tek
AI is overhyped and unreliable -Goldman Sachs

https://www.404media.co/goldman-sachs-ai-is-overhyped-wildly-expensive-and-unreliable/

"Despite its expensive price tag, the technology is nowhere near where it needs to be in order to be useful for even such basic tasks"

@[email protected]
Goldman Sachs: AI Is Overhyped, Wildly Expensive, and Unreliable

One of the world's largest investment banks wonders if generative AI will be worth the huge investment and hype: "will this large spend ever pay off?"

404 Media
Jul 14, 2024 at 12:29pmWeb
Show threadAutonomous UserJul 14, 2024
I don’t care what they think.
Show threadmindlightJul 14, 2024
Goldman Sachs is overhyped and unreliable.
Show threadOgmiosJul 14, 2024
I do find the similarities between the function of AI and the function of a corporation to be quite interesting…
Show threadparaphrandJul 14, 2024
It’s all the bullshitting going on in both.
Show threadgravitas_deficiencyJul 16, 2024
Be that as it may, I don’t think they’re incorrect in their statement here.
Show threaddoeknius_gloekJul 14, 2024
Never thought I’d agree with Goldman Sachs.
Show threadnyanJul 14, 2024
Even a stopped clock is right twice a day. Provided it’s an analogue clock.
Show threadnondescripthandleJul 14, 2024
We know, you guys tried using the buzz around it to push down wages. You either got what you wanted and flipped tune, or realized you feel for another tech bro middle-manning unsolicited solutions into already working systems.
Show threadhendrikJul 14, 2024
Came here to say, we read last week that the industry spent $600bn on GPUs, they need that investment returned and we're getting AI whether it's useful or not... But that's also written in the article.
Show threadthemurphyJul 14, 2024
There’s a company that didn’t invest in AI in time. Sounds just like Republican Elon Musk when he cried over AI being years ahead of his own.
Show threadLaserJul 15, 2024

Even a broken clock is right twice a day.

I don’t want to imply GS did a responsible thing, but… if they assessed the situation two years ago and decided RoI is unlikely and as such didn’t invest - wouldn’t their current stance actually be reasonable?

Show threadsimpleJul 14, 2024

AI was a promise more than anything. When ChatGPT came out, all the AI companies and startups promised exponential improvements that will chaaangeee the woooooorrlllddd

Two years later it’s becoming insanely clear they hit a wall and there isn’t going to be much change unless someone makes a miraculous discovery. All of that money was dumped in to just make bigger models that are 0.1% better than the last one. I’m honestly surprised the bubble hasn’t popped yet, it’s obvious we’re going nowhere with this.

Show threadbluGillJul 14, 2024

@simple

@technology @tek

ai has been doing that trick since the 1950s. There have been a lot of use coming out of ai, but it has never been called ai once successful and never lived up to the early hype. some in the know about all those previous ones were surprised by the hype and not surprised about where it has gone, while others pushed the hype.

The details have changed but nothing else.

Technology - kbin.run

This is a [most excellent](https://media.giphy.com/media/v1.Y2lkPTc5MGI3NjExN3N0NmhuODNib3d3Nzg0OHU2bTFqMXAzNW42Y2JsOTVmenNsNG8ycSZlcD12MV9pbnRlcm5hbF9naWZfYnlfaWQmY3Q9Zw/l46CDHTqbmnGZyxKo/giphy.gif) place for technology news and articles....

Show threadbionicjoeyJul 14, 2024
Yeah the only innovation here is that OpenAI had the balls to use the entire internet as a training set. The underlying algorithms aren’t really new, and the limitations have been understood by data scientists, computer scientists, and mathematicians for a long time.
Show threadFrozengyroJul 14, 2024
So now it just has to use every conversation that happens as a data set. They could use microphones from all over the world to listen and learn and understand better…
Show threadrottingleafJul 15, 2024

LISP machines were cool. They can bring back that kind of “AI” right now, I want to have one.

I mean, how cool can it be, having hardware acceleration of LISP-typical operations, and a whole LISP-built operating system.

Maybe resurrecting Genera is too much, but we can do with porting Emacs.

