[kylebrown]

> Can we entirely rule out the possibility of AI researchers making advancements over time, and then eventually some research lab building one that's super intelligent compared to us? Why?

That's not the thing we should be worried about, or at least that's the point I got from the article. The thing we should be worried about is the way machine learning is applied in the here-and-now: the ethics of big data social networks, the robustness of complex (API-driven) systems, and so on. I fully agree that these issues are much more pressing and worrying than some emergent super-intelligence.

But I thought the article was weak in its discussion of dreams, creativity, and linear "flat data". It links to a June 2015 popular mechanics article about applying a genetic search optimization algorithm to discover gene regulatory networks, downplaying it as not-true-intelligence. But it does not mention deep neural networks and their higher-dimensional abstractions, particularly the psychedelic "inception" images.

The author also mentions "linear reasoning", and says he expects we'll learn more about intelligence from stem cell and Alzheimer's research, and the "tissues surrounding neurons, and the roles they play in contextual regulation." As if to set up some dichotomy between machine and biological intelligence. But what about deep neural networks?? I'm not sure how that would affect the author's arguments, but I'd like to see it discussed.