Watching the Generative AI Hype Bubble Deflate

A big issue that a lot of these tech companies seem to have is that they don't understand what people want; they come up with an idea and then shove it into everything. There are services that I have actively stopped using because they started cramming AI into things; for example I stopped dual-booting with Windows and became Linux-only.
AI is legitimately interesting technology which definitely has specialized use-cases, e.g. sorting large amounts of data, or optimizing strategies within highly restrained circumstances (like chess or go). However, 99% of what people are pushing with AI these days as a member of the general public just seems like garbage; bad art and bad translations and incorrect answers to questions.
I do not understand all the hype around AI. I can understand the danger; people who don't see that it's bad are using it in place of people who know how to do things. But in my teaching for example I've never had any issues with students cheating using ChatGPT; I semi-regularly run the problems I assign through ChatGPT and it gets enough of them wrong that I can't imagine any student would be inclined to use ChatGPT to cheat multiple times after their grade the first time comes in. (In this sense, it's actually impressive technology - we've had computers that can do advanced math highly accurately for a while, but we've finally developed one that's worse at math than the average undergrad in a gen-ed class!)
- The answer is that it's all about "growth". The fetishization of shareholders has reached its logical conclusion, and now the only value companies have is in growth. Not profit, not stability, not a reliable customer base or a product people will want. The only thing that matters is if you can make your share price increase faster than the interest on a bond (which is pretty high right now).
  To make share price go up like that, you have to do one of two things; show that you're bringing in new customers, or show that you can make your existing customers pay more.
  For the big tech companies, there are no new customers left. The whole planet is online. Everyone who wants to use their services is using their services. So they have to find new things to sell instead.
  And that's what "AI" looked like it was going to be. LLMs burst onto the scene promising to replace entire industries, entire workforces. Huge new opportunities for growth. Lacking anything else, big tech went in HARD on this, throwing untold billions at partnerships, acquisitions, and infrastructure.
  And now they have to show investors that it was worth it. Which means they have to produce metrics that show people are paying for, or might pay for, AI flavoured products. That's why they're shoving it into everything they can. If they put AI in notepad then they can claim that every time you open notepad you're "engaging" with one of their AI products. If they put Recall on your PC, every Windows user becomes an AI user. Google can now claim that every search is an AI interaction because of the bad summary that no one reads. The point is to show "engagement", "interest", which they can then use to promise that down the line huge piles of money will fall out of this pinata.
  The hype is all artificial. They need to hype these products so that people will pay attention to them, because they need to keep pretending that their massive investments got them in on the ground floor of a trillion dollar industry, and weren't just them setting huge piles of money on fire.
  
  I know I'm an enthusiast, but can I just say I'm excited about NotebookLLM? I think it will be great for documenting application development. Having a shared notebook that knows the environment and configuration and architecture and standards for an application and can answer specific questions about it could be really useful.
  "AI Notepad" is really underselling it. I'm trying to load up massive Markdown documents to feed into NotebookLLM to try it out. I don't know if it'll work as well as I'm hoping because it takes time to put together enough information to be worthwhile in a format the AI can easily digest. But I'm hopeful.
  That's not to take away from your point: the average person probably has little use for this, and wouldn't want to put in the effort to make it worthwhile. But spending way too much time obsessing about nerd things is my calling.
  
