>The recent leap in machine learning has felt rather hyped to me. I don't think AGI is near. I've always thought it's never too early to start allocating signi

>The recent leap in machine learning has felt rather hyped to me. I don't think AGI is near. I've always thought it's never too early to start allocating significant resources to AGI research and safety given the potential impact. That said, I've up until very recently agreed with your take on the situation. What changed my mind was an article detailing the latest advances in silver nanowire mesh networks.[0] I knew neural computing was a thing, but not that we already had a computing substrate capable of self-organizing its own neural architecture based entirely on external input, with power requirements analogous to the human brain. No firmware or software required. One could say that human physiology remains far more complex just on the substrate front alone, what with the brain being an incredibly complex, delicate balance of chemicals and heterogeneous cells. However, this particular artificial substrate is already succeeding in basic learning tasks, despite the fact it's far simpler. I steongly suspect we've figured out at least one artificial computing substrate not only capable of, but perhaps well-suited towards producing AGI, and that it's just a matter of scaling it. Of course, once you scale the technology sufficiently, the question then becomes how to architect and train it into an AGI. You say as much above, but I suspect the architecture need not be human to be a threat, or to otherwise become extremely powerful. [0] https://www.quantamagazine.org/a-brain-built-from-atomic-switches-can-learn-20170920/ https://www.quantamagazine.org/a-brain-built-from-atomic-swi...