You must log in or register to comment.
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.
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.
If only Sun survived till now, I feel they would have good days
The problem is a lot of what Sun brought to the industry is now in the Linux arena. If Sun survived, would Linux have happened? With such a huge development infrastructure around Linux, would Sun really add value?
I was a huge fan of Sun also, they revolutionized the industry far above their footprint. However their approach seemed more research or academic at times, and didn’t really work with their business model. Red Hat figured out a balance where they could develop opensource while making enough to support their business. The Linux world figured out a different balance where the industry is above and beyond individual companies and doesn’t require profit
The problem is a lot of what Sun brought to the industry is now in the Linux arena. If Sun survived, would Linux have happened? With such a huge development infrastructure around Linux, would Sun really add value?
Linux is not better than Solaris. It was, however, circumstantially more affordable, more attractive, and more exciting than Solaris at the same time. They’ve made a lot of strategic mistakes, but those were in the context of having some vision.
I mean this to say that the “huge development infrastructure around Linux” is bigger, but much less efficient than that of any of BSDs, and than that of Solaris in the past. Linux people back then would take pride in ability to assemble bigger resources, albeit with smaller efficiency, and call that “the cathedral vs the bazaar”, where Linux is the bazaar. Well, by now one can see that the bazaar approach make development costs bigger long-term.
IMHO if Sun didn’t make those mistakes, Solaris would be the most prestigious Unix and Unix-like system, but those systems would be targeted by developers similarly. So Linux would be alive, but not much more or less popular than FreeBSD. I don’t think they’d need Solaris to defeat all other Unix systems. After all, in early 00s FreeBSD had SVR4 binary compatibility code, similarly to its Linux compatibility code, which is still there and widely used. Probably commercial software distributed in binaries would be compiled for that, but would run on all of them. Or maybe not.
It’s hard to say.
But this
The Linux world figured out a different balance where the industry is above and beyond individual companies and doesn’t require profit
is wrong, everything about Linux that keeps going now is very commercial. Maybe 10 years ago one could say it’s not all about profit.
The point is the industry is not a profit driven entity, but has room for many profit driven entities.
That’s like saying your body is not a protein driven mechanism (cause there are many other things involved), but has room for proteins.
If somebody tears out half of your internal organs, you die.
If profit-driven companies stop participating in Linux, Linux dies. Today’s Linux. Linux of year 1999 wouldn’t.
That’s how even gifts can be the needle to control you.
I mean, why is this even a point of contention. BSDs played safe in terms of politics, Linux gambled by not considering the dangers. BSDs grew more slowly, Linux took the bank. But now Linux is confined by the decisions made back then. BSDs are more free.
I’ve ran some college hw through 4o just to see and it’s remarkably good at generating proofs for math and algorithms. Sometimes it’s not quite right but usually on the right track to get started.
In some of the busier classes I’m almost certain students do this because my hw grades would be lower than the mean and my exam grades would be well above the mean.
deleted by creator
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.
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.
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?
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.
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.
No, not that either. Unless you consider “use LLM to summarize the changes/errors/inaccuracies, then have a human read the whole thing again” an improvement over “just have a human read the whole thing”.
Because LLM will do all these things:
- point you toward issues
- point you toward non-issues
- not point you toward issues
- change stuff even when “instructed” not to
If there is one thing you don’t want to throw an LLM at without full, unbiased review, it’s documents where the wording is legally binding. And if you have to do a full, unbiased review to begin with, where you can’t even trust your tool to have highlighted all the important parts, you may as well not bother with the tool.
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.
Aside from a handful of business that tried to do that and failed miserably, some of them failing in actual court, you mean?
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 TeslerThat’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!
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.
You can’t just throw out random Wikipedia links. For example, the Article on AGI explicitly says we don’t have a definition of what human level cognition actually is. Which is what the person you were replying to was saying. You’re doing a fallacious appeal to authority, except that the authority doesn’t agree with you.
Sometimes it seems like the biggest success of AI has been refining the definition of intelligence. But we still have a long way to go
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.
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.