  The answer is that it’s all about “growth”. The fetishization of shareholders has reached its logical conclusion, and now the only value companies have is in growth. Not profit, not stability, not a reliable customer base or a product people will want. The only thing that matters is if you can make your share price increase faster than the interest on a bond (which is pretty high right now).
  As you can see, this can't go on indefinitely. And also such unpleasantries are well known after every huge technological revolution. Every time eventually resolved, and not in favor of those on the quick buck train.
  It's still not a dead end. The cycle of birth, growth, old age, death, rebirth from the ashes and so on still works. It's only the competitive, evolutionary, "fast" model has been killed - temporarily.
  These corporations will still die unless they make themselves effectively part of the state.
  BTW, that's what happened in Germany described by Marx, so despite my distaste for marxism, some of its core ideas may be locally applicable with the process we observe.
  It's like a worldwide gold rush IMHO, but not even really worldwide. There are plenty of solutions to be developed and sold in developing countries in place of what fits Americans and Europeans and Chinese and so on, but doesn't fit the rest. Markets are not exhausted for everyone. Just for these corporations because they are unable to evolve.
  Lacking anything else, big tech went in HARD on this, throwing untold billions at partnerships, acquisitions, and infrastructure.
  If only Sun survived till now, I feel they would have good days. What made them fail then would make them more profitable now. They were planning too far ahead probably, and were too careless with actually keeping the company afloat.
  My point is that Sun could, unlike these corporations, function as some kind of "the phone company", or "the construction company", etc. Basically what Microsoft pretended to be in the 00s. They were bad with choosing the right kind of hype, but good with having a comprehensive vision of computing. Except that vision and its relation to finances had schizoaffective traits.
  Same with DEC.
  The point is to show “engagement”, “interest”, which they can then use to promise that down the line huge piles of money will fall out of this pinata.
  Well. It's not unprecedented for business opportunities to dry out. It's actually normal. What's more important, the investors supporting that are the dumber kind, and the investors investing in more real things are the smarter kind. So when these crash (for a few years hunger will probably become a real issue not just in developing countries when that happens), those preserving power will tend to be rather insightful people.
- I understand some of the hype. LLMs are pretty amazing nowadays (though closedai is unethical af so don't use them).
  I need to program complex cryptography code for university. Claude sonnet 3.5 solves some of the challenges instantly.
  And it's not trivial stuff, but things like "how do I divide polynomials, where each coefficient of that polynomial is an element of GF(2^128)." Given the context (my source code), it adds it seamlessly, writes unit tests, and it just works. (That is important for AES-GCM, the thing TLS relies on most of the time .)
  Besides that, LLMs are good at what I call moving words around. Writing cute little short stories in fictional worlds given some info material, or checking for spelling, or re-formulating a message into a very diplomatic nice message, so on.
  On the other side, it's often complete BS shoehorning LLMs into things, because "AI cool word line go up".

- 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.
- 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.
  
  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
  
  Review of legal documents.
- 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.
  
  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?
  
  "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.
  
  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.
- 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.
- 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.
- 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.)
  
  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.
  
  See now, I would prefer AI in my toaster.
  You really wouldn't.
  
  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
- Like what outcome?
  I have seen gains on cell detection, but it's "just" a bit better.

"Built to do my art and writing so I can do my laundry and dishes" -- Embodied agents is where the real value is. The chatbots are just fancy tech demos that folks started selling because people were buying.
- Too bad it actively makes all of your work lower quality via the "helping".
- Though the image generators are actually good. The visual arts will never be the same after this
  
  Compare it to the microwave. Is it good at something, yes. But if you shoot your fucking turkey in it at Thanksgiving and expect good results, you're ignorant of how it works. Most people are expecting language models to do shit that aren't meant to. Most of it isn't new technology but old tech that people slapped a label on as well. I wasn't playing Soul Caliber on the Dreamcast against AI openents... Yet now they are called AI opponents with no requirements to be different. GoldenEye on N64 was man VS AI. Madden 1995... AI. "Where did this AI boom come from!"
  Marketing and mislabeling. Online classes, call it AI. Photo editors, call it AI.
  
  Sometimes I really regret having signed onto an instance that disables downvotes.
  
  I've been thinking about this a lot recently. No, we're not there yet, may never be. Compare what Jesar, one of my favorite artists, can do - and that was in the oh-so-long-ago 2000s - and what an AI can do. It's simply not up to the task. I do use AI a lot to create what is basically utility art. But it depends on pre-defined textual or visual inputs whereas only an artist can have divine inspiration. AI is more of a sterile tool, like interactive clipart, if you will.

At a beach restaurant the other night I kept hearing a loud American voice cut across all conversation, going on and on about “AI” and how it would get into all human “workflows” (new buzzword?). His confidence and loudness was only matched by his obvious lack of understanding of how LLMs actually work.
- "Confidently incorrect" I think describes a lot of AI aficionados.
  
  And LLMs themselves.
  
