matching with ANNs.
- p1esk 10y agoI think you might be confused about terminology. Neuromorphic computing is running some known ANN model directly in hardware. Why do we want it? Because ANN models in software work well for pattern matching, and we want to speed it up/make it more efficient.
- return0 10y agoNope, ANN's and deep learning are not used by these boards (Neurogrid, zeroth, truenorth).
- p1esk 10y agohttps://arxiv.org/abs/1603.08270 https://arxiv.org/abs/1603.08270 They have been designed, and are being used either for more efficient pattern matching, or to speed up brain simulations (again, using known neuronal models). You seem to expect something else from neuromorphic computing, why?
- return0 10y agoI stand with Yann Lecun's criticism on the article: https://m.facebook.com/yann.lecun/posts/10152184295832143 https://m.facebook.com/yann.lecun/posts/10152184295832143 > [the truenorth team had] to shoehorn a convnet on a chip that really wasn't designed for it. I mean, if the goal was to run a convnet at low power, they should have built a chip for that. The performance (and the accuracy) would be a lot better than this. They used their 'neuromorphic' chip in an explicitly non-neuromorphic way, basically approximately mapping deep learning processes to their chip. There is very little neuromorphicity (brain-likeness) about it (plasticity rules out of their ass, for starters). And they still get less than state-of-the art performance in most tasks! I expect 'neuromorphic' to be used when sound neuroscience is used in large scale implementations that allow us to actually simulate parts of the brain. Anything else, we call it what it is, ANNs.
- p1esk 10y agoWell, none of those chips are brain-like at all. For example, TrueNorth is fully digital, it uses separate compute/memory blocks, signal multiplexing, signal encoding, routing protocols, instruction set, etc, none of which is in any way related to what brain is doing. What makes you think it's "neuromorphic"? Whether you like it or not, get used to people calling their hardware ANN implementations "neuromorphic".
- return0 10y agoNope, neuromorphic means the hardware would simulate the neurobiology, not ANNs. More practically, they would never publish in Science if their title was "printing ANNs in hardware".