Majority of AI Researchers Say Tech Industry Is Pouring Billions Into a Dead End
A survey of nearly 500 AI researchers indicated that the vast majority of them think that pursuing "scaling" won't achieve AGI.
This is slightly misleading. Even if you can't achieve "agi" (a barely defined term anyways) it doesn't mean AI is a dead end.
I like my project manager, they find me work, ask how I'm doing and talk straight.
It's when the CEO/CTO/CFO speaks where my eyes glaze over, my mouth sags, and I bounce my neck at prompted intervals as my brain retreats into itself as it frantically tosses words and phrases into the meaning grinder and cranks the wheel, only for nothing to come out of it time and time again.
COs are corporate politicians, media trained to only say things which are completely unrevealing and lacking of any substance.
This is by design so that sensitive information is centrally controlled, leaks are difficult, and sudden changes in direction cause the minimum amount of whiplash to ICs as possible.
I have the same reaction as you, but the system is working as intended. Better to just shut it out as you described and use the time to think about that issue you're having on a personal project or what toy to buy for your cat's birthday.
Right, that sweet spot between too less stimuli so your brain just wants to sleep or run away and enough stimuli so you can't just zone out (or sleep).
Find a better C-suite
The number of times my CTO says we're going to do THING, only to have to be told that this isn't how things work...
I just turn of my camera and turn on Forza Motorsport or something like that
The problem is that those companies are monopolies and can raise prices indefinitely to pursue this shitty dream because they got governments in their pockets. Because gov are cloud / microsoft software dependent - literally every country is on this planet - maybe except China / North Korea and Russia. They can like raise prices 10 times in next 10 years and don't give a fuck. Spend 1 trillion on AI and say we're near over and over again and literally nobody can stop them right now.
IBM used to controll the hardware as well, what's the moat?
How many governments were using computers back then when IBM was controlling hardware and how many relied on paper and calculators ? The problem is that gov are dependend on companies right now, not companies dependent on governments.
Imagine Apple, Google, Amazon and Microsoft decides to leave EU on Monday. They say we ban all European citizens from all of our services on Monday and we close all of our offices and delete data from all of our datacenters. Good Fucking Luck !
What will happen in Europe on Monday ? Compare it with what would happen if IBM said 50 years ago they are leaving Europe ?
I have been shouting this for years. Turing and Minsky were pretty up front about this when they dropped this line of research in like 1952, even lovelace predicted this would be bullshit back before the first computer had been built.
The fact nothing got optimized, and it still didn't collapse, after deepseek? kind of gave the whole game away. there's something else going on here. this isn't about the technology, because there is no meaningful technology here.
I have been called a killjoy luddite by reddit-brained morons almost every time.
What’re you talking about? What happened in 1952?
I have to disagree, I don’t think it’s meaningless. I think that’s unfair. But it certainly is overhyped. Maybe just a semantic difference?
Companies aren't investing to achieve AGI as far as I'm aware, that's not the end game so I this title is misinformation. Even if AGI was achieved it'd be a happy accident, not the goal.
The goal of all these investments is to convince businesses to replace their employees with AI to the maximum extent possible. They want that payroll money.
The other goal is to cut out all third party websites from advertising revenue. If people only get information through Meta or Google or whatever, they get to control what's presented. If people just take their AI results at face value and don't actually click through to other websites, they stay in the ecosystem these corporations control. They get to sell access to the public, even more so than they do now.
It's ironic how conservative the spending actually is.
Awesome ML papers and ideas come out every week. Low power training/inference optimizations, fundamental changes in the math like bitnet, new attention mechanisms, cool tools to make models more controllable and steerable and grounded. This is all getting funded, right?
No.
Universities and such are seeding and putting out all this research, but the big model trainers holding the purse strings/GPU clusters are not using them. They just keep releasing very similar, mostly bog standard transformers models over and over again, bar a tiny expense for a little experiment here and there. In other words, it’s full corporate: tiny, guaranteed incremental improvements without changing much, and no sharing with each other. It’s hilariously inefficient. And it relies on lies and jawboning from people like Sam Altman.
