I believe this about as much as I believed the “We’re about to experience the AI singularity” morons.
Yay
This is why you’re seeing news articles from Sam Altman saying that AGI will blow past us without any societal impact. He’s trying to lessen the blow of the bubble bursting for AI/ML.
As I use copilot to write software, I have a hard time seeing how it’ll get better than it already is. The fundamental problem of all machine learning is that the training data has to be good enough to solve the problem. So the problems I run into make sense, like:
- Copilot can’t read my mind and figure out what I’m trying to do.
- I’m working on an uncommon problem where the typical solutions don’t work
- Copilot is unable to tell when it doesn’t “know” the answer, because of course it’s just simulating communication and doesn’t really know anything.
2 and 3 could be alleviated, but probably not solved completely with more and better data or engineering changes - but obviously AI developers started by training the models on the most useful data and strategies that they think work best. 1 seems fundamentally unsolvable.
I think there could be some more advances in finding more and better use cases, but I’m a pessimist when it comes to any serious advances in the underlying technology.
- Copilot can’t read my mind and figure out what I’m trying to do.
Try writing comments
Not copilot, but I run into a fourth problem:
4. The LLM gets hung up on insisting that a newer feature of the language I’m using is wrong and keeps focusing on “fixing” it, even though it has access to the newest correct specifications where the feature is explicitly defined and explained.Oh god yes, ran into this asking for a shell.nix file with a handful of tricky dependencies. It kept trying to do this insanely complicated temporary pull and build from git instead of just a 6 line file asking for the right packages.
“This code is giving me a return value of X instead of Y”
“Ah the reason you’re having trouble is because you initialized this list with brackets instead of
new()
.”“How would a syntax error give me an incorrect return”
“You’re right, thanks for correcting me!”
“Ok so like… The problem though.”
Yeah, once you have to question its answer, it’s all over. It got stuck and gave you the next best answer in it’s weights which was absolutely wrong.
You can always restart the convo, re-insert the code and say what’s wrong in a slightly different way and hope the random noise generator leads it down a better path :)
I’m doing some stuff with translation now, and I’m finding you can restart the session, run the same prompt and get better or worse versions of a translation. After a few runs, you can take all the output and ask it to rank each translation on correctness and critique them. I’m still not completely happy with the output, but it does seem that sometime if you MUST get AI to answer the question, there can be value in making it answer it across more than one session.
I’ve also run into this when trying to program in Rust. It just says that the newest features don’t exist and keeps rolling back to an unsupported library.
So you use other people’s open source code without crediting the authors or respecting their license conditions? Good for you, parasite.
Very frequently, yes. As well as closed source code and intellectual property of all kinds. Anyone who tells you otherwise is a liar.
Ah, I guess I’ll have to question why I am lying to myself then. Don’t be a douchebag. Don’t use open source without respecting copyrights & licenses. The authors are already providing their work for free. Don’t shit on that legacy.
Programmers don’t have the luxury of using inferior toolsets.
That statement is as dumb as it is non-sensical.
Ahh right, so when I use copilot to autocomplete the creation of more tests in exactly the same style of the tests I manually created with my own conscious thought, you’re saying that it’s really just copying what someone else wrote? If you really believe that, then you clearly don’t understand how LLMs work.
I know both LLM mechanisms better than you, it would appear, and my point is not so weak that I would have to fabricate a strawman that I then claim is what you said, to proceed to argue the strawman.
Using LLMs trained on other people’s source code is parasitic behaviour and violates copyrights and licenses.
Look, I recognize that it’s possible for LLMs to produce code that is literally someone else’s copyrighted code. However, the way I use copilot is almost exclusively to autocomplete my thoughts. Like, I write enough code until it guesses what I was about to write next. If that happens to be open source code that someone else has written, then it is complete coincidence that I thought of writing that code. Not all thoughts are original.
Further, whether I should be at fault for LLM vendors who may be breaking copyright law, is like trying to make a case for me being at fault for murder because I drive a car when car manufacturers lobby to the effect that people die more.
Not all thoughts are original.
Agreed, and I am also 100% opposed to SW patents. No matter what I wrote, if someone came up with the same idea on their own, and finds out about my implementation later, I absolutely do not expect them to credit me. In the use case you describe, I do not see a problem of using other people’s work in a license breaking way. I do however see a waste of time - you have to triple check everything an LLM spits out - and energy (ref: MS trying to buy / restart a nuclear reactor to power their LLM hardware).
Further, whether I should be at fault for LLM vendors who may be breaking copyright law, is like trying to make a case for me being at fault for murder because I drive a car when car manufacturers lobby to the effect that people die more.