  I would also add "hopeful delusionals" and "unhinged cultist" to that list of labels.
  Seriously, we have people right now making their plans for what they're going to do with their lives once Artificial Super Intelligence emerges and changes the entire world to some kind of post-scarcity, Star-Trek world where literally everyone is wealthy and nobody has to work. They think this is only several years away. Not a tiny number either, and they exist on a broad spectrum.
  Our species is so desperate for help from beyond, a savior that will change the current status-quo. We've been making fantasies and stories to indulge this desire for millenia and this is just the latest incarnation.
  No company on Earth is going to develop any kind of machine or tool that will destabilize the economic markets of our capitalist world. A LOT has to change before anyone will even dream of upending centuries of wealth-building.
  
  AI itself too i guess. Also i have to point this out every time but my username was chosen way before all this shit blew up into our faces. Ive used this one on every platform for years.
- Some people can only hear "AI means I can pay people less/get rid of them entirely" and stop listening.
  
  AI means C level jobs should be on the block as well. The board can make decisions based on their output.
  
  Just wait until Elon puts AI in those new robots he invented!!!
  /s for those who need it…
- I've noticed that the people most vocal about wanting to use AI get very coy when you ask them what it should actually do.
  
  I also notice the ONLY people who can offer firsthand reports how it's actually useful in any way are in a very, very narrow niche.
  Basically, if you're not a programmer, and even then a very select set of programmers, then your life is completely unimpacted by generative AI broadly. (Not counting the millions of students who used it to write papers for them.)
  AI is currently one of those solutions in search of a problem. In its current state, it can't really do anything useful broadly. It can make your written work sound more professional and at the same time, more mediocre. It can generate very convincing pictures if you invest enough time into trying to decode the best sequence of prompts and literally just get lucky, but it's far too inacurate and inconsistent to generate say, a fully illustrated comic book or cartoon, unless you already have a lot of talent in that field. I have tried many times to use AI in my current job to analyze PDF documents and spreadsheets and it's still completely unable to do work that requires mathematics as well as contextual understanding of what that math represents.
  You can have really fun or cool conversations with it, but it's not exactly captivating. It is also wildly inaccurate for daily use. I ask it for help finding songs by describing the lyrics and other clues, and it confidentially points me to non-existing albums by hallucinated artists.
  I have no doubt in time it's going to radically change our world, but that time frame is going to require a LOT more time and baking before it's done. Despite how excited a few select people are, nothing is changing overnight. We're going to have a century-long "singularity" and won't realize we've been through it until it's done. As history tends to go.
  
  Because as a social phenomenon it promises to decide for them what it should actually do.
  
  Porn / ai gf. Thats what 90% of ai power users do.
- I really like the idea of an LLM being narrowly configured to filter, summarize data which comes in at a irregular/organic form.
  You would have to do it multiples in parallel with different models and slightly different configurations to reduce hallucinations (Similar to sensor redundancies in Industrial Safety Levels) but still, ... that alone is a game changer in "parsing the real world" .... that energy amount needed to do this "right >= 3x" is cut short by removing the safety and redundancy because the hallucinations only become apparent down the line somewhere and only sometimes.
  They poison their own well because they jump directly to the enshittyfication stage.
  So people talking about embedding it into workflow... hi... here I am! =D
  
  A buddy of mine has been doing this for months. As a manager, his first use case was summarizing the statuses of his team into a team status. Arguably hallucinations aren’t critical

But the line must go up!
- The article does mention that when the AI bubble is going down, the big players will use the defunct AI infrastructure and add it to their cloud business to get more of the market that way and, in the end, make the line go up.
  
  That's not what the article says.
  They're arguing that AI hype is being used as a way of driving customers towards cloud infrastructure over on-prem. Once a company makes that choice, it's very hard to get them to go back.
  They're not saying that AI infrastructure specifically can be repurposed, just that in general these companies will get some extra cloud business out of the situation.
  AI infrastructure is highly specialized, and much like ASICs for the blockchain nonsense, will be somewhere between "very hard" and "impossible" to repurpose.
  
  Assuming a large decline in demand for AI compute, what would be the use cases for renting out older AI compute hardware on the cloud? Where would the demand come from? Prices would also go down with a decrease in demand.