Show threadrottingleafJul 15, 2024

(Repeating myself due to being banned from my previous instance for offering to solve a problem with nukes)

Bring back Lisp machines. I like what was called AI when they were being made.

Show threadwhyNotSquirrelJul 14, 2024
I don’t think they were really trying, it was just an easy way to get funds no?
Show threadbambooJul 14, 2024
There are millions of people devoting huge amounts of time and energy into improving AI capabilities, publishing paper after paper finding new ways to improve models, training, etc. Perhaps some companies are using AI hype to get free money but that doesn’t discredit the hard work of others.
Show threadhenrikxJul 15, 2024
Can’t believe you get downvoted for saying that. No worries though as they will all be proven wrong eventually.
Show threadraspberriesareyummyJul 15, 2024

There are millions of people devoting huge amounts of time and energy into improving AI capabilities,

millions of students who bought into the marketing bullshit, you mean.

Show threadhenrikxJul 14, 2024
You should all see the story about the invention blue LEDs. No one believed that it could work except some japanese guy (Shuji Nakamura) who kept working on it despite his company telling him to stop working on it. No one believed it could ever be solved despite being so close.
Show threadzbyte64Jul 14, 2024
I mean if you ignore all the papers that point out how dubious the gen AI benchmarks are, then it is very impressive.
Show threadcley_fayeJul 14, 2024

No one believed that it could work except some japanese guy

There is a difference in not knowing how to do a thing and someone coming out doing the thing, and knowing how something works, knowing it’s by design limitations, and still hoping it may work out.

Show threadraspberriesareyummyJul 15, 2024
mwahahah. The people who are working on LLMs right now are the dumbasses and MBAs of the industry. If we ever get anything like an artificial general AI, it will come from a team of serious researchers / engineers who don’t give a shit about marketing.
Show threadEvotechJul 14, 2024
Finally, the suits are catching up
Show threadMyOpinionJul 14, 2024
The final thought in the article was perfect. What is this all for? Nothing it seems in the end.
Show threadzbyte64Jul 14, 2024
WDYM? The big corporations get a free pass to ignore their climate pledges and do the exact opposite.
Show threadmrvictory1Jul 14, 2024
In 2 interviews, the interviewees claim that the investors may lose faith in return of investment if “the killer application of AI” is not available in 18 months. In other words, if the AI is a bubble, it will burst in only 18 months.
Show threadAlphane MoonJul 14, 2024
That seems like a fair assumption. I would argue we are at the peak of the bubble and only recently we’ve seen the suits (Goldman Sachs and more broadly analysts at banks) start asking questions about ROI and real use cases.
Show threadGreyBeardJul 14, 2024
Financially? Yeah, AI is a bubble for sure. Gobs of money are being poured in with few results to show for it. That bubble will burst. But just like the dotcom bubble, that doesn’t mean the technology is useless or won’t change the world, just not instantly over night with a single investment, which is what the investment groups expect.
Show threadwewbullJul 14, 2024

This technology requires finance. You can’t train a model without millions of dollars.

If the money goes the technology is dead until the cost of the training machines comes down a few orders of magnitude.

Show threadbambooJul 14, 2024
At least in the US, the research is fairly isolated from capital markets. The military pours huge amounts of money into research on new tech like this, often over ambitiously and with no real expectation of short term returns. Even if there is a financial bubble burst that shuts down a lot of the commercial operations, universities and military contractors will continue working and publishing papers improving the state of the art until industry decides it’s time to try commercializing it again. It’s the basic pattern that has brought us most of the major tech innovations in the US.
Show threadlanolinoilJul 14, 2024
Hey! This god damned steam engine keeps using up all our fucking water and coal. This shit is so inefficient and overhyped
Show threadSlopppyEngineerJul 14, 2024

It’s like how steam powered cars were developed, but by the time they engineered out all the disadvantages like start to bring the car up to temperature half an hour before driving, the gasoline powered car was there leaving the steam car is the dust.

Not to mention the experiments with steam powered aircraft.

Show threadlanolinoilJul 15, 2024
yeah might as well wait for LLLLLMs
Show threadSlopppyEngineerJul 15, 2024

Marketing will give it a better name.

