If you can make it to London, Anders is doing a 2 hour WBE talk on Saturday the 22nd. There’s also the option of lunch before and pub after.

If not, they’re planning to webcast it. But the event is free, and Anders is amazing to listen to and debate with, so I recommend coming.

The report does not claim that WBE will happen before other AI approaches succeed; this question is not addressed. The report does not claim that we ought to try to develop WBE; the issue desirability is not addressed. The report also does not address safety issues, nor does it discuss the potential socio-economic consequences of WBE. We omitted these issues, not because we deem them unimportant, but because we thought it best to start by trying to create some basic technical understanding of the prospect and the challenges it involves. We hope to address these wider questions in future work, or to stimulate others to do so.

That being said, WBE along with all other advancements in our understanding of brain-cognitive science will slowly give us more and more of the picture and engineers will naturally use that knowledge to build technology based on it. The end result of WBE will not be a functioning human-like intelligence in a box, but will be theory and algorithms of how the brain processes information. This in turn can and probably will be used to build intelligent machines by piecing together the necessary parts as we see fit. An analogy is we can model an ant colony digitally and the result is not to have a digital ant colony running around on screen (may have entertainment value but little else), but better internet routers based on the principles discovered. Already, biologically based algorithms for machine vision are surpassing all other attempts thus far and that trend will continue.

I think a combined approach of current AI/engineering methods along with the new tools and ideas that computational neuroscience provide will be the best route towards intelligent machines of value to society.

I used to dance tango with a neuroscientist a lot. I once asked him this question myself, for which he had an interesting theory, based on discoveries about dreaming. Of course when we dream, the hippocampus sets up a slow wave, to which the amydagla contributes by somehow encouraging or activating so-called PGO waves from other parts of the brain, to set important visual centers in motion and thus coherently bring images to the dream.

All this stuff is happening when we sleep, and somehow the main scanning brain wave goes out to “sweep up” all these events so we can experience them at the level of our coherent selves. (Because even when I sleep I wake up and realize that dreams have happened to “me.”)

Said dancing neuroscientist argued therefore that brainwaves were perhaps important in coordinating our brain parts and gathering up all the disjointed crazy, million things happening at once perceptual input and allowing us to have an understandable, meaningful “experience” out of that. An important thing to note is that of the four kinds of brainwaves, while one predominates, they are all always there, a little bit.

So while we are in the brainwave state we call “beta,” chatting away, there is also always a trace amount of the other brainwaves, even the delta we associate with sleep. It may be that even when you are actively awake, small parts of your brain are actively asleep. I now use this as a convenient excuse all the time.

It may well be possible to simulate this more simply, but you would have to understand the function.

DARPA’s efforts so far do not seem to be on a scale proportional to the scale of the opportunity the field represents.

The NSA has bigger computers and smarter employees, and so might also have a shot. They might keep their superintelligence chained up in the basement, though.

In both cases, I suspect the problem is vision and interest. Governments don’t exactly have a stellar record for innovaton in computer science. ARPANET was cool – but since then the torch has mostly been carried by companies. Maybe governments will muscle in on the field later on, when they can better see what is likely to happen.