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

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

#121
post #93

Earlier quoted context omitted.

One big one is farming, think harvesting machinery. There's a number of startups trying to get that going. I think most are not at the scale to be successful the way the market themselves, but their collective learning will eventually lead to some consolidation. Why AI for that, it's vision AI to know when fruit is ripe or vegetables are ready for harvest. Then hand eye coordination to not bruise the fruit/vegetables…

Depending on the crop you’re talking about, we are still very very far away from this. People have been trying to design machines to pick fruit, even in toy scenarios, for decades, and we have little to show for it. I don’t think that image processing is the bottleneck here, it’s literally the mechanism as far as I understand. I’m skeptical that any mechanical equipment will ever be able to do these tasks as cheaply,…

Look at olive harvesting machines.

Definitely easier than fruit, but we've made so much progress.

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

#122

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…

Your comment is a little hand-wavy and strongly worded ("revolution", "immeasurable", "limitless", "all domains"). Many things have exponential growth - bacterial reproduction, compound interest, certain chemical reactions. It's important to understand that this does not automatically result in miraculous universal transformation, but must be considered in the context of the world we live in. A little humility is alw…

Your analytical thinking misses the human element. To give an example: Steve Jobs didn't have humility, nor did he shy away from hyperbole. You would have had the same response to his words, but look at what he - literally, in the physical world - achieved. Human motivation - no matter how deluded - is not actually something not to dismiss. It has effects on others, which translates to action. The inputs are not all machines. At least not yet.

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

#123

This is so strange. If you use facebook, google, netflix, apple, microsoft, amazon, tesla or a whole host of other products and services you are interfacing with AI all the time, sometimes as the core product of the service. To think there’s no value there is asinine. Comes up a lot on HN. Seems like people who get excited for these types of articles are set in their ways and don’t want to progress forward.

What AI exactly I interface in netflix? Movie recommendations based on some predefined classifications? Search engine? those problems were solved by google 20 years ago.

All the recommendation and ad engines are not that smart, far from it, and the smart stuff they do is just by tracking you and looking at what you do, this is not AI, just classic cold war spying.

Those siri and alexa are taking commands as if you are programming a device, you just say it rather than write it but the dynamic is the same, they can't process anything even slightly deviating out of their "programming" language. Both sound recognition and all those self driving stuff is more about advanced signal processing rather than some AI and as such are limited and will never be anything even remotely close to the way humans perceive things.

They promised deviation from the classic machine "thinking" but rather a foray into the human mind by machine. So far it is a failure, machines keep doing what machines are good at and nothing more.

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

#124
Maybe it's because everyone talks/chats every day with "virtual assistants" at banks and every other organization, and never ever finds them useful. Their main purpose is to frustrate you enough so you give up trying to connect to a real person.

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

#125
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…

Until GPT-3 can write something meaningful

What is "meaningful"? Honest question. Isn't meaning assigned by a reader? If I'm reading poetry generated by GPT-3 and I like it just as much as poetry written by a human poet, does it make it meaningful? What if I finetune GPT-3 (or the bigger next gen version) on every scientific paper ever written, and as a result it generates a novel idea that turns out to be valid and useful, should I care if it happened by accident, or without "understanding"? Can the knowledge encoded in the model parameters be interpreted as some form of understanding? If no, why not? What's missing exactly? What is different from how human scientists operate?

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

#126
People are going to complain that AI is lame right up until the point that it gets general enough to make them all irrelevant in terms of work productivity. Then rather than modifying society to distribute the gains, they will leave the outdated structures in place and try (too late) to suppress it.

At no point (until it's too late) will there be be effective legislation discouraging the creation of fully general and autonomous digital persons that compete with humans.

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

#127
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…

Serious (and likely ignorant) question - what does linearity have to do with anything here? linear over what and why does non-linearity make something 'unpredictable'?

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

#128
post #109

Earlier quoted context omitted.

This is so strange. If you use facebook, google, netflix, apple, microsoft, amazon or a whole host of other services you are interfacing with AI all the time. To think there’s no value there is asinine. Comes up a lot on HN. Seems like people set in their ways who don’t want to progress forward.

oh yeah, magnificient AI at Google search. Picked up my ebook-reader again, wanted to know about the state of linux there. so do a search: " linux ssh" (since a good shell is the point, where you can start developing). Turns out, the first 3 pages want to sell me the same thing I already own, with one outlier selling nutritional supplements. Oh well done AI!

It’s doing exactly as it’s trained. Nudge the useds to buy more trinkets.

Now just imagine how good it could be if it was being trained to actually give good search results instead of selling.

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

#129
post #97

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…

There's value, the tech works, but applying it is surprisingly hard. I met someone who dedicates their life to using machine learning to replace/aid/automate pathologists 6+ hour days searching for cancer tumors in lungs. They have been at it for 5 years. There is an insane amount of approvals, red tape, knowing the right people, convincing the hospital to use it - all tasks not related to the tech actually working.…

There is a strong chance that the technology to create digital beings will be available before human society is able to integrate and adjust to the current generation of AI.

So what may happen is that the way that AI really gets integrated is by actually replacing human beings who largely die off.

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

#130
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…

Intelligence is the amalgamation of many smaller problems working together and building on top of each other. * Facial recognition/detection * Facial synthesis (deepfakes) * Speech synthesis, including mimickry * Speech recognition * Natural language processing * Gait/walking algorithms * Motion planning * etc. Complexity arises from simple units working together in parallel. We're working on the smaller, specialized…

I agree with the notion that artificial intelligence is a graph of smaller problems, as is human perception.

The problem is a question of informational density. Biological systems are computationally very dense. Far more dense than the 4nm transistor fabrication available today, and with a far larger volume of size.

Consequentially, the computational capability of most AI systems is far lower than its biological equivalent. And as you find in most information finite discretization problems - the lower density information system will alias against the higher information system.

So, that means you will have a hierarchy/pipeline of computational stages - each aliasing reality. Eventually, you will find that your parameterization of each perceptual stage has a strange property. The size of each subsequent layer is important... but the relative computational space of each subsequent stage is even more important. Because mismatched stages results in nothing but numerical interference and noise.

And I think that is where we are today. The IQ of a krill shrimp.

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