This AI Boom Will Also Bust

For user behavior: bots, clickfraud/clickjacking, bored teenagers, competitors who are sussing out your product, people who got confused by your user interface, users who have Javascript disabled and so never trigger your clicktracking, users who are on really old browsers who don't have Javascript to begin with.

And then there's bugs in your data pipeline: browser (particularly IE) bugs, logging bugs, didn't understand your distributed databases's conflict resolution policy bugs, failed attempts at cleaning all the previous categories, incorrect assumptions about the "shape" of your data, self-DOS attacks (no joke - Google almost brought down itself by having an img with an empty src tag, which forces the browser to make a duplicate request on every page) which result in extra duplicate requests, incorrectly filtering requests so you count /favicon.ico as a pageview, etc.

What does it mean? I'd say the ability to perceive depth is pretty useful.

I think what we're seeing is an explosion of new approaches to computerized problem solving made possible by huge amounts of data and enormous computing resources. A lot of what has become possible in the last couple of decades is indeed new, but the apparent rapid advance is really just a matter of applying the brute force of a massively upgraded ability to process huge quantities of data in parallel, and this has led us to make erroneous assumptions about future progress in these areas.

Basically, these are new solutions to new problems, and we're rapidly seeing the easy 80% of this new generation of "AI" happen and it seems magical. But soon enough we'll hit the wall where further progress becomes harder and harder and brute force approaches are no longer sufficient to achieve interesting results.

It is not suffering from hype. There is too little hype. People are vastly underestimating what is about to happen.

See my comments here:

https://news.ycombinator.com/item?id=13079598

under our recent article " Artificial Intelligence Generates Christmas Song".

Basically, if there is no pixie dust that makes humans intelligent, and instead it is a matter of the architecture of the brain and the first few years of supervised sensory input, then neural net breakthroughs (which use a similar architecture/topology) have the potential at any moment in time to break through and match general human intelligence.

What I mean is that if someone sent back source code from 80 years from now, but we had to run it on a bunch of Amazon / Google servers in a server farm, we're pretty much guaranteed to have enough computing power to do so!

(This is a combination of the number of neurons, their number of connections, and their very slow speed.)

We have the hardware.

Now: we do not actually have the source code from 80 years from now that we can go ahead and run on those machines.

So, we're at like heavier-than-air travel right before the Wright Brothers flew at Kittie Hawk. Except we have like jet engines already -- just no way to design them into something that flies.

I think that AI is vastly underrated and I watch with incredible interest every single breakthrough.

For the second category above, ML built into products or engineering solutions, Alphago surprised me, because Go had an intractibly large possibility space, it's not in any sense subject to brute-forcing or exhaustive search.

Dragon's Natural dictation surprised me in that using its model its able to get basically perfect dictation. I've never worked as a transcriptionist, but a small search reveals it has basically annihilated the industry of medical transcription.

These are not the big, general breakthrough.

But the big, general breakthrough is right there, somewhere. The results researchers are coming up with are astounding, and they're doing it in many cases with neural nets, quite similar to the wiring of the human mind.

The hype is faaaaaaaaaaaaaaar less than warranted for the stage that we're at. At any moment someone can put together something that achieves higher-level intelligence and can be set loose upon the world corpus of culture.

True, there are no clear indications that this is about to happen (For example: people do not extract innate language algorithms from the human genome which encodes them), so we are not exactly taking many steps that we could be trying to. As far as I know we're not even genetically engineering people to see what different parts of DNA do -- which is obviously a very, very good thing, and who would allow anyone to bear to term a child made as an experiment to see what DNA does.

But despite not going from a human starting point, the results that we are achieving in many cases match and surpass human ability - while we do know that in many cases some of their architecture is similar. I feel quite strongly that we have more than enough hardware for general intelligence - and I see advances every day that could end up going past the ppint of no return on it.

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EDIT: got a downvote, but I would prefer a discussion if you think I'm wrong.

However as ma2rten eloquently describes, for the purpose of AI research it might be beneficial to bite through the harder AI required when only having access to stereo vision.

A lot of problems are not tackled on a fundamental level. Occlusion, context, proprioception, prediction, timing, attention, saliency, etc.

A simple rat has more intelligence than whatever is behind a dashcam, security cam or webcam.