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.
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.
“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.
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!
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
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.
Downvoting someone on the Internet is easier than tangentially modifying reality in a measurable way
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.
Humans are notoriously worse at tasks that have to do with reviewing than they are at tasks that have to do with creating. Editing an article is more boring and painful than writing it. Understanding and debugging code is much harder than writing it etc., observing someone cooking to spot mistakes is more boring than cooking etc.
This also fights with the attention required to perform those tasks, which means a higher ratio of reviewing vs creating tasks leads to lower quality output because attention is depleted at some point and mistakes slip in. All this with the additional “bonus” to have to pay for the tool AND the human reviewing while also wasting tons of water and energy. I think it’s wise to ask ourselves whether this makes sense at all.
If you consider debugging broken LLM-generated code to be a skill… sure, go for it. But, since generated code is able to use tons of unknown side effects and other seemingly (for humans) random stuff to achieve its goal, I’d rather take the other approach, where it takes a human half an hour to write the code that some LLM could generate in seconds, and not have to learn how to parse random mumbo jumbo from a machine, while getting a working result.
Writing code is far from being the longest part of the job; and you gingerly decided that making the tedious part even more tedious is a great idea to shorten the already short part of it…
I have one of those at work now, but my experience with it is still quite limited. With Copilot it was quite useful for knocking up quick boutique solutions for particular problems (stitch together a load of PDFs sorted on a name heading), with the proviso that you might end up having to repair bleed between dependency versions and repair syntax. I couldn’t trust it with big refactors of existing systems.
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 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.
The large financial company that I work for
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.
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.
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.
See now, I would prefer AI in my toaster.
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.
I agree with your wife: there’s always an aspirational salad in the fridge. For most foods, I’m pretty good at not buying stuff we won’t eat, but we always should eat more veggies. I don’t know how to persuade us to eat more veggies, but step 1 is availability. Like that Reddit meme
- Availability
- ???
- Profit by improved health
It’s been years… maybe we don’t need the costco size for the love of pete.
Even if they plateaued in place where they are right now it would lead to major shakeups in humanity’s current workflow
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.
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.
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?
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.
@remindme@mstdn.social 1 year. Let me know about the seachange of new 10x transform based programmers that have automated me out of a job.
Oh boy…what can possibly go wrong for documents where small minutiae like wording can make a huge difference.
I don’t know anything about the online news business but it certainly appears to have changed. Most of it is dreck, either way, and those organizations are not a positive contributor to society, but they are there, it is a business, and it has changed society
I don’t see the change. Sure, there are spam websites with AI content that were not there before, but is this news business at all? All major publishers and newspapers don’t (seem to) use AI as far as I can tell.
Also I would argue this is no much of a change except maybe in simplicity to generate fluff. All of this existed already for 20 years now, and it’s a byproduct of the online advertisement business (that for sure was a major change in society!). AI pieces are just yet another way to generate content in the hope of getting views.
Goldman Sachs, quote from the article:
“AI technology is exceptionally expensive, and to justify those costs, the technology must be able to solve complex problems, which it isn’t designed to do.”
Generative AI can indeed do impressive things from a technical standpoint, but not enough revenue has been generated so far to offset the enormous costs. Like for other technologies, It might just take time (remember how many billions Amazon burned before turning into a cash-generating machine? And Uber has also just started turning some profit) + a great deal of enshittification once more people and companies are dependent. Or it might just be a bubble.
As humans we’re not great at predicting these things including of course me. My personal prediction? A few companies will make money, especially the ones that start selling AI as a service at increasingly high costs, many others will fail and both AI enthusiasts and detractors will claim they were right all along.