If you drive a car on “autopilot” and get someone killed, you are absolutely at fault for murder. Not in the legal sense, because fuck capitalism, but absolutely in the moral sense. Also, there’s legal precedent in a different example: https://www.findlaw.com/legalblogs/criminal-defense/can-you-get-arrested-for-buying-stolen-goods/
If you unknowingly buy stolen (fenced) goods, if found out, you will have to return them to the rightful owner without getting your money back - that you would then have to try and get back from the vendor.
In the case of license agreements, you would still be participant to a license violation - and if you consider a piece of code that would be well-recognizable, just think about the following thought experiment:
Assume someone trained the LLM on some source code Disney uses for whatever. Your code gets autocompleted with that and you publish it, and Disney finds out about it. Do you honestly think that the evil motherfuckers at Disney would stop at anything short of having your head served on a silver platter?
I completely understand where you’re coming from, and I absolutely agree with you, genAI is copyright infringement on a weapons-grade scale. With that said, though, in my opinion, I don’t know if calling people parasites like this will really convince people, or change anything. I don’t want to tone police you, if you want to tell people to get fucked, then go ahead, but I think being a bit more sympathetic to your fellow programmers and actually trying to help them see things from our perspective might actually change some minds. Just something to think about. I don’t have all the answers, feel free to ignore me. Much love!
You are right. My apologies, and my congratulations for finding the correct “tone” to respond to me ;) The thing is, I am absolutely fed up with especially the bullshit about snake oil vendors selling LLMs as “AI”, and I am much more fed up with corporations on a large scale getting away with - since it’s for profit - what I guess must already be called theft of intellectual property.
When people then use said LLMs to “develop software”, I’m kind of convinced they are about as gone mentally as the MAGA cult and sometimes I just want to vent. However, I chose the word parasite for a reason, because it’s a parasitic way of working: they use the work of other people, which for more specific algorithms, an LLM will reproduce more or less verbatim, while causing harm to such people by basically copy-pasting such code while omitting the license statement - thereby releasing such code (if open source) into the “wild” with an illegally(*) modified license.
- illegal of course only in such countries whose legal system respects copyright and license texts in the first place
Considering on top the damage done to the environment by the insane energy consumption for little to no gain, people should not be using LLMs at all. Not even outside coding. This is just another way to contribute missing our climate goals by a wide margin. Wasting energy like this - basically because people are too lazy to think for themselves - actually gets people killed due to extreme weather events.
So yeah, you have a valid point, but also, I am fed up with the egocentric bullshit world that social media has created and that has culminated in what will soon be a totalitarian regime in the country that once brought peace to Europe by defeating the Nazis and doing a PROPER reeducation of the people. Hooray for going off on a tangent…
Oh no!
Anyway…
I’ve been hearing about the imminent crash for the last two years. New money keeps getting injected into the system. The bubble can’t deflate while both the public and private sector have an unlimited lung capacity to keep puffing into it. FFS, bitcoin is on a tear right now, just because Trump won the election.
This bullshit isn’t going away. Its only going to get forced down our throats harder and harder, until we swallow or choke on it.
With the right level of Government support, bubbles can seemingly go on for literal decades. Case in point, Australian housing since the late 90s has been on an uninterrupted tear (yes, even in ‘08 and ‘20).
But eventually, bubbles either deflate or pop, because eventually governments and investors will get tired of propping it up. It might take decades, but I think it’s inevitable.
I wish just once we could have some kind of tech innovation without a bunch of douchebag techbros thinking it’s going to solve all the world’s problems with no side effects while they get super rich off it.
… bunch of douchebag techbros thinking it’s going to solve all the world’s problems with no side effects…
one doesn’t imagine any of them even remotely thinks a technological panacaea is feasible.
… while they get super rich off it.
because they’re only focusing on this.
True, they just sell it to their investors as a panacea
Some are just opportunists, but there are certainly true believers — either in specific technologies, or pedal-to-the-metal growth as the only rational solution to the world’s problems.
Andreessen is pretty open about it: https://a16z.com/the-techno-optimist-manifesto/
I think Andreessen is lying and the “techno optimist manifesto” is a ruse for PR.
a16z has been involved in various crypto pump and dumps. They are smart enough to know that something like “play to earn” is not sustainable and always devolves into a pyramid scheme. Doesn’t stop them from getting in early and dumping worthless tokens on the marks.
The manifesto honestly reads like it was written by a teenager. The style, the tone, the excessive quotes from economists. This is pretty typical stuff for American oligarch polemics, no?
Oh they definitely exist. At a high level the bullshit is driven by malicious greed, but there are also people who are naive and ignorant and hopeful enough to hear that drivel and truly believe in it.
