this post was submitted on 22 Dec 2024
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There is this seeming need to discredit AI from some people that goes overboard. Some friends and family who have never really used LLMs outside of Google search feel compelled to tell me how bad it is.
But generative AIs are really good at tasks I wouldn't have imagined a computer doing just a few year ago. Even if they plateaued in place where they are right now it would lead to major shakeups in humanity's current workflow. It's not just hype.
The part that is over hyped is companies trying to jump the gun and wholesale replace workers with unproven AI substitutes. And of course the companies who try to shove AI where it doesn't really fit, like AI enabled fridges and toasters.
This is easy to say about the output of AIs.... if you don't check their work.
Alas, checking for accuracy these days seems to be considered old fogey stuff.
This is literally the hype. This is the hype that is dying and needs to die. Because generative AI is a tool with fairly specific uses. But it is being marketed by literally everyone who has it as General AI that can "DO ALL THE THINGS!" which it's not and never will be.
The obsession with replacing workers with AI isn't going to die. It's too late. The large financial company that I work for has been obsessively tracking hours saved in developer time with GitHub Copilot. I'm an older developer and I was warned this week that my job will be eliminated soon.
So the company that is obsessed with money that you work for has discovered a way to (they think) make more money by getting rid of you and you're surprised by this?
At least you've been forewarned. Take the opportunity to abandon ship. Don't be the last one standing when the music stops.
I never said that I was surprised. I just wanted to point out that many companies like my own are already making significant changes to how they hire and fire. They need to justify their large investment in AI even though we know the tech isn't there yet.
Computers have always been good at pattern recognition. This isn't new. LLM are not a type of actual AI. They are programs capable of recognizing patterns and Loosely reproducing them in semi randomized ways. The reason these so-called generative AI Solutions have trouble generating the right number of fingers. Is not only because they have no idea how many fingers a person is supposed to have. They have no idea what a finger is.
The same goes for code completion. They will just generate something that fills the pattern they're told to look for. It doesn't matter if it's right or wrong. Because they have no concept of what is right or wrong Beyond fitting the pattern. Not to mention that we've had code completion software for over a decade at this point. Llms do it less efficiently and less reliably. The only upside of them is that sometimes they can recognize and suggest a pattern that those programming the other coding helpers might have missed. Outside of that. Such as generating act like whole blocks of code or even entire programs. You can't even get an llm to reliably spit out a hello world program.
Large context window LLMs are able to do quite a bit more than filling the gaps and completion. They can edit multiple files.
Yet, they're unreliable, as they hallucinate all the time. Debugging LLM-generated code is a new skill, and it's up to you to decide to learn it or not. I see quite an even split among devs. I think it's worth it, though once it took me two hours to find a very obscure bug in LLM-generated code.
What is your favorite flavor of kool aid?
Grape, my nigga.
"It's part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, 'that's not thinking'"
-Pamela McCorduck
"AI is whatever hasn't been done yet."
- Larry Tesler
That's the curse of the AI Effect.
Nothing will ever be "an actual AI" until we cross the barrier to an actual human-like general artificial intelligence like Cortana from Halo, and even then people will claim it isn't actually intelligent.
I mean, I think intelligence requires the ability to integrate new information into one's knowledge base. LLMs can't do that, they have to be trained on a fixed corpus.
Also, LLMs have a pretty shit-tastic track record of being able to differentiate correct data from bullshit, which is a pretty essential facet of intelligence IMO
LLMs have a perfect track record of doing exactly what they were designed to, take an input and create a plausible output that looks like it was written by a human. They just completely lack the part in the middle that properly understands what it gets as the input and makes sure the output is factually correct, because if it did have that then it wouldn't be an LLM any more, it would be an AGI.
The "artificial" in AI does also stand for the meaning of "fake" - something that looks and feels like it is intelligent, but actually isn't.
Well at least until those who study intelligence and self-awareness actually come up with a comprehensive definition for it. Something we don't even have currently. Which makes the situation even more silly. The people selling LLMs and AGNs as artificial intelligence are the PT Barnum of the modern era. This way to the egress folks come see the magnificent egress!
They already did. AGI - artificial general intelligence.
The thing is, AGI and AI are different things. Like your "LLMs aren't real AI" thing , large language models are a type of machine learning model, and machine learning is a field of study in artificial intelligence.
LLMs are AI. Search engines are AI. Recommendation algorithms are AI. Siri, Alexa, self driving cars, Midjourney, Elevenlabs, every single video game with computer players, they are all AI. Because the term "Artificial Intelligence" by itself is extremely loose, and includes the types of narrow AI all of those are.
Which then get hit by the AI Effect, and become "just another thing computers can do now", and therefore, "not AI".
That just Compares it to human level intelligence. Something which we cannot currently even quantify. Let alone understand. It's ultimately a comparison, a simile not a scientific definition.
Search engines have always been databases. With interfaces programmed by humans. Not ai. They've never suddenly gained new functionality inexplicably. If there's a new feature someone programmed it.
Search engines are however becoming llms and are getting worse for it. Unless you think eating rocks and glue is particularly intelligent. Because there is no comprehension there. It's simply trying to make its output match patterns it recognizes. Which is a precursor step. But is not "intelligence". Unless a program doing what it's programed to do is artificial intelligence. Which is such a meaningless measure because that would mean notepad is artificial intelligence. Windows is artificial intelligence. Linux is artificial intelligence.
You can argue what you think the words should mean in your opinion in the field of artificial intelligence. I agree with some of them.
It just doesn't change what they actually do mean.