And I’m sure each slice will have an entirely necessary chip on it, legally protected from workarounds , to
prevent using other brand or commodity breadensure the optimal experience
See now, I would prefer AI in my toaster.
I was so hoping that was toasty the toaster! Waffles? How about a bagel?
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.
So true.
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.
deleted by creator
Too bad it actively makes all of your work lower quality via the “helping”.
Just like every other coworker, it’s important to know what tasks they do well and where they typically need help
Lmao your stance is really “every coworker makes all product lower quality by nature of existence”? Thats some hardcore Cope you’re smoking.
Every coworker has a specific type of task they do well and known limits you should pay attention to.
Yes and therefor any two employees must never be allowed to speak to each other. You know, because it makes all of their work worse quality. /s
That’s quite the extreme interpretation.
I’m a lead software dev, and when deadlines are close, I absolutely divvy up tasks based on ability. We’re a webapp shop with 2D and 3D components, and I have the following on my team:
- 2 BE devs with solid math experience
- 1 senior BE without formal education, but lots of knowledge on frameworks
- 1 junior fullstack that we hired as primarily backend (about 75/25 split)
- 2 senior FE devs, one with a QA background
- 2 mid level FEs who crank out code (but miss some edge cases)
- 1 junior FE
That’s across two teams, and one of the senior FEs is starting to take over the other team.
If we’re at the start of development, I’ll pair tasks between juniors and seniors so the juniors get more experience. When deadlines are close, I’ll pair tasks with the most competent dev in that area and have the juniors provide support (write tests, fix tech debt, etc).
The same goes for AI. It’s useful at the start of a project to understand the code and gen some boilerplate, but I’m going to leave it to the side when tricky bugs need to get fixed or we can’t tolerate as many new bugs. AI is like a really motivated junior, it’s quick to give answers but slow to check their accuracy.
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.
I wasn’t playing Soul Caliber on the Dreamcast against AI openents…
Maybe terminology differs by region, but I absolutely played against AI as a kid. When I set up a game of Command and Conquer or something, I’d pick the number of AI opponents. Sometimes we’d call them bots (more common in FPS) or “the computer” or “CPU” (esp in Civ and other TBS), but I distinctly remember calling RTS SP opponents “AI” and I think many games used that terminology during the 90s.
What frustrates me is the opposite of what you’re saying, people have changed the meaning of “AI” from a human programmed opponent to a statistical model. When I played against “AI” 20-30 years ago, I was playing against something a human crafted and tuned. These days, I don’t play against “AI” because “AI” generates text, images, and video from a statistical model and can’t really play games. AI is something that runs in the cloud, with maybe a small portion on phones and Windows computers to do simple tasks where the network would add too much latency.
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.
I think “interactive clipart” is a great description. You are, I believe, totally correct that (at least for now) GenAI can’t do what professionals can do, but it can do better than many / most non-professionals. I can’t do art to save my life, and I don’t have the money to pay pros to make the mundane, boring everyday things that I need (like simple, uncluttered pictures for vocabulary cards). GenAI solves that problem for me.
Similarly, teachers used to try to rewrite complex texts for students at lower reading levels (such as English Learners). That took time and some expertise. Now, GenAI does it prolly many tens of thousands of times a day for teachers all over the USA.
I think, at least for the moment, that middle / lower level is where GenAI is currently most helpful - exactly the places that, in earlier times, were happy with clipart.
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.
Relaunching Stadia?
Haha. I believe the AMD Instinct / Nvidia Datacentre GPUs aren’t that great for gaming.
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
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.
Page doesn’t render properly.
deleted by creator
Thanks – it has been clear enough that an another AI winter is coming. Likely latest when the Global Financial Crisis 2 is here.
deleted by creator
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.
Based on what, exactly?
Based on the upcoming robot apocalypse, obviously.
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.
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…
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.
I just want you to know that actual scientists have morals. You are not a scientist and I’m coming to replace you.
Where do you work?
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.
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.
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
Many of these failures will go away
In a rational, non-capitalist world, yes. In our world, all of those data centres will last until they can’t find a way to squeeze some sort of profit out of them.
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.
Your example is strange because, as far as I know, GPTs aren’t economical either.
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).
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).
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?