So you're saying we wont have any crowdsourced blockchain Web 2.0 AIs?
- Quantum! don't forget quantum, you filthy peasant.
- Nope. No Crowdsourced Blockchain Web 3.0 VR+AR AI NFTs.
- Please, stay with the time. We're at Web 6.0 already.
- Where's my federated open source AI that runs on Linux 😤
- The drones doing airstrikes might!

Big tech is out of ideas and needs AI to work in order to drive growth.

oh wow who would have guessed that business consultancy companies are generally built on bullshitting about things which they dont really have a grasp of

Bye bye XBox ._.

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- Thanks -- it has been clear enough that an another AI winter is coming. Likely latest when the Global Financial Crisis 2 is here.

- I'm loading up on vacuum tubes.
  
  They make the LLM responses "warmer".
  
  I'm stocked up on obsolete media formats.
- The hype of massive LLMs will die, but smaller companies in all sectors are only increasing the amount of GPUs they're buying.
- You do you, but I think there's a good chance we see a pullback, followed by a pivot, followed by a more sustained rise. Basically, once investors realize AI can't deliver on the promises of the various marketing depts, they'll pull investment, and then some new tech or application will demonstrate sustained demand.
  I think we're at that first crest, so I expect a pullback in the next few years. In short, I expect AI to experience something like what the Internet experienced at the turn of the millennium.
- Based on what, exactly?
  
  Based on the upcoming robot apocalypse, obviously.

To have a bubble you need companies with no clear path to monetization, being over-valued to an extreme degree. This leaves me wondering : what company specifically ? Are they talking about nVidia ? OpenAI ? MidJourney ? Or the slew of LLM-powered SaaS products that have started appearing ? How exactly are we defining "over-valuation" here ? Are we talking about the tech industry as a whole ?
We often invite the comparison to the DotCom bubble but that's apples to oranges. You had companies making social networks for dogs or similar bullshit, valued in the billions and getting a ticker at the stock market before making a single dime. Or companies with outlandish promises such as delivering to any home in the US, in <1 hour, for a low price, and building warehouses by the hundreds before having a storefront. What would be the 2024 equivalent ? If a bubble is about to deflate then there should be dozens of comparable examples.
- Exactly. There's a very clear path to monetisation for the bigger tech companies (ofc, not the random startup that screams "AI quantum computing blockchain reeeee").
  Lemmy is just incredibly biased against AI, as it could replace a shit ton of jobs and lead to a crazy amount of wealth inequality. However, people need to remember that the problem isn't the tech- it's the system that the tech is being innovated in.
  Denying AI is just going to make this issue a lot worse. We need to work to make AI be beneficial for all of us instead of the capitalists. But somehow leftist talk surrounding AI has just been about hating on it/ denying it, instead of preparing for a world in which it would be critical infrastructure very soon.
  
  What job could possibly replace...? If you can replace a job with LLMs it means either that the job is not needed on the first place (bullshit job) or that you can replace it with a dice (e.g., decision-making processes), since LLMs-output will depend essentially just on what is in the training material -which we don't know (I.e., the answer is essentially random).
  
  I don't think it's just Lemmy, i had similar conversations on Reddit. People don't realize that the companies they claim are over-valued actually have very strong business fundamentals. That's why in articles like OP's they will never mention any names or figures. I guess it's very convincing for outsiders but it doesn't stand any amount of scrutiny.
  If you take OpenAI for example, they went from 0 to 3.6B$ annual revenue in just two fucking years. How is that not worth a boatload of money ? Even Uber didn't have that kind of growth and they burned a LOT more cash than OpenAI is burning right now.
  As for the “AI quantum computing blockchain reeeee” projects... well they have a very hard time raising money right now and when they do, it's at pretty modest valuations. The market is not as dumb as it is portrayed.

