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An understanding of AI’s limitations is starting to sink in

economist.com

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Re: An understanding of AI’s limitations is starting to sink in

#321

Post by pmezard »

MiroF wrote: post #296
pmezard wrote: post #276

Earlier quoted context omitted.

> To be perfectly honest, it surprises me the extent to which ML naysaying seems to be popular on HN. Maybe because there is a larger fraction of people who know or see how the sausages are made. There are cool things, but is not magical nor transformative. At least not yet.

I work in “making the sausage” - deep learning techniques have already completely transformed my field and are transforming many others. Most of the people I see naysaying don’t appear to causally work in the field, because their critiques are not the same as the ones people in the field are using.

Can you give a concrete example of deep-learning techniques which have transformed a field? Something not theoretical or confined in a lab? Something which may have changed my life?

Re: An understanding of AI’s limitations is starting to sink in

#322

Post by wpietri »

p1esk wrote: post #255
wpietri wrote: post #164

Earlier quoted context omitted.

In communication, meaning is a collaboration between writer and reader. The writer does their best to convey something; the reader does their best to understand. There's also the kind of meaning that scientists and researchers talk about when they extract knowledge from data. That's pretty different from communication; it's more a process of internal generation of notions and explanations that could later be conveyed…

a process of internal generation of notions How is this "knowledge extraction from data" process different?

Different from what? Regular communication? Because the first involves trying to sync up two minds to have the same idea. The latter involves one mind, trying to generate an idea that ends up being useful. Useful in the George Box sense: "All models are wrong, some models are useful."

Re: An understanding of AI’s limitations is starting to sink in

#323

Post by gwern »

quicklime wrote: post #165
pengaru wrote: post #154

Earlier quoted context omitted.

Ah, yes, I am using noscript. That explains it, javascript is destroying the web.

I just disabled JavaScript by setting Firefox's "javascript.enabled" flag to false, and it still renders fine for me. Here's what the HTML source looks like when I grab the page using curl: predicts that artificial intelligence ( AI) will add $16trn to the global economy by 2030 So it looks like it's coming through in caps from the server. I don't think a lack of JavaScript by itself is causing the problem...

> I don't think a lack of JavaScript by itself is causing the problem...

, however, does not do lowercasing. All it does is make the font smaller. 'AI' should be caps regardless of whether it is wrapped in or not. That implies that something in the CSS or HTML is overloading to make it lowercase, so it can be correctly transformed to uppercase smallcaps for the reasons I explain above, which it assumes will be done by the later JS (which however doesn't run under NoScript). Using just makes it an even uglier unnecessary hack...

Re: An understanding of AI’s limitations is starting to sink in

#324

Post by randcraw »

For a rather complete view of what deep learning still does not do, I recommend the work of Gary Marcus and Ernest Davis. While seeming solely critical, I think they make very good points about the limits inherent in deep learning as we know it now, and how it needs to grow to overcome those deficits.

"Rebooting AI" https://www.penguinrandomhouse.com/books/603982/rebooting-ai...

And a few articles, for audiences both popular and technical:

Deep Learning: A Critical Appraisal https://arxiv.org/abs/1801.00631

The Next Decade in AI https://arxiv.org/pdf/2002.06177.pdf

How to Build AI We Can Trust https://www.nytimes.com/2019/09/06/opinion/ai-explainability...

And a HBR podcast ("Beyond Deep Learning") https://hbr.org/podcast/2019/10/beyond-deep-learning-with-ga...

Re: An understanding of AI’s limitations is starting to sink in

#325

Post by machiaweliczny »

mjburgess wrote: post #319
tgv wrote: post #277

Earlier quoted context omitted.

My first AI teacher (even before '89) compared solving AI with neural nets to teaching pigs to fly by throwing them from a tower. Improvements come from building higher towers. There's a recent NLP model that was trained on a trillion words. It would take us 10,000 years to read or listen (no breaks, no sleep) to that many words. Problems like attention, and the relation between memory and sequential thinking haven't…

It isn't ever going to model our style of thinking. A "neural network" is just high-dimension linear regression; the idea it has anything to do with the brain is metaphorical nonesense. No algorithm running on digital hardware can emulate the biological process of animal intelligence.

Why not?

Re: An understanding of AI’s limitations is starting to sink in

#326

Post by Veedrac »

coverup wrote: post #288
TrackerFF wrote: post #278

Earlier quoted context omitted.