Did you know that Boeing first named their passenger jet the 700 series. but marketing found that 707 sounded much better. That’s why we now have the famous 747 and so on.

Show threadlanolinoilJul 17, 2024
surprised it didn’t end up in a razor blade race where you fly the Airbus 900000000000009
Show threadbambooJul 14, 2024
Remember that time the dot com bubble burst and that was the end of the internet commerce? Crazy people thought they could buy and sell goods and services over the internet. Glad we live in saner times now.
Show threadAlpaguJul 14, 2024
This is a start. It will be better.
Show threadgedaliyahJul 14, 2024

I remember saying a year ago when everybody was talking about the AI revolution: The AI revolution already happened. We’ve seen what it can do, and it won’t expand much more.

Most people were shocked by that statement because it seemed like AI was just getting started. But here we are, a year later, and I still think it’s true.

Show threadSterile_TechniqueJul 14, 2024

Those people were talking about the kind of AI we see in sci-fi, not the spellchecker-on-steroids we have today. There used to be a distinction, but marketing has muddied those waters. The sci-fi variety has been rebranded “AGI” so I guess the rest of that talk would go right along with it - the ‘AGI singularity’ and such.

All still theoretically possible, but I imagine climate will take us out or we’ll find some clever new way to make ourselves extinct before real AI …or AGI… becomes a thing.

Show threadjayboneJul 14, 2024
Given AI’s energy needs, it’s already helping to take us out.
Show threadOutlierBlueJul 14, 2024

The AI revolution already happened. We’ve seen what it can do, and it won’t expand much more.

That’s like seeing a basic electronic calculator in the 60s and saying that computing won’t expand much more. Full-AI isn’t here yet, but it’s coming, and it will far exceed everything that we have right now.

Show threadturmacarJul 14, 2024

Sure.

GPT4 is not that. Neither will GPT5 be that. They are language models that marketing is calling AI. They have a very specific use case, and it’s not something that can replace any work/workers that requires any level of traceability or accountability. It’s just “the thing the machine said”.

Marketing latched onto “AI” because blockchain and cloud and algorithmic had gotten stale and media and CEOs went nuts. I Samsung is now producing an “AI” vacuum that adjusts suction between hardwood and carpet. That’s not new technology. That’s not even a new way of doing that technology. It’s just jumping on the bandwagon.

Show threadaestheleteJul 15, 2024

Marketing latched onto “AI” because blockchain and cloud and algorithmic had gotten stale and media and CEOs went nuts.

Notably, this also coincided with the first higher interest rate environment in the broader economy in over a decade.

Show threadHackyHorse3000Jul 14, 2024
That’s the thing though, that’s not comparable, and misses the point entirely. “AI” in this context and the conversations regarding it in the current day is specifically talking about LLMs. They will not improve to the point of general intelligence as that is not how they work. Hallucinations are inevitable with the current architectures and methods, and they lack a inherent understanding of concepts in general. It’s the same reason they can’t do math or logic problems that aren’t common in the training set. It’s not intelligence. Modern computers are built on the same principals and architectures as those calculators were, just iterated upon extensively. No such leap is possible using large language models. They are entirely reliant on a finite pool of data to try to mimic most effectively, they are not learning or understanding concepts the way “Full-AI” would need to to actually be reliable or able to generate new ideas.
Show threadchrash0Jul 14, 2024
it’s super weird that people think LLMs are so fundamentally different from neural networks, the underlying technology. neural network architectures are constantly improving, and LLMs are just a product of a ton of research and an emergence after the discovery of the transformer architecture. what LLMs have shown us is that we’re definitely on the right track using neural networks to solve a wide range of problems classified as “AI”
Show threadHackyHorse3000Jul 14, 2024
I think the main problem is applying LLM outside the domain of “complete this sentence”. It’s fine for what it is, and trained on huge datasets it obviously appears impressive, but it doesn’t know if it’s right or wrong, and evaluation metrics are different. In most traditional applications of neural networks, you have datasets with right and wrong answers, that’s not how these are trained, as there is no “right” answer to “tell me a joke.” So the training has to be based on what would likely fill in the blank. This could be an actual joke, a bad joke, a completely different topic, there’s no difference in the training data. The biases, incorrect answers, all the faults of this massive dataset are inherent in the model, and there’s no fixing that. They are fundamentally different in their application and evaluation (this extends to training) methods from other neural networks that are actually effective at what they do, like image processing and identification. The scope of what they’re trying to do with a finite dataset is not realistic and entirely unconstrained, as compared to more “traditional” neural networks, which are very narrow in scope exactly because of this issue.
Show threadgedaliyahJul 14, 2024