Education is one area where GenAI is having a huge impact. Teachers work with text and language all day long. They have too much to do and not enough time to do it. Ideally, for example, they should "differentiate" for EACH and EVERY student. Of course that almost never happens, but second best is to differentiate for specific groups - students with IEPs (special ed), English Learners, maybe advanced / gifted.
More tech aware teachers are now using ChatGPT and friends to help them do this. They are (usually) subject area experts, so they can quickly read through a generated or modified text and fix or remove errors - hallucinations are less (ime) of an issue in this situation. Now, instead of one reading that only a few students can actually understand, they have three at different levels, each with their own DOK questions.
People have started saying "AI won't replace teachers. Teachers who use AI will replace teachers who don't."
Of course, it will be interesting to see what happens when VC funding dries up, and the AI companies can't afford to lose money on every single interaction. Like with everything else in USA education, better off districts may be able to afford AI, and less-well-off (aka black / brown / poor) districts may not be able to.

I saved a lot of time due to ChatGPT. Need to sign up some of my pupils for a competition by uploading their data in a csv-File to some plattform? Just copy and paste their data into chsatgpt and prompt it to create the file. The boss (headmaster) wants some reasoning why I need some paid time for certain projects? Let ChatGPT do the reasoning. Need some exercises for one of my classes that doesn't really come to grips with while-loops? let ChatGPT create those exercises (some smartasses will of course have ChatGPT then solve those exercises). The list goes on...
- Just copy and paste [student personal data] into [3rd parties database]
  Yeah, that's a problem, especially in Europe. Im unsure about US, but it's definitely a breach of GDPR.
- You are an asshole if you're uploading student data to a mining operation.
  
  Well, I hope the data protection official of my school won't find out. Oh wait, shit. He did find out. It's me and idgaf.
- Yeah, and Wikipedia is one of the most useful sites on the net, but it didn't exactly result in the entire web becoming crowdsourced.
- ChatGPT is basically like a really good intern, and I use it heavily that way. I run literally every email through it and say "respond to so and so, say xyz" and then maybe a little refining, copy paste, done.
  The other day, my boss sent me an excel file with a shitload of data in it that he wanted me to analyze some such way. I just copy pasted it into gpt and asked it, and it spit out the correct response. Then my boss asked me to do something else that required a bit of excel finagling that I didn't really know how to do, so i asked gpt, and it told me the formula, which worked immediately first try.
  So basically it helps me accomplish tasks in seconds that previously would've taken hours. If anything, I think markets are currently undervalued, because remarkably, fucking NONE of my colleagues or friends are using it at all yet. Once there's widespread adoption, which will pretty much have to happen if anyone wants to stay competitive once it gains more traction, look out...
  
  That also is my experience.
- The poem about AI that often gets posted says "What are you trying to avoid? The living [of a life]?"
  And yeah, that's what it's for, dodging shit you don't want to do. I gotta produce some useless bullshit that no one's going to read or care about: AI.
  I don't even mind AI art for things like LinkedIn posts, blogs like "What is warehouse management?" or "Top 10 finance trends in 2025" - SEO spam that no human will read. No one wants to write it, read it, or care about it- its just a x kb file to tell Google to look here.
- Those pupils will really thank you when they grow up and there isn't enough fresh water because all the data centres are using it up far faster than it can be replenished.
  https://utulsa.edu/news/data-centers-draining-resources-in-water-stressed-communities/
  
  The thing about tech bubbles is everyone rushes in full bore, on the hope that they can be the ones whose moonshot goes the distance. However even in the case where the technology achieves all its promise, most of those early attempts will not. Soon enough, we’ll be down to the top few, and only their datacenters will need to exist. Many of these failures will go away
- One time, I needed to convince my boss's boss that we needed to do something, and he wanted it in writing. Guess who wrote the proposal? And far more eloquently than I could have alone, in the time allowed. It required some good prompts, attentive proofreading, and a few drafts. But in the end, it was quite effective.