That's actually something ML is incredibly useful at, when it comes to machines with sensors - failure prediction / anomaly detection, etc. In the industry, (preventive) maintenance takes up a pretty huge chunk of resources. It's something techs need to do often, and it's often a laborious task, but it's obviously done to reduce downtime. So the business insight, as they like to call it, is to reduce costs tied up to…

Yep, you and the user you're replying to are both right in different ways. One thing's for sure - machines don't generate "insights" on their own. Let's define an "insight" as "new meaningful knowledge", just for fun. We could talk about what comprises "new" and "meaningful" but it would be beside the point I'm making. In a supervised learning problem, the range of possible outputs is already known, meaning the model…

This is demonstrably false; AlphaGo made significant new discoveries, for example.

Re: An understanding of AI’s limitations is starting to sink in

#327

Post by bsenftner »

laingc wrote: post #96
mtgp1000 wrote: post #11

I'm not sure how anyone who's watched the exponential growth of a brand new domain can pick a point today to and say that things aren't as good as we expected. What may have happened was that some eager CEOs have overpromised on timelines and resources. But the revolution is coming, ML is already starting to change society. We're building the tech. Right now. The author does not even realise the immeasurable potentia…

I completely agree with this. Let me add a non-US perspective that may surprise some people. I think a big part of what is holding back many companies from making effective, genuine, real-world use of AI is that a significant majority of the individuals involved are bad at their jobs . On the business side, there is an widespread unwillingness to acknowledge that technical people may be better placed to make decision…

I think you've identified the basic, classic difference between artists/thinkers/scientists and everyone else: just as a musician can be given a piano and in time they create complex compositions, those that can see and operate in abstract conceptual spaces will see and use AI to create wonderfully complex compositions everyone else will be slackjawed in awe. This is human nature. AI is not an intelligence player, it's an instrument to find and tune like steroids one's own intelligence. Just like a piano, AI is useless to most people, because they do not have the artists/thinkers/scientists drive and comfort with abstract problems that are easier with even the most basic AI.

Re: An understanding of AI’s limitations is starting to sink in

#328

Post by pgwhalen »

cjhanks wrote: post #59

We have also been watching these machine learning models for 6 months: - increase the volatility in virtually every financial market they touched - be exploited by adversarial learning networks to amplify funded propaganda as news - use poorly contrived sentiment analysis to generate incomprehensibly meaningless news headlines These non-linear "function approximators" have absolutely unpredictable and insane non-line…

I’m curious if you have a source that ML has increased financial markets volatility.

Re: An understanding of AI’s limitations is starting to sink in

#329

Post by bildung »

govg wrote: post #317
bildung wrote: post #306

Earlier quoted context omitted.

Both voice recognition had first working research machines in the 1950s. Of course present models are way better than these, but fundamentally these are the same as those in the '50s, "just" with tremendously better hardware and algorithms. But there is zero intelligence in these, the models have no internal concept of language or the world around them. This will certainly produce many great specific solutions for sp…

There are tons of research projects that do exactly what you're talking about, initializing an agent with zero knowledge in an environment which just provide rules of discovery and reward. The agent then takes actions in that space and learns from its own experiences. It's just that it is hard to compare with humans, who have had the benefit of evolution over millions of years. A basic example is that of AlphaGo Zero…

AlphaGo Zero definitely falls in the same category as GPT-3 - yes, this is unsupervised learning, but it still is fundamentally the same approach, exactly because of the way discovery and reward work on the model.

This isn't how a child learns to walk at all: A child a priori has the concept of walking, the concept of self, the concept of movement in space, the concept of willing to walk etc. - it just doesn't have the motoric control. The small part of training motoric control through repeated trial and error is indeed similar to what unsupervised learning models, but the important part is missing.

Re: An understanding of AI’s limitations is starting to sink in

#330

Post by wharfjumper »

Judgmentality wrote: post #104
p1esk wrote: post #56

Earlier quoted context omitted.

Things may have changed over the past 5 years or so. Things may have changed over the past 5 weeks or so with GPT-3.

Until GPT-3 can write something meaningful, it's really just a showcase of the technology and a gimmick of a product. Sure it's cool, but what problem is it solving? As far as I can tell the only useful function it has is polluting the internet with pseudo-intellectual comments to promote some agenda (likely political). So now that I think about it, it actually would be incredibly valuable for things like subverting…

I don't understand why the goal is to "guarantee safety". It seems to be generally accepted that human error causes approximately 90% of motor vehicle accidents [0]. Surely then the goal of any autonomous or semi-autonomous transport system should be to merely reduce that percentage? If all motor vehicles were "self-driving" and the total number of annual deaths was reduced by one, wouldn't that be a good thing? I would rather reduce my chance of dying early than eliminate the possibility of being killed by a bot.

0. http://cyberlaw.stanford.edu/blog/2013/12/human-error-cause-...

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