Earlier quoted context omitted.
Where are stop signs hexagons? Am I being a pedantic numpty or am I illustrating a point about the many ways errors creep in, regardless of the natural- or artificial-ness of the intelligence?
You're being a pedantic. Human beings are tremendously better at driving than machines despite sometimes saying hexagonal rather than octagonal. Humans and current AIs both make mistakes but humans manage a kind of robustness, ability to deal gracefully with unexpected situations, that current AIs don't seem to be progressing towards.
An understanding of AI’s limitations is starting to sink in
191–200 of 403 posts
Re: An understanding of AI’s limitations is starting to sink in
#192Earlier quoted context omitted.
Ok, consider me intrigued. What is that we are going to see/experience once you folks had some time? Genuine question! Can you give us a basic idea of the things that you are already sure by now will see the light of day?
I guess once the field starts mixing probabilistic, deep and logic approaches we will see a bit of progress towards AGI. This is one example of where things might be heading: https://science.sciencemag.org/content/350/6266/1332
Re: An understanding of AI’s limitations is starting to sink in
#193We 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…
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.
Re: An understanding of AI’s limitations is starting to sink in
#194Earlier quoted context omitted.
Linear models have more bias, so they represent current data less well and are more predictive of future, unseen data (think of a straight line through a point cloud). Non-linear models have more variance so they represent current data better and are less predictive of future, unseen data (think of a line snaking around a point cloud). An added complication is that deep neural net models are, in practice, vectors (or…
I'm not good at math, but I'm confused by the association of AI with non-linear stuff, setting aside the association of non-linear with "bad". I thought ML involved linear algebra or something (says xkcd!) which would presumably be...linear?
Re: An understanding of AI’s limitations is starting to sink in
#195Earlier 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…
Isn't it good enough, or very nearly, to generate fake news? And if you can generate something that fools a large percentage of humans, even for a second or two, you can sell ads. It would be solving a problem for anyone who can profit from it. I thought the people who developed it stated that it was too dangerous to release widely? Dangerous = useful to bad people, no?
Re: An understanding of AI’s limitations is starting to sink in
#196Earlier quoted context omitted.
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…
The thing is, if we could write a specific, closed-end, prescriptive definition of "meaningful" or "understanding" or whatever, then we'd be able to program it. And we can't, so we have to settle for something else, usually how a thing fails to be what we (indeed subjectively) consider meaningful. Still, it's not arbitrary. The way that something like GPT-3 tends to fail basically is that you 2-3 paragraphs where par…
Re: An understanding of AI’s limitations is starting to sink in
#197We 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…
Re: An understanding of AI’s limitations is starting to sink in
#198Earlier quoted context omitted.
Ok, consider me intrigued. What is that we are going to see/experience once you folks had some time? Genuine question! Can you give us a basic idea of the things that you are already sure by now will see the light of day?
"Hi AlphaGo, let's play tic tac toe". Consider me bored of it all. We're not close to anything. The emphasis is on "artificial", not "intelligence". It should be renamed Glorified Calculation. There are some neat tricks, writing your first neural net is great fun, but we're using the word intelligence with spectacular liberty. I'll keep an eye open for something inspiring, but I've seen nothing of the sort yet.
Re: An understanding of AI’s limitations is starting to sink in
#199Earlier quoted context omitted.
since you’re working on the field : i’m still under the impression that modern ML (neural network in particular) are not producing any science, nor are they producing any level of understanding of the phenomenon it’s trying to model. And that as such, we can’t provide a reliable estimate of the limitations of the produced model, other than by feeding it tons of inputs and measure the result. It would be like trying t…
Some of this would be considered a feature by companies. It's more defensible to have unknowable AI deciding to do illegal things than programmers hard coding illegal things. Which really boggles my mind. When my kid does something illegal I'm held liable. When an ML algorithm programmed by a team of people does, nothing we can do about that!
On the other hand, the difference between a team of people and a particular person with mens rea, that's not unique to AI either.
Re: An understanding of AI’s limitations is starting to sink in
#200Earlier quoted context omitted.
Ok, consider me intrigued. What is that we are going to see/experience once you folks had some time? Genuine question! Can you give us a basic idea of the things that you are already sure by now will see the light of day?
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…