Like when Microsoft shoves GPT4 into notepad.exe. Obviously a terrible terrible product from a UX/CX perspective. But also, extremely expensive for Microsoft right? They don’t gain anything by stuffing their products with useless annoying features that eat expensive cloud compute like a kid eats candy. That only happens because their management people truly believe, honest to god, that this is a sound business strategy, which would only be the case if they are completely misunderstanding what GPT4 is and could be and actually think that future improvements would be so great that there is a path to mass monetization somehow.
Yeah my management was all gungho about exploiting AI to do all sorts of stuff.
Like read. Not generative AI crap, but read. They came to us and said quite literally: “how can we use something like ChatGPT and make it read.”
I don’t know who or how they convinced them to use something that wasn’t generative AI, but it did convince me that managers think someone being convincing and confident is correct all the time.
Being convincing and confident without actually knowing is how 9/10s of them make it to the C suite.
That’s probably why they don’t worry about confidently incorrect AI.
Salesmanship is the essence of management at those levels.
Which brings us back around to the original subject of this thread - tech bros - in my own experienced in Tech recently and back in the 90s boom, this generation of founders and “influencers” aren’t techies, they’re people from areas heavy on salesmanship, not actually on creating complex things that objectivelly work.
The complete total dominance of sales types in both domains id why LLMs are being pushed the way they are as if they’re some kind of emerging-AGI and lots of corporates believe it and are trying to hammer those square pegs into round holes even though the most basic of technical analises would tell them that it doesn’t work like that.
Ultimately since the current societal structures we have massively benefit that kind or personality, we’re going to keep on having these kinds of barely-useful-stuff-insanely-hyped-up cycles wasting tons of resources because salesmanship is hardly a synonym for efficiency or wisdom.
Yeah yours is a more thorough and less flippant description of what I meant.
We used to make fun of all the corporate word salad that the Managment would use at my last “real” job. But it really was weird salad all the way down [up].
No no, I disagree I think that shoving AI into all these apps is a solid plan on their behalf. People are going to stop recall and shut it off. So instead they put AI components into every app, It now has the right to overview everything you’re doing and every app collects data on you sending it home to update their personalized models for you so they can better sell you products.
That’s not what’s happening here. Microsoft management are well aware that AI isn’t making them any money, but the company made a multi billion dollar bet on the idea that it would, and now they have to convince shareholders that they didn’t epicly fuck up. Shoving AI into stuff like notepad is basically about artificially inflating “consumer uptake” numbers that they can then show to credulous investors to suggest that any day now this whole thing is going to explode into an absolute tidal wave of growth, so you’d better buy more stock right now, better not miss out.
Soooo… Without capitalism?
Pretty much.
Of course most don’t actually even believe it, that’s just the pitch to get that VC juice. It’s basically fraud all the way down.
Good. I look forward to all these idiots finally accepting that they drastically misunderstood what LLMs actually are and are not. I know their idiotic brains are only able to understand simple concepts like “line must go up” and follow them like religious tenants though so I’m sure they’ll waste everyone’s time and increase enshitification with some other new bullshit once they quietly remove their broken (and unprofitable) AI from stuff.
No shit. This was obvious from day one. This was never AGI, and was never going to be AGI.
Institutional investors saw an opportunity to make a shit ton of money and pumped it up as if it was world changing. They’ll dump it like they always do, it will crash, and they’ll make billions in the process with absolutely no negative repercussions.
Turns out AI isn’t real and has no fidelity.
Machine learning could be the basis of AI but is anyone even working on that when all the money is in LLMs?
I’m not an expert, but the whole basis of LLM not actually understanding words, just the likelihood of what word comes next basically seems like it’s not going to help progress it to the next level… Like to be an artificial general intelligence shouldn’t it know what words are?
I feel like this path is taking a brick and trying to fit it into a keyhole…
learning is the basis of all known intelligence. LLMs have learned something very specific, AGI would need to be built by generalising the core functionality of learning not as an outgrowth of fully formed LLMs.
and yes the current approach is very much using a brick to open a lock and that’s why it’s … ahem … hit a brick wall.
Yeah, 20 something years ago when I was trying to learn PHP of all things, I really wanted to make a chat bot that could learn what words are… I barely got anywhere but I was trying to program the understanding of sentence structure and feeding it a dictionary of words… My goal was to have it output something on its own …
I see these things become less resource intensive and hopefully running not on some random server…
I found the files… It was closer to 15 years ago…
Trying to invent artificial intelligence to learn php is quite funny lol
I’m amazed I still have the files… But yeah this was before all this shit was big… If I had a better drive I would have ended up more evil than zuck … my plan was to collect data on everyone who used the thing and be able to build profiles on everyone based on what information you gave the chat … And that’s all I can really remember… But it’s probably for the best…
Also a bit sadistic to be honest. Bringing a new form of life into the world only to subject it to PHP.
shouldn’t it know what words are?