That's a disturbing handwave. "We don't really know what intelligence is, so therefore, anything we call intelligence is fair game"
A thermometer tells me what temperature it is. It senses the ambient heat energy and responds with a numeric indicator. Is that intelligence?
My microwave stops when it notices steam from my popcorn bag. Is that intelligence?
If I open an encyclopedia book to a page about computers, it tells me a bunch of information about computers. Is that intelligence?
I never know what to think when I come across a comment like this one—which does describe, even if only at a surface level, how an LLM works—with 50% downvotes. Like, are people angry at reality, is that it?
With as much misinformation that's being spread about regarding LLMs. It would only lose more people's comprehension to go into anything more than a generalization.
The problem is people are being sold AGI. But chat GPT and all these other tools don't even remotely qualify for that. They're really nothing more than a glorified Alice chatbot system on steroids. The one neat new trick to all this is that they've automated the training a bit. But these llms have no more comprehension of their output or the input they were given than something like the old Alice chatbot.
These tools have been described as artificial intelligence to layman for decades at this point. It makes it really hard to change that calcified opinion. People would rather believe that it's some magical thing not just probability and maths.
They are bullshit machines, trained to output something that users think is the right output.
Downvoting someone on the Internet is easier than tangentially modifying reality in a measurable way
Like which one? Because it's now 2 years we have chatGPT and already quite a lot of (good?) models. Which shakeup do you think is happening or going to happen?
Computer programming has radically changed. Huge help having llm auto complete and chat built in. IDEs like Cursor and Windsurf.
I’ve been a developer for 35 years. This is shaking it up as much as the internet did.
I quit my previous job in part because I couldn't deal with the influx of terrible, unreliable, dangerous, bloated, nonsensical, not even working code that was suddenly pushed into one of the projects I was working on. That project is now completely dead, they froze it on some arbitrary version.
When junior dev makes a mistake, you can explain it to them and they will not make it again. When they use llm to make a mistake, there is nothing to explain to anyone.
I compare this shake more to an earthquake than to anything positive you can associate with shaking.
And so, the problem wasn't the ai/llm, it was the person who said "looks good" without even looking at the generated code, and then the person who read that pull request and said, again without reading the code, "lgtm".
If you have good policies then it doesn't matter how many bad practice's are used, it still won't be merged.
The only overhead is that you have to read all the requests but if it's an internal project then telling everyone to read and understand their code shouldn't be the issue.
This is a problem with your team/project. It’s not a problem with the technology.
I hardly see it changed to be honest. I work in the field too and I can imagine LLMs being good at producing decent boilerplate straight out of documentation, but nothing more complex than that.
I often use LLMs to work on my personal projects and - for example - often Claude or ChatGPT 4o spit out programs that don't compile, use inexistent functions, are bloated etc. Possibly for languages with more training (like Python) they do better, but I can't see it as a "radical change" and more like a well configured snippet plugin and auto complete feature.
LLMs can't count, can't analyze novel problems (by definition) and provide innovative solutions...why would they radically change programming?
You’re missing it. Use Cursor or Windsurf. The autocomplete will help in so many tedious situations. It’s game changing.
ChatGPT 4o isn't even the most advanced model, yet I have seen it do things you say it can't. Maybe work on your prompting.
That is my experience, it's generally quite decent for small and simple stuff (as I said, distillation of documentation). I use it for rust, where I am sure the training material was much smaller than other languages. It's not a matter a prompting though, it's not my prompt that makes it hallucinate functions that don't exist in libraries or make it write code that doesn't compile, it's a feature of the technology itself.
GPTs are statistical text generators after all, they don't "understand" the problem.
Exactly this. Things have already changed and are changing as more and more people learn how and where to use these technologies. I have seen even teachers use this stuff who have limited grasp of technology in general.
Review of legal documents.
Oh boy...what can possibly go wrong for documents where small minutiae like wording can make a huge difference.
Creating legal documents, no. Reviewing legal documents for errors and inaccuracies totally.
I really can't see this being done by any sane person. Why would you have a generator of text reviewing stuff (besides grammar)? Do you have any reference of some companies doing this, perhaps?
Its complex pattern matching and looking up existing case law online. This work has been outsourced to contracting companies for at least 7 years that I'm aware of. If it is something that can be documented in a run book for non professionals to do for twenty cents on the dollar then there is no reason it can't be done by a script for .002.
See now, I would prefer AI in my toaster. It should be able to learn to adjust the cook time to what I want no matter what type of bread I put in it. Though is that realky AI? It could be. Same with my fridge. Learn what gets used and what doesn't. Then give my wife the numbers on that damn clear box of salad she buys at costco everytime, which take up a ton of space and always goes bad before she eats even 5% of it. These would be practical benefits to the crap that is day to day life. And far more impactful then search results I can't trust.
You really wouldn't.
I was so hoping that was toasty the toaster! Waffles? How about a bagel?
You better believe that AI-powered toaster would only accept authorized bread from a bakery that paid top dollar to the company that makes them. To ensure the best quality possible and save you from inferior toast, of course.
Lol, enshitification should at least take a few months... I hope.
There's a good point here that like about 80% of what we're calling AI right now... isn't even AI or even LLM. It's just.... algorithm, code, plain old math. I'm pretty sure someone is going to refer to a calculator as AI soon. "Wow, it knows math! Just like a person! Amazing technology!"
(That's putting aside the very question of whether LLMs should even qualify as AIs at all.)
In my professional experience, AI seems to be just a faster way to generate an algorithm that is really hard to debug. Though I am dev-ops/sre so I am not as deep in it as the devs.