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Researchers: Are we on the cusp of an ‘AI winter’?

bbc.co.uk

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Re: Researchers: Are we on the cusp of an ‘AI winter’?

#11

Post by etaioinshrdlu »

ForHackernews wrote: post #10
etaioinshrdlu wrote: post #2

I think the total economic impact of AI will be greatest for tasks that output high-dimensional data, such as GANs. For the simple reason that it can replace a lot more human labor. A great many jobs could be augmented with such tech. Furthermore, I think the results from GPT-2 and similar language models show that researchers have found a scalable technique for sequence understanding. They are likely to just work be…

Does GPT-2 really "understand" anything? I feel like this is pretty quickly going to devolve into a semantic argument, but having interacted with some trained GPT-2 models, it seems to produce only what Orwell would have called duckspeak[0]. There's very clearly no mind behind the words, so it's hard for me to credit it with understanding. [0] http://www.orwelltoday.com/duckspeak.shtml

I think the only time a system can be truly be said to understand something is when its answers are derived from logic (such as old school symbolic AI). No matter how good current statistical approaches get, they won't meet that bar.

However, I do believe we see evidence of approximate logical reasoning in these models, as well as the concept of abstraction.

Furthermore we can take statements generated with statistical techniques and validate them mechanically with older techniques. This is basically what recent work in automated theorem proving using deep learning is about.

Generating logical statements using heuristics and then validating them mechanically also sounds like a reasonable approximation of what a human often does, speaking as a human.

Re: Researchers: Are we on the cusp of an ‘AI winter’?

#12

Post by ForHackernews »

etaioinshrdlu wrote: post #11
ForHackernews wrote: post #10

Earlier quoted context omitted.

Does GPT-2 really "understand" anything? I feel like this is pretty quickly going to devolve into a semantic argument, but having interacted with some trained GPT-2 models, it seems to produce only what Orwell would have called duckspeak[0]. There's very clearly no mind behind the words, so it's hard for me to credit it with understanding. [0] http://www.orwelltoday.com/duckspeak.shtml

I think the only time a system can be truly be said to understand something is when its answers are derived from logic (such as old school symbolic AI). No matter how good current statistical approaches get, they won't meet that bar. However, I do believe we see evidence of approximate logical reasoning in these models, as well as the concept of abstraction. Furthermore we can take statements generated with statistic…

> Generating logical statements using heuristics and then validating them mechanically also sounds like a reasonable approximation of what a human often does, speaking as a human.

I think I agree with that, but I might add that humans who understand a topic well can also make novel connections and uncover further implications that might seem illogical at first glance. This process of "insight" seems poorly understood by everyone, but I think it goes beyond validating heuristic intuition.

Re: Researchers: Are we on the cusp of an ‘AI winter’?

#14

Post by _bxg1 »

mindcrime wrote: post #3

No. Maybe an "AI Fall", but I doubt there will ever be another true "AI Winter". The AI we have today is too good, and creates too much value... at this point, there is no longer any question as to whether or not there is value in continuing to research and invest in AI. What will happen, almost without doubt, is that particular niches within the overall rubric of "AI" will go in and out of vogue, and investment in p…

We could still have the bottom fall out of the term "AI", since there's a big gap between the present reality - no matter how useful - and the aspirational nature of the phrase "Artificial Intelligence". Take any business that brands itself as an "AI startup", any quote from Mark Zuckerberg about solving Facebook's content problem with AI, etc., and replace "AI" with "statistical algorithms" and it just doesn't have nearly the same ring to it. That alone means we're due for some kind of big correction.

Re: Researchers: Are we on the cusp of an ‘AI winter’?

#15

Post by allovernow »

thrower123 wrote: post #8

I've been waiting for the hype and marketing to collapse for a few years. Probably the fastest way to tarnish public perception of AI would be to keep pushing "AI-enhanced" products in front of the consumer as has been done. These things tend to demo well and have a nice cool factor for the first fifteen minutes or so, but after any kind of prolonged usage the limitations and rough-edges come up quick.

This is brand new technology. It's going to take a few years to reliably productionize - and most of the applied solutions will look nothing like the research. Many real world problems are going to combine multiple neural nets into systems with specific applications and there's a lot of detail to work out.

