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Glad to see this articulated so well. The 'Overall' paragraph sums up thoughts that had been in the back of my mind for months. Plus, hey, it's Gwern. If you're

Glad to see this articulated so well. The 'Overall' paragraph sums up thoughts that had been in the back of my mind for months. Plus, hey, it's Gwern. If you're reading this: you're an inspiration, man. What is still unclear -- to me at least -- is the technical challenges that lie ahead of this "neural networks all the way down" approach. I get the impression we'll need quite a few breakthroughs before usable Agent AIs are a thing. Insights on the order of importance as, say, backpropagation and using GPUs.

visarga 10y ago
> we'll need quite a few breakthroughs before usable Agent AIs are a thing. Insights on the order of importance as, say, backpropagation and using GPUs. I think a 10x-100x increase in efficiency is going to come soon, based on more research into efficient hardware and efficient models. New algorithms, new hardware and especially a lot of money and talent invested in research are going to power the next step.
sapphireblue 10y ago
Meta- reinforcement learning could prove to be such breakthrough, see [1],[2]. Also next generation ASIC accelerators (Google's TPU, Nervana) can give 10x increase in NN performance over a GPU manufactured on the same process, with another 10x possible with some form of binarized weights, e.g. BNN, XNOR-net. There are also interesting techniques to update the model's parameters in a sparse manner. So, there certainly is a lot of room left for performance improvements! 1. https://arxiv.org/abs/1611.05763 https://arxiv.org/abs/1611.05763 2. https://arxiv.org/abs/1611.02779 https://arxiv.org/abs/1611.02779