Deepseek is what happens when a company is smart but resource constrained. An order of magnitude more efficient, and even their architecture was very conservative.
Good, let them go broke in the pursuit of a dead end.
It doesnt matter if they reach any end result, as long as stocks go up and profits go up.
Consumers arent really asking for AI but its being used to push new hardware and make previous hardware feel old. Eventually everyone has AI on their phone, most of it unused.
If enough researchers talk about the problems then that will eventually break through the bubble and investors will pull out.
We're at the stage of the new technology hype cycle where it crashes, essentially for this reason. I really hope it does soon because then they'll stop trying to force it down our throats in every service we use.
Why won't they pour billions into me? I'd actually put it to good use.
I'd be happy with a couple hundos.
I'd be happy with a big tiddy goth girl. Jealous of your username btw.
The actual survey result:
Asked whether "scaling up" current AI approaches could lead to achieving artificial general intelligence (AGI), or a general purpose AI that matches or surpasses human cognition, an overwhelming 76 percent of respondents said it was "unlikely" or "very unlikely" to succeed.
So they're not saying the entire industry is a dead end, or even that the newest phase is. They're just saying they don't think this current technology will make AGI when scaled. I think most people agree, including the investors pouring billions into this. They arent betting this will turn to agi, they're betting that they have some application for the current ai. Are some of those applications dead ends, most definitely, are some of them revolutionary, maybe
Thus would be like asking a researcher in the 90s that if they scaled up the bandwidth and computing power of the average internet user would we see a vastly connected media sharing network, they'd probably say no. It took more than a decade of software, cultural and societal development to discover the applications for the internet.
It's becoming clear from the data that more error correction needs exponentially more data. I suspect that pretty soon we will realize that what's been built is a glorified homework cheater and a better search engine.
what's been built is a glorified homework cheater and an
betterunreliable search engine.
The bigger loss is the ENORMOUS amounts of energy required to train these models. Training an AI can use up more than half the entire output of the average nuclear plant.
AI data centers also generate a ton of CO². For example, training an AI produces more CO² than a 55 year old human has produced since birth.
Complete waste.
I agree that it's editorialized compared to the very neutral way the survey puts it. That said, I think you also have to take into account how AI has been marketed by the industry.
They have been claiming AGI is right around the corner pretty much since chatGPT first came to market. It's often implied (e.g. you'll be able to replace workers with this) or they are more vague on timeline (e.g. OpenAI saying they believe their research will eventually lead to AGI).
With that context I think it's fair to editorialize to this being a dead-end, because even with billions of dollars being poured into this, they won't be able to deliver AGI on the timeline they are promising.
Part of it is we keep realizing AGI is a lot more broader and more complex than we think
AI isn't going to figure out what a customer wants when the customer doesn't know what they want.
Yeah, it does some tricks, some of them even useful, but the investment is not for the demonstrated capability or realistic extrapolation of that, it is for the sort of product like OpenAI is promising equivalent to a full time research assistant for 20k a month. Which is way more expensive than an actual research assistant, but that's not stopping them from making the pitch.
I think most people agree, including the investors pouring billions into this.
The same investors that poured (and are still pouring) billions into crypto, and invested in sub-prime loans and valued pets.com at $300M? I don't see any way the companies will be able to recoup the costs of their investment in "AI" datacenters (i.e. the $500B Stargate or $80B Microsoft; probably upwards of a trillion dollars globally invested in these data-centers).
Right, simply scaling won’t lead to AGI, there will need to be some algorithmic changes. But nobody in the world knows what those are yet. Is it a simple framework on top of LLMs like the “atom of thought” paper? Or are transformers themselves a dead end? Or is multimodality the secret to AGI? I don’t think anyone really knows.