The hype may collapse in the short term, but that's only because many of the first movers are stereotypical tech startups who overpromise without truly understanding the problem or solution spaces and therefore underdeliver.

But, speaking from personal experience, some of the tech has already been proven - one example is massively accelerated modeling as an alternative to slow finite difference/finite element simulation with 99% accuracy, which will in the next 6-12 months totally change the approach to a wide range of modeling problems, and enable a totally new form of work where instead of setting up a model and waiting days or weeks, one may iterate effectively in real time. There are emerging solutions to knowledge management and "intelligent" data harvesting, where ML outputs are being manipulated in a rudimentary form of reasoning. Think specialized industries like petroleum, mechanical engineering, EM engineering - plenty of "layman" related features like recommendation engines are going to flop, but the cat is out of the bag for heavy industrial knowledge work. Just give it some time - we are on the cusp of a monumental leap in R&D across the spectrum of human endeavor. Very exciting times.

Re: Researchers: Are we on the cusp of an ‘AI winter’?

#16

Post by KaoruAoiShiho »

thrower123 wrote: post #8

I've been waiting for the hype and marketing to collapse for a few years. Probably the fastest way to tarnish public perception of AI would be to keep pushing "AI-enhanced" products in front of the consumer as has been done. These things tend to demo well and have a nice cool factor for the first fifteen minutes or so, but after any kind of prolonged usage the limitations and rough-edges come up quick.

The hype only started in 2015ish, how many years could you have been waiting for it to collapse?

Re: Researchers: Are we on the cusp of an ‘AI winter’?

#17

Post by mark_l_watson »

I have worked in the field since 1982, so I have experienced “the need to work on other things for a while” to earn a living.

My prediction is that we are going to see a small revolution in cost reduction: hardware for deep learning will get cheaper; great educational materials like fast.ai and Andrew Ng’s lessons will increase the hiring pool of people who know enough to be useful; the large AI companies will continue to share technology and trained models to help their hiring funnel and general PR; programmer less modeling will really start to be a real thing.

Re: Researchers: Are we on the cusp of an ‘AI winter’?

#18

Post by Findeton »

rococode wrote: post #5

I think there's an interesting disconnect right now between research and practice. Cutting-edge research does feel like it's reaching a plateau - across most AI fields even "major" breakthroughs are only gaining a couple percentage points and we're probably starting to hit the limits of what current approaches can achieve. When the state-of-the-art is 97% on a task, there's only so much room for improvement. Yoav Gol…

I have some hope that research like what Numenta is based upon will lead us closer to an AGI.

Re: Researchers: Are we on the cusp of an ‘AI winter’?

#19

Post by cbanek »

> While AGI isn't going to be created any time soon, machines have learned how to master complex tasks like:

> translating text into practically every language

Note: they said they have mastered these tasks.

Yeah... I'm not sure a lot of native speakers would agree. Here's a great example of using Google Translate to automatically translate a video game.

https://www.youtube.com/watch?v=_uNkubEHfQU

> Driving cars

I'm not so sure about that one either.

I think we're in the valley that AI can do a lot of things, but are hitting limits in accuracy where humans are still better at some of these things sometimes. That is, the AI isn't always better than humans, even at a specific, non-general task.

Now don't get me wrong, we've made a lot of progress, but I wonder if we can get these things to a place better than humans before the next economic recession. I think the biggest risk to AI is having the money dry up. Right now the hype is strong and the money is (nearly) free. If one of those changes, we could put this back on the shelf for another decade. If we go into a recession, labor will be cheap, so why bother automating with AI?

For example, we had self driving freeway cars back in the 90's.[0][1] Here's one of the lessons learned:

> In 1987, some UK Universities expressed concern that the industrial focus on the project neglected import traffic safety issues such as pedestrian protection.

And who doesn't remember the brilliant Dr. Sbaitso, my childhood therapist. [2]

[0] https://en.wikipedia.org/wiki/Eureka_Prometheus_Project [1] https://www.youtube.com/watch?v=I39sxwYKlEE [2] https://en.wikipedia.org/wiki/Dr._Sbaitso

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