If that's the actual meat of your claim, it's weird to just put it unsupported at the end. If you think it's an aside you've got a big problem, because without it the rest is pretty weak.
We saw this with chess. Anybody who was clinging on to the idea that well, the machines can't really play chess, because technically there do seem to be a few humans who are better, was screwed the moment the machines begin routinely beating grand masters. Either this categorically isn't something that the machines can do, or, it is and so it's important that they can do it at all. We shouldn't expect any half measures on this.
Do you consider Rob Liefeld an artist? What do you reckon the chances are that the machine can get human anatomy right more often than Rob Liefeld? Rob is a human, so it seems like that should give him an advantage. However unlike Rob DALL-E has learned by seeing lots of existing pictures of humans that they don't look the way Rob draws them...
https://www.youtube.com/watch?v=ANRnuT9nLEE&list=PLrxfgDEc2N...
Transcript: https://www.preposterousuniverse.com/podcast/2022/02/14/184-...
"...And then there’s natural language understanding and reasoning, and I would say we have not really made progress at all. GPT-3, which we may wanna talk about, gives the illusion of having natural language of understanding, but I don’t really think that it does. And we are nowhere near, for example, an all-purpose general assistant. ..."
Either the quote is poorly chosen or reading this article is not worth the time.
The Mindscape Podcast is hosted by Sean Carroll. You have a very sharp quantum physicist interviewing an expert in the field of AI research.
The podcast is worth the time, and the quote is representative of an expert's take on the matter. He elaborates, but I don't need to write an essay just to argue on the internet.
Who was "clinging on to the idea that well, the machines can't really play chess" and when was that?
That’s the way it is with AI: first people say X is impossible for computers, then they say X is hard, then they say X doesn’t work for certain edge cases, then they say we’ve known all along that computers could do X.
>> Levy wrote, "I had proved that my 1968 assessment had been correct, but on the other hand my opponent in this match was very, very much stronger than I had thought possible when I started the bet."[37] He observed that, "Now nothing would surprise me (very much)."[38]
(Edit: the quote is from your WP link.)
So that at least really does not match the pattern you mention. Levy's evaluation of chess engines was pretty much in the water, all the way up to Kasparov's loss to Deep Blue. As far as I can tell he never said anything like "the machines can't really play chess" as the OP suggested. He just made a prediction about how much they could advance in ten years. And he was right.
I would therefore like more justification for your assertion that "that's the way it is in AI". I would also like a clarification: who are the "people" who say all those things? How representative are they of experts and researchers?
Who makes all those naive predictions about the impossibility of AI that are later proven wrong? For the time being, it seems that naive predictions can be traced more directly to luminaries of the field, like Alan Turing or Marvin Minsky [2], who predict that AI is "just around the corner", rather than skeptics and naysayers who say it wont' happen, as is usually suggested.
And then of course, there's Rodney Brooks' dated predictions, so far standing the test of time (although that's a short time!) [3].
_______________
[1] Totally coincidentally, Donald Michie was my thesis advisor's thesis advisor, so I'm, like, his academic grandchild.
[2] See: https://web.eecs.umich.edu/~kuipers/opinions/AI-progress.htm...
"In 1958, Herbert Simon and Allen Newell wrote, “within ten years a digital computer will be the world’s chess champion”; note that this is 10 years before Levy and McCarthy's bet.
[3] https://rodneybrooks.com/predictions-scorecard-2022-january-...
https://news.ycombinator.com/item?id=11718300
If we count GitHub Copilot as the tip of the spear then I was too optimistic.
> GitHub Copilot ... was first announced by GitHub on 29 June 2021
https://en.wikipedia.org/wiki/Program_synthesis#Origin
Much work has been done since then and inductive program synthesis from incomplete specifications consisting of input/output examples (a form of machine learning) has been possible for quite some time. This is the second time this week I point to the report by Gulwani et al for a modern overview (of both kinds):
Program Synthesis
https://www.semanticscholar.org/paper/Program-Synthesis-Gulw...
Rather than Copilot being the "tip of the spear", it is really a step back, a system that can only generate code but not check its correctness, unlike pretty much every program synthesis system since forever. Although this may actually be an advantage for its commercial application (since it makes it easier to match expectations of the system's performance) it is not really any indication of progress, in any way, shape or form. In truth, Copilot is famous today because it is supported by a large company like Microsoft and because earlier work is not well-known by most people who get their AI knews from blogs and podcasts, who are also not very well aware of the history of the field. But, "tip of the spear"? Oh, no. Unless it's a very blunt, toy spear, more like a tech demo of a spear.