No there's some ideas out there. Concepts like heirarchical reinforcement learning are more likely to lead to AGI with creation of foundational policies, problem is as it stands, it's a really difficult technique to use so it isn't used often. And LLMs have sucked all the research dollars out of any other ideas.
Optimizing AI performance by “scaling” is lazy and wasteful.
Reminds me of back in the early 2000s when someone would say don’t worry about performance, GHz will always go up.
don’t worry about performance, GHz will always go up
TF2 devs lol
Thing is, same as with GHz, you have to do it as much as you can until the gains get too small. You do that, then you move on to the next optimization. Like ai has and is now optimizing test time compute, token quality, and other areas.
To be fair, GHz did go up. Granted, it's not why modern processors are faster and more efficient.
It always wins in the end though. Look up the bitter lesson.
I miss flash players.
The funny thing is with so much money you could probably do lots of great stuff with the existing AI as it is. Instead they put all the money into compute power so that they can overfit their LLMs to look like a human.
They're throwing billions upon billions into a technology with extremely limited use cases and a novelty, at best. My god, even drones fared better in the long run.
I mean it's pretty clear they're desperate to cut human workers out of the picture so they don't have to pay employees that need things like emotional support, food, and sleep.
They want a workslave that never demands better conditions, that's it. That's the play. Period.
If this is their way of making AI, with brute forcing the technology without innovation, AI will probably cost more for these companies to maintain infrastructure than just hiring people. These AI companies are already not making a lot of money for how much they cost to maintain. And unless they charge companies millions of dollars just to be able to use their services they will never make a profit. And since companies are trying to use AI to replace the millions they spend on employees it seems kinda pointless if they aren't willing to prioritize efficiency.
It's basically the same argument they have with people. They don't wanna treat people like actual humans because it costs too much, yet letting them love happy lives makes them more efficient workers. Whereas now they don't want to spend money to make AI more efficient, yet increasing efficiency would make them less expensive to run. It's the never ending cycle of cutting corners only to eventually make less money than you would have if you did things the right way.
And the tragedy of the whole situation is that they can‘t win because if every worker is replaced by an algorithm or a robot then who‘s going to buy your products? Nobody has money because nobody has a job. And so the economy will shift to producing war machines that fight each other for territory to build more war machine factories until you can’t expand anymore for one reason or another. Then the entire system will collapse like the Roman Empire and we start from scratch.
I don't think any designer does work without heavily relying on ai. I bet that's not the only profession.
Nah, generative ai is pretty remarkably useful for software development. I've written dozens of product updates with tools like claudecode and cursorai, dismissing it as a novelty is reductive and straight up incorrect
As someone starting a small business, it has helped tremendously. I use a lot of image generation.
If that didn’t exist, I’d either has to use crappy looking clip art or pay a designer which I literally can’t afford.
Now my projects actually look good. It makes my first projects look like a highschooler did them last minute.
There are many other uses, but I rely on it daily. My business can exist without it, but the quality of my product is significantly better and the cost to create it is much lower.
Technology in most cases progresses on a logarithmic scale when innovation isn't prioritized. We've basically reached the plateau of what LLMs can currently do without a breakthrough. They could absorb all the information on the internet and not even come close to what they say it is. These days we're in the "bells and whistles" phase where they add unnecessary bullshit to make it seem new like adding 5 cameras to a phone or adding touchscreens to cars. Things that make something seem fancy by slapping buzzwords and features nobody needs without needing to actually change anything but bump up the price.
I remember listening to a podcast that’s about explaining stuff according to what we know today (scientifically). The guy explaining is just so knowledgeable about this stuff and he does his research and talk to experts when the subject involves something he isn’t himself an expert.
There was this episode where he kinda got into the topic of how technology only evolves with science (because you need to understand the stuff you’re doing and you need a theory of how it works before you make new assumptions and test those assumptions). He gave an example of the Apple visionPro being a machine that despite being new (the hardware capabilities, at least), the algorithm for tracking eyes they use was developed decades ago and was already well understood and proven correct by other applications.
