Curiously, the things brains tend to be really good at are often NP-hard problems if you require the optimal solution. But this is really just a curiosity because brains don't calcualte the optimal solution and what they do calculate is good enough. So the question for me is whether we should even be trying to do any of this stuff with computers in the first place. You might be on to something there. Imagine a self-driving car controlled by moths reacting stimuli...
Growing organs for transplants or meat for consumption is one thing, but using the brain of a living creature purely as a tool is a whole different kind of horror.
http://www.research.ufl.edu/publications/explore/v10n1/extra...
You'll probably be able to find earlier examples.
What a silly thing to say. It's pretty depressing that there are obviously scientists, engineers, and investors out there with the arrogance and/or naivete to believe that software neural nets are something more than mere conceptual mimicry of layman-level theory about how actual brains work.
What's really sad is that however good brains are at what they do, it's also pretty silly to think that emulating them more closely is a good way to improve digital computer systems, which have entirely different strengths. Yes, take what we can learn from how brains process information efficiently, but don't try to force an incomplete and inaccurate model of brain function onto non-biological hardware and expect it to be anything more than a poor brain and a poor computer.
It just goes "octopamine ... something something, biological neural nets don't use backpropagation".
kind of like smell this go left, smell this go right...you win...reward previous actions.