And this is by no means restricted to program synthesis, and Copilot. For example, the first self-driving car to drive on a stretch of real road, with real traffic, without human intervention, was Ernst Dickmann's 1995 robot car:
https://people.idsia.ch/~juergen/robotcars.html
Again: 1995. And yet, fully autonomous self-driving cars are still not here. The revolution hasn't happened and progress has only crawled marginally forward.
Waymo has taxi service. It's losing money doing that, and it's only in a few select places, but it's doing autonomous journeys, with no "safety driver" on city streets. It understands junctions, and traffic signals, pedestrians and cyclists, because on the city streets those things are commonplace. It's doing the hard part.
I don't think that constitutes "crawled marginally forward", it's a considerable advance.
Gosh, the robot car work was incredible, I can't believe I've never heard of it before!
- - - -
Copilot isn't cutting edge but it's significance is just that it's a mass market tool. It will be interesting to see how well it does, and whether users find it worthwhile overall after a couple of years. Will it be improved to the point where it starts to compete with its users?
I've asked other programmers before, if you could write a program that replaced you would you do it?
(One of the reasons I like Schmidhuber is that his goal, since early on, is to "Create an automatic scientist, and then retire.")
To me the ultimate effect of programming is to obviate the programmer.
I think Copilot can be used very effectively, as long as its capabilities and their limitations are communicated clearly. For instance, I think it can make a great boilerplate generator, as long as users stick to short code snippets.
Well, I don't know about replacing programmers. I think that's Sci-Fi, for the time being, and for a while longer still. What I'm more interested in is creating tools to help programmers do their job. Copilot does that already, btw, I'm not dissing it. I'm just pointing out it doesn't represent a sudden shift in capabilities, to be clear.
>> (One of the reasons I like Schmidhuber is that his goal, since early on, is to "Create an automatic scientist, and then retire.")
I didn't know Schmidhuber had said that. My thesis advisor, Stephen Muggleton, was part of an interdisciplinary team who created a robot scientist that can develop its own theories and then choose, and run, the experiments to prove them:
https://en.wikipedia.org/wiki/Robot_Scientist
Another one of those things that are not well-known, I guess. I wasn't involved with that, btw, but I think recent advances could make for a much more powerful system. I am considering something similar as a research project, post-doc.
Cheers!
Text conditional image generation is still a fairly new thing, we don’t know what its upper limits will prove to be. Also, it seems likely that, whatever level of capability they reach, humans will learn how to use them effectively as tools for their own purposes. Some people might use them for quickly preflighting ideas, others to create boilerplate, some people may use them to speed up their workflow or scale up productivity. People didn’t know what all the use cases for personal computers would be when they were introduced in the mid-70’s, or what capabilities they would possess decades later.
I'm going to try to work up a decent reply to your article, but it might take me a day or two.
Have you read Wendell Berry's "What are People For?" (that essay not the whole eponymous book)?
- - - -
The (open) secret at the heart of AI is that no AI can answer: "What is good?" ( https://news.ycombinator.com/item?id=31720621 )
AKA "Lucky for whom?" Teela Brown, fictional character in Larry Niven novels
Spoiler alert!
This link gives details of the character that are spoilers: https://larryniven.fandom.com/wiki/Teela_Brown
Unfortunately those details are the point I'm trying to make, and I'm a huge Niven fan so I'm not going to spoil Ringworld, but it ties in with the (ultimately metaphysical) question, "What is good?"
Commercially viable AI vs skilled engineers, that’s going to take longer.
I wouldn’t be surprised if we could replace the average BA with an AI right now.
Still, it’s only a matter of time till nicer graphics are possible. Most graphic designers and artists are still worse than this thing, especially the type that bought a $200 drawing tablet on Amazon and sell their services on Fiverr. Those people are no better than Dall-E, just like most copywriters are no better than GPT-3.
Even if they are in fact better it’s only a few years till that changes. Deepmind can train a new model faster than you can go back to grad school.
If the delineation can only be made because you are an art major, or practicing artist, that is not really compelling to your own market.
We are on the third generation of these type of "AI" and they are already past the point where people would exchange cash for a print of this work. It is only a matter of time until people are using these to generate the general picture and then drawing it using their preferred medium (e.g. oil, watercolor).
I do think this can be thought of more like a sketchbook or a camera at the end of the day, since real contemporary art collectors will not go for a print from Dall-e 2 or Midjourney so readily. Make a painting from it and if it's a decent rendition it will likely sell.
You don't have to be anywhere near perfect to cause tremendous disruption. "Polyester" grade artwork will be perfectly acceptable for a lot of use cases.