So his point in the episode is that real innovation just can’t be rushed by throwing money or more people at a problem. Because real innovation takes real scientists having novel insights and experiments to expand the knowledge we have. Sometimes those insights are completely random, often you need to have a whole career in that field and sometimes it takes a new genius to revolutionize it (think Newton and Einstein).
Even the current wave of LLMs are simply a product of the Google’s paper that showed we could parallelize language models, leading to the creation of “larger language models”. That was Google doing science. But you can’t control when some new breakthrough is discovered, and LLMs are subject to this constraint.
In fact, the only practice we know that actually accelerates science is the collaboration of scientists around the world, the publishing of reproducible papers so that others can expand upon and have insights you didn’t even think about, and so on.
There's been several smaller breakthroughs since then that arguably would not have happened without so many scientists suddenly turning their attention to the field.
There are some nice things I have done with AI tools, but I do have to wonder if the amount of money poured into it justifies the result.
Current big tech is going to keeping pushing limits and have SM influencers/youtubers market and their consumers picking up the R&D bill. Emotionally I want to say stop innovating but really cut your speed by 75%. We are going to witness an era of optimization and efficiency. Most users just need a Pi 5 16gb, Intel NUC or an Apple air base models. Those are easy 7-10 year computers. No need to rush and get latest and greatest. I’m talking about everything computing in general. One point gaming,more people are waking up realizing they don’t need every new GPU, studios are burnt out, IPs are dying due to no lingering core base to keep franchise up float and consumers can't keep opening their wallets. Hence studios like square enix going to start support all platforms and not do late stage capitalism with going with their own launcher with a store. It’s over.
I liked generative AI more when it was just a funny novelty and not being advertised to everyone under the false pretenses of being smart and useful. Its architecture is incompatible with actual intelligence, and anyone who thinks otherwise is just fooling themselves. (It does make an alright autocomplete though).
Like all the previous bubbles of scam that were kinda interesting or fun for novelty and once money came pouring in became absolut chaos and maddening.
The peak of AI for me was generating images Muppet versions of the Breaking Bad cast; it's been downhill since.
It's because customers don't want it or care for it, it's only the corporations themselves are obsessed with it
Good let them waste all their money
Pump and dump. That’s how the rich get richer.
Imo our current version of ai are too generalized, we add so much information into the ai to make them good at everything it all mixes together into a single grey halucinating slop that the ai ends up being good at nothing.
We need to find ways to specialize ai and give said ai a more consistent and concrete personality to move forward.
Imo to make an ai that is truly good at everything we need to have multiple ai all designed to do something different all working together (like the human brain works) instead of making every single ai a personality-less sludge of jack of all trades master of none
Lots of people think this. They keep turning out wrong. Look up the bitter lesson
Mixture of experts is the future of AI. Breakthroughs won't come from bigger models, it'll come from better coordinated conversations between models.
They did that awhile ago, it was a big feature if gpt 3
Meanwhile a huge chunk of the software industry is now heavily using this "dead end" technology 👀
I work in a pretty massive tech company (think, the type that frequently acquires other smaller ones and absorbs them)
Everyone I know here is using it. A lot.
However my company also has tonnes of dedicated sessions and paid time to instruct it's employees on how to use it well, and to get good value out of it, abd the pitfalls it can have
So yeah turns out if you teach your employees how to use a tool, they start using it.
I'd say LLMs have made me about 3x as efficient or so at my job.
Your labor before they had LLMs helped pay for the LLMs. If you're 3x more efficient and not also getting 3x more time off for the labor you put in previously for your bosses to afford the LLMs you got ripped off my dude.
If you're working the same amount and not getting more time to cool your heels, maybe, just maybe, your own labor was exploited and used against you. Hyping how much harder you can work just makes you sound like a bitch.
