ythn, you should start where we had the combustion engine, since it was a source of huge amounts of power (the power density of the fuel) that was already effectively being turned into motion.

What I'm saying is that the server farms @ Google, Amazon, and elsewhere, are at the stage of the "combustion engine" -- not just 'powerful enough', but more powerful than necesssary. I base this on a count of the number of neurons in the human brain, their rough topology and connectedness, how quickly and often they fire, etc.

In that sense, I think you will find it almost impossible to conclude that our server farms today do not have sufficient power to simulate 86 billion neurons' 7k connections each, at a lowly few hundred herz. They are not even more connected than we are able to simulate, precisely because we can saturate links over a million roundtrips before we meet brain's realtime behavior. (Or at least, thousands of times.)

So perhaps "we are just imitating birds by gluing feathers to cardboard wings, flapping them, and hoping flight just sort of happens" -- but while having an engine attached that's at least an order of magnitude more powerful than is required to achieve flight.

In that context, the story we're replying to is like a video of someone achieving a 2 second flight - with a lot of feathers flying everywhere. It might not seem like much, but given what we know an 86-billion-neuron neural net is capable of, it is exciting.

The results of AI based on neural nets that I see being posted every single day are absolutely astounding.

this is happening right in front of your eyes. you're witnessing the birth of flight.

no, the engines won't fly the way birds do -- but they're more than powerful enough to start flying, and you are seeing this every single day.

By the way, you know there's not a particular push toward trying to make neural nets that are self-conscious or feel pain, etc? This just isn't a primary goal of researchers at this very second.

Just as flight engineers don't really try to make ornithopters. We have better and more powerful things to be doing.

this is an absolutely miraculous time. And you're not seeing it - which is sad.

This isn't some kind of pipe dream. These are results coming out every single day.

Here's a neural net designed to make horror art out of normal photos:

http://nightmare.mit.edu/

And that's just one thing out of many. Nuance's Dragon systems have practically eliminated the entire profession of medical transcriptionist. (Just google regarding 'medical transcription dead' without quotes to find people from that industry reporting on its demise.) Becoming a medical transcriptionist today is like going to typewriter repair school. Because speech recognition techniques based on machine learning have gotten that good.

Go, an incredibly nuanced game with a staggering possibility space, has fallen to machine learning competing with a lifetime of competitive human mastery.

It doesn't matter in what order or how the next breakthroughs come that go toward sentient or at least very intelligent interaction. We know what the limits are. And we know based on the topology and computation involved, that we have massively more than enough horsepower.

so while you might point to flying feathers and crashing airplane and deride it, I think about the jet engine behind those flying feathers and my heart skips a beat when I see it sustain flight for 2.3 seconds before producing "A hundred and half hour ago" like a human toddler blabbering incoherently and without even understanding those words.

Because I know what else AI has been accomplishing, and I know the horsepower behind it. you need to expand your thinking and realize that our algorithms and machine learning techniques are playing catchup with hardware that has been sitting around being dumb.

That's right: computers have just been sittin' around, bein' dumb, while they have all the computational power necessary to surpass humans in every realm of neural computation. mark my words, ythn. no pipe dream involved.