"Today’s hype will have lasting effects that constrain tomorrow’s possibilities."
Nope. No it won't. I'd love to have the patience to be more diplomatic but they're just wrong... and dumb.
I'm getting so sick of these anti AI cultists who seem to be made up of grumpy tech nerds behaving like "I was using AI before it was cool" hipsters and panicking artists and writers. Everyone needs to calm their tits right down. AI isn't going anywhere. It's giving creative and executive options to millions of people that just weren't there before.
We're in an adjustment phase right now and boundaries are being re-drawn around what constitutes creativity. My leading theory at the moment is that we'll all mostly eventually settle down to the idea that AI is just a tool. Once we're used to it and less starry eyed about it's output then individual creativity, possibly supported by AI tools, will flourish again. It's going to come down to the question of whether you prefer reading something cogitated, written, drawn or motion rendered by AI or you enjoy the perspective of a human being more. Both will be true in different scenarios I expect.
Honestly, I've had to nope out of quite a few forums and servers permanently now because all they do in there is circlejerk about the death of AI. Like this one theory that keeps popping up that image generating AI specifically is inevitably going to collapse in on itself and stop producing quality images. The reverse is so obviously true but they just don't want to see it. Otherwise smart people are just being so stubborn with this and it's, quite frankly, depressing to see.
Also, the tech nerds arguing that AI is just a fancy word and pixel regurgitating engine and that we'll never have an AGI are probably the same people that were really hoping Data would be classified as a sentient lifeform when Bruce Maddox wanted to dissassemble him in "The Measure of a Man".
How's that for whiplash?
- Models are not improving, companies are still largely (massively) unprofitable, the tech has a very high environmental impact (and demand) and not a solid business case has been found so far (despite very large investments) after 2 years.
  That AI isn't going anywhere is possible, but LLM-based tools might also simply follow crypto, VR, metaverses and the other tech "revolutions" that were just hyped and that ended nowhere. I can't say it will go one way or another, but I disagree with you about "adjustment period". I think generative AI is cool and fun, but it's a toy. If companies don't make money with it, they will eventually stop investing into it.
  Also
  Today’s hype will have lasting effects that constrain tomorrow’s possibilities
  Is absolutely true. Wasting capital (human and economic) on something means that it won't be used for something else instead. This is especially true now that it's so hard to get investments for any other business. If all the money right now goes into AI, and IF this turns out to be just hype, we just collectively lost 2, 4, 10 years of research and investments on other areas (for example, environment protection). I am really curious about what makes you think that that sentence is false and stupid.
  
  Models are not improving? Since when? Last week? Newer models have been scoring higher and higher in both objective and subjective blind tests consistently. This sounds like the kind of delusional anti-AI shit that the OP was talking about. I mean, holy shit, to try to pass off "models aren't improving" with a straight face.
- It's fucking fantastic news, tbh.
  Here's my take, let them dismiss it.
  Let em! Remember Bitcoin at $15k after 2019?
  Let em! And it's justified! If Ai isn't important right now, then why should its price be inflated to oblivion? Let it fall. Good! Lower prices for those of us that do see the value down the road.
  That's how speculative investment works. In no way is this bad. Are sales bad? Sit back and enjoy the show.
  
  Are sales bad?
  Of AI products? By all available metrics, yes, sales for AI driven products are atrocious.
  Even the biggest name in AI is desperately unprofitable. OpenAI has only succeeded in converting 3% of their free users to paid users. To put that on perspective, 40% of regular Spotify users are on premium plans.
  And those paid plans don't even cover what it costs to run the service for those users. Currently OpenAI are intending to double their subscription costs over the next five years, and that still won't be enough to make their service profitable. And that's assuming that they don't lose subscribers over those increased costs. When their conversion rate at their current price is only 3%, there's not exactly an obvious appetite to pay more for the same thing.
  And that's the headline name. The key driver of the industry. And the numbers are just as bad everywhere else you look, either terrible, or deliberately obfuscated (remember, these companies sank billions of capex into this; if sales were good they'd be talking very openly and clearly about just how good they are).