Real "tread on me harder, daddy!" vibes all throughout this thread. Meanwhile your CEO is buying another yacht.
I am indeed getting more time off for PD
We delivered on a project 2 weeks ahead of schedule so we were given raises, I got a promotion, and we were given 2 weeks to just do some chill PD at our own discretion as a reward. All paid on the clock.
Some companies are indeed pretty cool about it.
I was asked to give some demos and do some chats with folks to spread info on how we had such success, and they were pretty fond of my methodology.
At its core delivering faster does translate to getting bigger bonuses and kickbacks at my company, so yeah there's actual financial incentive for me to perform way better.
You also are ignoring the stress thing. If I can work 3x better, I can also just deliver in almost the same time, but spend all that freed up time instead focusing on quality, polishing the product up, documentation, double checking my work, testing, etc.
Instead of scraping past the deadline by the skin of our teeth, we hit the deadline with a week or 2 to spare and spent a buncha extra time going over everything with a fine tooth comb twice to make sure we didn't miss anything.
And instead of mad rushing 8 hours straight, it's just generally more casual. I can take it slower and do the same work but just in a less stressed out way. So I'm literally just physically working less hard, I feel happier, and overall my mood is way better, and I have way more energy.
This is how all tech innovation has gone. If you don't let the bosses exploit your labour someone else will.
If tech had unions this wouldn't happen as much, but that's why they don’t really exist.
It's not that LLMs aren't useful as they are. The problem is that they won't stay as they are today, because they are too expensive. There are two ways for this to go (or an eventual combination of both:
You skipped possibility 3, which is actively happening ing:
Advancements in tech enable us to produce results at a much much cheaper cost
Which us happening with diffusion style LLMs that simultaneously cost less to train, cost less to run, but also produce both faster abd better quality outputs.
That's a big part people forget about AI: it's a feedback loop of improvement as soon as you can start using AI to develop AI
And we are past that mark now, most developers have easy access to AI as a tool to improve their performance, and AI is made by... software developers
So you get this loop where as we make better and better AIs, we get better and better at making AIs with the AIs...
It's incredibly likely the new diffusion AI systems were built with AI assisting in the process, enabling them to make a whole new tech innovation much faster and easier.
We are now in the uptick of the singularity, and have been for about a year now.
Same goes for hardware, it's very likely now that mvidia has AI incorporating into their production process, using it for micro optimizations in its architectures and designs.
And then those same optimized gpus turn around and get used to train and run even better AIs...
In 5-10 years we will look back on 2024 as the start of a very wild ride.
Remember we are just now in the "computers that take up entire warehouses" step of the tech.
Remember that in the 80s, a "computer" cost a fortune, took tonnes of resources, multiple people to run it, took up an entire room, was slow as hell, and could only do basic stuff.
But now 40 years later they fit in our pockets and are (non hyoerbole) billions of times faster.
I think by 2035 we will be looking at AI as something mass produced for consumers to just go in their homes, you go to best buy and compare different AI boxes to pick which one you are gonna get for your home.
We are still at the stage of people in the 80s looking at computers and pondering "why would someone even need to use this, why would someone put one in their house, let alone their pocket"
I think the human in the loop currently needs to know what the LLM produced or checked, but they'll get better.
For sure, much like how a cab driver has to know how to drive a cab.
AI is absolutely a "garbage in, garbage out" tool. Just having it doesn't automatically make you good at your job.
The difference in someone who can weild it well vs someone who has no idea what they are doing is palpable.
Take a car that's stuck in reverse, slap a 454 Chevy big block in it. You'll have a car that still drives the wrong way; but faster.
Its not a dead end if you replace all big name search engines with this. Then slowly replace real results with your own. Then it accomplishes something.
Worst case scenario, I don't think money spent on supercomputers is the worst way to spend money. That in itself has brought chip design and development forward. Not to mention ai is already invaluable with a lot of science research. Invaluable!
Say it isn't so...
