I really object to most of the ideas on this list. 5, 6, and 7, are not even AI algorithms but just applications of AI algorithms. 7, knowledge bases, is partic

I really object to most of the ideas on this list. 5, 6, and 7, are not even AI algorithms but just applications of AI algorithms. 7, knowledge bases, is particularly concerning on that list. A truly intelligent AI shouldn't require humans to input knowledge about the world into it, it should be able to learn it itself. Algorithmic Information Theory isn't really an approach to AI, but more like a theoretical basis for AI. No one can ever build a working AIXI-tl, it is designed with the assumption of infinite computing power. However they do make a good foundation for understanding why AI can work, in theory. I've argued that neural networks are a (very rough) approximation of AIXI: http://houshalter.tumblr.com/post/120134087595/approximating-solomonoff-induction http://houshalter.tumblr.com/post/120134087595/approximating... Brain simulations as stated probably won't happen. I think neuroscience research may contribute to AI research. So deep learning will absorb the ideas and use what actually works in practice. But for the most part deep learning has been evolving independently of neuroscience and that will probably continue. Artificial life is cool but really really hard to get anything interesting from. The "genome" you choose to evolve, and the environment you put it into, matter a huge amount. People have tried making computer code that can evolve, but it usually doesn't get far. Most mutations on most pieces of code just break it, rather than changing its behavior slightly. That's why deep learning is so successful. Neural nets are "fuzzy" and small changes to the parameters make small changes to the output. And you can do gradient descent on it, and see exactly what parameters to change. Rather than mutating them randomly and hoping it works better. Mostly AI just needs more computing power. The rapid drop in the price of FLOPS has enabled huge progress in AI in the past 5-10 years. And as the article states, we only have a tiny fraction of the processing power of the human brain. But as Moore's law and related exponential increases continue, we aren't very far from that. Even as transistor sizes stop shrinking, we have a long way to go with 3d architectures or specialized ASICs for AI.