I have no idea how people can consider this to be a hype bubble especially after the o3 release. It smashed the ARC AGI benchmark on the performance front. It ranks as the 175th best competitive coder in the world on Codeforces' leaderboard.
o3 proved that it is possible to have at least an expert AGI if not a Virtuoso AGI (according to Deep mind's definition of AGI). Sure, it's not economical yet. But it will get there very soon (just like how the earlier GPTs were a lot dumber and took a lot more energy than the newer, smaller parameter models).
Please remember - fight to seize the means of production. Do not fight the means of production themselves.
- It's a bubble because OpenAI spend $2.35 for every $1.00 they make. Yes, you're mathing right, that is a net loss.
  It's a bubble because all of the big players in AI development agree that future models will cost exponentially more money to train, for incremental gains. That means there is no path forward that doesn't intensely amplify the unprofitability of an already deeply unprofitable industry.
  It's a bubble because newer models with better capabilities only cost more and more to run.
  It's a bubble because as far as anyone knows there will never be a solution to the hallucination problem.
  It's a bubble because despite investments treating it as a trillion dollar industry, no one has yet figured out a trillion dollar problem that AI can solve.
  You're trying on a new top of the line VR headset and saying "Wow, this is incredible, how can anyone say this is a bubble?" Its not about how cool the tech is in isolation, it's about its potential to effect widespread change. Facebook went in hard on VR, imagining a future where everyone worked from home while wearing VR headsets. But what they got was an expensive toy that only had niche uses.
  AI performs do well on certain coding tasks because a lot of the individual problems that make up a particular piece of software have already been solved. It's standard practice to design programs as individual units, each of which performs the smallest task possible, and which can then be assembled to complete more complex tasks. This fits very well into the LLM model of assembling pieces into their most likely expected configurations. But it cannot create truly novel code, except by a kind of trial and error mutation process. It cannot problem solve. It cannot identify a users needs and come up with ideal solutions to them. It cannot innovate.
  This means that, at best, genAI in the software world becomes a tool for producing individual code elements, guided and shepherded by experienced programmers. It does not replace the software industry, merely augments it, and it does so at a cost that many companies simply may not feel is worth paying.
  And that's its best case scenario. In every other industry AI has been a spectacular failure. But it's being invested in as if it will be a technological reckoning for every form of intellectual labour on earth. That is the absolute definition of a bubble.
- o3 made the high score on ARC through brute force, not by being good. To raise the score from 75% to 87% required 175 times more computing power, but exactly stunning returns.
  
  Why does it matter?
  If it can through brute force, it can do it. That's the first step towards true agi, nobody said the first AGI would be economical, this feels like a major goalpost shift if you're acknowledging it can do it at all, isn't that insane?
  A little bit ago, everyone would've been saying this will never happen, that there was a natural wall simply because all it does is predict the next token, it's been like, a few years of llm's and they're already getting this insane. We're going to have AGI soon, it might not be a transformer, but billions upon billions of dollars are being thrown at this problem, there are people smart enough in the world to make this work, and this is the earliest sign that it's coming.
- Where, in that position piece, do they mention o3? Who "proved" this?
  Additionally, I'm pretty sure that this "ARC AGI" benchmark is not using the same definition of AGI that you linked to by DeepMind. Conflating them is misleading. There is already so much misinformation out there about "AI", don't add to it.
  Lastly, I struggle to take at face value essays written by for-profit companies claiming they have AGI (that DeepMind paper links to OpenAI essays). They only stand to gain monetarily by claiming that their AI is an AGI (to be clear, this is an opinion; I do not have evidence to suggest that OpenAI is being disingenuous).
- Unless we invent cold fusion between the next 5 years, they will never be economical. They are the most energy inefficient thing ever invented by humanity and all prediction models state that it will cost more energy, not less, to keep making them better. They will never be energy efficient nor economical in their current state, and most companies are out of ideas on how to shake it up. Even the people who created generative models agree that they have just been brute forcing by making the models larger with more energy consumption. When you try to make them smaller or more energy efficient, they fall off the performance cliff and only produce garbage. I'm sure there are researchers doing cool stuff, but it is neither economical nor efficient.
  
  Untrue. There are small models that produce better output than the previous "flagships" like GPT-2. Also, you can achieve much more than we currently do with far less energy by working on novel, specialised hardware (neuromorphic computing).
- Your example is strange because, as far as I know, GPTs aren't economical either.
- Why is it getting an AGI stamp now? I was under the impression humanity has not delivered a sentient AI? Which is what the AGI title was supposed to be used for...has that been pulled back again?
  
  Agi has nothing to do with sentience, which cannot be measured, openai, I think validly, defines it as a system that can do all intellectual labor.