Not necessarily, but it should be smart enough to associate symbols with some form of meaning. It doesn’t do that, it juts associates symbols with related symbols, so if there’s nothing similar that already exists, it’s not going to be able to come back with anything sensible.
I think being able to create new content with partial sample data is necessary to really be considered general AI. That’s what humans do, and we don’t necessarily need the words to describe it.
Right, so AIs don’t really know what words are. All they see are tokens. The tokens could be words and letters, but they could also be image/video features, audio waveforms, or anything else.
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Then what is this I’m feeling if it’s not AGI? 🤔
Maybe GERD?
It’s gonna crash like a self driving tesla. It’s gonna fall apart like a cybertrukkk.
Theres no bracing for this, OpenAI CEO said the same thing like a year ago and people are still shovelling money at this dumpster fire today.
Ya AI was never going to be it. But I wouldn’t understate its impact even in its current stage. I think it’ll be a tool that will be incredibly useful for just about every industry
There aren’t many industries where results that are correct in the very common case everybody knows anyway, a bit wrong in the less common case and totally hallucinated in the actually original cases is useful. Especially if you can’t distinguish between those automatically.
Well duhhhh.
Language models are insufficient.
They also need:Someone in here has once linked me a scientific article about how today’s “AI” are basically one level below what they need to be anything like an AI. A bit like the difference between exponent and Ackermann function, but I really forgot what that was all about.
LLMs are AI. There’s a common misconception about what ‘AI’ actually means. Many people equate AI with the advanced, human-like intelligence depicted in sci-fi - like HAL 9000, JARVIS, Ava, Mother, Samantha, Skynet, and GERTY. These systems represent a type of AI called AGI (Artificial General Intelligence), designed to perform a wide range of tasks and demonstrate a form of general intelligence similar to humans.
However, AI itself doesn’t imply general intelligence. Even something as simple as a chess-playing robot qualifies as AI. Although it’s a narrow AI, excelling in just one task, it still fits within the AI category. So, AI is a very broad term that covers everything from highly specialized systems to the type of advanced, adaptable intelligence that we often imagine. Think of it like the term ‘plants,’ which includes everything from grass to towering redwoods - each different, but all fitting within the same category.
I know those terms. I wanted to edit it, but was too lazy. You still did understand what I meant, right?
We don’t call a shell script “AI” after all, and we do call those models that, while for your definition there shouldn’t be any difference.
The stuff in computer games that makes NPCs move around the game world from point A to point B has been called AI for ages (and in this case specifically, is generally the A* pathing algorithm which isn’t even all that complex).
It’s only recently that marketing-types, salesmen and journalists with no actual technical expertise have started pushing AI as if the I in the acronym actually meant general intelligence rather than the “intelligence-alike” meaning that it has had for decades.
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“The economics are likely to be grim,” Marcus wrote on his Substack. “Sky high valuation of companies like OpenAI and Microsoft are largely based on the notion that LLMs will, with continued scaling, become artificial general intelligence.”
“As I have always warned,” he added, “that’s just a fantasy.”
Microsoft shit is a mega corp… AI is based on their revenue lol
Even Zuckerberg admits that trying to scale LLMs larger doesn’t work because the energy and compute requirements go up exponentially. There must exist a different architecture that is more efficient, since the meat computers in our skulls are hella efficient in comparison.
Once we figure that architecture out though, it’s very likely we will be able to surpass biological efficiency like we have in many industries.
With current stat prediction models?
That’s a bad analogy. We weren’t able to surpass biological efficiency in industry sector because we figured out human anatomy and how to improve it. It’s simply alternative ways to produce force like electricity and motors which had absolutely no relation to how muscles works.
I imagine it would be the same for computers, simply another, better method to achieve something but it’s so uncertain that it’s barely worth discussing about.
Of course! It’s not like animals have jet engines!
Human brains are merely the proof that such energy efficiencies are possible for intelligence. It’s likely we can match or go far beyond that, probably not by emulating biology directly. (Though we certainly may use it as inspiration while we figure out the underlying principles.)
Oh nice, another Gary Marcus “AI hitting a wall post.”
Like his “Deep Learning Is Hitting a Wall” post on March 10th, 2022.
Indeed, not much has changed in the world of deep learning between spring 2022 and now.
No new model releases.
No leaps beyond what was expected.
\s
Gary Marcus is like a reverse Cassandra.
Consistently wrong, and yet regularly listened to, amplified, and believed.
Great!! …I don’t what chatGPT to go anywhere, I use it every day and Google has become assss.