Just like how self-driving will decimate the trucking workforce, all while people continue to screech about how "it can't handle snow therefore it's useless".
As long as we can miniaturize the models sufficiently that individuals and small companies can get output that's comparable to what big corporations with deep pockets can get, these sorts of AI tools have the potential to revolutionize creativity.
If you don't believe that, just consider where technology was 100 years ago and what the response would have been if you'd described DALL-E in its current incarnation and asked people if they thought that would ever come to pass.
It also seems silly to compare billion parameter AI models to polyester and try to reduce their value to the trite "artificial is bad" argument which has plagued human thinking for centuries.
Wait, YC invests in this space? If it isn't any trouble, could you point me to a few?
I hope I am wrong so that society has more time to adapt to the worker displacement and downstream policy issues.
I’ve walked through several of the world’s top art museums. Most art is aesthetically crap.
I wish this were true, because it assumes a lot about Humanity living up to it's highest potential in terms of QC; but the truth is we're talking about digial content creation, which has been churning obscene amounts of data on a daily basis in the Internet era. And this means that it isn't about 'the best of the best' what it actually is a race to the bottom in terms of 'good enough' source material which is as disposable and fleeting as it's consumers attention span.
As a space nerd (its in my bio) I followed James Webb since Cassini was decommissioned/crashed and I found out about the necessary crypgenic tests to make Jw work were underway, but even as impressive as I find the images we see (and they are breath taking) I'm still spending way more time on DALLE-2 subreddit admiring all the prompts because I still don't have access to it myself and like the sheer novelty of it all.
You want a more closer analogue than polyester clothes? Try food: processed junk and by extension the American diet has made us awash in excess and rather than create more discerning consumers who have all the options that Modern chemistry, biology and AG science have to offer to shift the market to a more sustainable and higher quality point: we instead face the stark reality that the 1-2 killers in most developed countries are heart disease and diabetes that are directly correlated to the over consumption of cheap junk. Obesity remains one of the biggest threats to over all quality and longevity of an individual's life!
I study AI and ML and I have many artists friends, I used to be a cook so it's not a far leap, and we often discuss that this is inevitable: the inability to excel and to standout in a World in just one medium due to the advancement of technology.
It's not enough to be a creative who just focuses on music or painting, or sculpture if you want to have anything but a self-funded gallery where you try to sell your pieces to the attendees (often at a loss) in order to market yourself in the hopes of a larger commission that lets you quit your day job (or at least have a hiatus) when social media has availed itself as a gallery of what may not be the best artists in the World but the most prolific and often those with the best marketing and most followers to stay as the top trending in your discipline.
It's something we did encountered sooner in the culinary World as food porn became as ubiquitous as it was pre-covid so I see it quite clearly, it wasn't enough to deliver amazing service and provide a good meal sourced from artisans and local farmers and grow from word to mouth, now you had to play the social media game and become influencers or host influencers and then have them 'engage' with their demographic to expand your clientele and reservations for that quarterly push: and as was our case it helps if you are related to a certain tech mogul who dominates social media and try to ride coat tails where ever possible. And even that isn't enough as you still have to pay off yelp for keeping bad reviews at bay in a perverse game, while gamifying Google reviews etc... but we had tech giants buy-out on a weekly basis, proving it works.
It's becoming such that it's less about the execution of the art or the craft itself but rather doing N amount of things to remain as a signal amongst all the noise while the art becomes a secondary possibly tertiary part of what keeps the lights on; techies wanted disruption, and this is what it looks like in the 21st century.
I think this may be required reading for kids just graduating HS and thinking about what to do, as it gives a sobering view of what has happened in just a short duration when it comes to AI in certain, often precarious, Industries [0] and how it can potentially shape culture itself as so much of AI growth is in the surveillance-economy.
0: https://www.technologyreview.com/supertopic/ai-colonialism-s...
GPT-3 might generate a novel, but, generally speaking the prose is jarring and awful to read, because there is no intent (danger: philosophically loaded word) behind it. It's all automated collages and they all feel... cheap.
The world is beginning to discover that polyester isn't very good. It's bad for the skin, bad for the environment, and terrible for human health in general (microplastics generated from washing polyester give a medium for increases in algal blooms in coastal waters... etc.). It is cheap, but we're going to figure out it isn't good, and stop making or buying it (I hope).
DALL-E and GPT-3 are the polyester of design and creative construction. They're cheap; aesthetically uncomfortable. We'll turn to humans for high-quality design until we actually get AGI, and those systems are not a path to AGI.