Oh, I’m not saying that there won’t one day come a better technology that can do a lot more. What I’m saying is that the present technology will never do much more than it is already doing. This is not an issue of refining the technology for more applications. It’s a matter of completely developing a new type of technology.

In areas of generative text, summarizing articles and books, as well as writing short portions of code in order to assist humans, creating simple fan art, and meaningless images like avatars, and those stock photos at the top of articles, Perhaps creating short animations, Improving pattern recognition of things like speech and facial recognition… In all of these areas, AI was very rapidly revolutionary.

Generative AI will not become capable of doing things that it’s not already doing. Most of what it’s replacing are just worse computer programs. Some new technology will undoubtedly be revolutionary in the way that computers were a completely new revolution on top of basic function calculators. People are developing quantum computers, and mapping the precise functions of brain cells. If you want, you can download a completely mapped actual nematode brain right now. You can buy brain cells online, even human brain cells, and put them into computers. Maybe they can even run Doom. I have no idea what the next computing revolution will be capable of, but this one has mostly run its course. It has given us some very incredible tools in a very narrow scope, and those tools will continue to improve incrementally, but there will be no additional revolution.

OpenWorm

An open-source project dedicated to creating a virtual C. elegans nematode in a computer. - OpenWorm

GitHub
Show threadChickenLadyLovesLifeJul 15, 2024

That’s like seeing a basic electronic calculator in the 60s and saying that computing won’t expand much more.

“Who would ever need more than 640K of RAM?” -Bill Gates

Show threadraspberriesareyummyJul 15, 2024

Full-AI isn’t here yet, but it’s coming, and it will far exceed everything that we have right now.

go back to school, hopefully your next statement won’t sound as dumb.

Show threadSeattleRainJul 14, 2024
It’ll expand but it will take 5-10 years. Just like Web 1.0 and 2.0.
Show threadcley_fayeJul 14, 2024
Not with the current tech. It can go faster, have more detailed output, maybe consume less too, but there seems to be a ceiling on what LLM and their derivative can do. There has been no improvement in that regard, and people that look into it are pretty confident that it won’t happen at this point.
Show threadSlopppyEngineerJul 15, 2024
AI development is indeed a series of S-curves and we’re currently nearing the peak of the curve. It’s going to be some time before the new S begins.
Show threadUplinkJul 15, 2024
I think it all depends on how good our tools to detect AI generated content become. If it is not distinguishable, then the internet is probably about to be flooded by AI generated content which in turn means AI is going to be trained more and more with AI content, degrading the model in the process.
Show threadLEXJul 14, 2024
Oh yeah? It’s great for porn, Goldman Sachs, you bunch of suit wearing degenerates. I bet a lot of people would argue that’s pretty freaking useful.
Show threadsuctionJul 14, 2024
NO KIDDING YOU WORLD-DESTROYING MONEYHUNGRY COCKROACHES
Show threadcoffee_with_creamJul 14, 2024
It’s weird to me that people on Lemmy are so anti ML. If you aren’t impressed, you haven’t used it enough. “Oh it’s not 100% perfect,” well yeah who cares? You should partner it with a human to supervise it anyway. 1 human can supervise many ML partners
Show threadnandeEbisuJul 15, 2024

In terms of practical commercial uses, these highly human in the loop systems are about where it is and there are practical applications and products build off of it. I think what was sold though is a much more of either a replacement of people or a significant jump in functionality.

For example, there are products that will give you an AI summary of a structured or fairly uniform document like a generic press release, but there’s not really a good replacement for something to read backgrounds on 50 different companies and figure out which one you should invest in without a human basically doing all of that work themselves anyway just to check the work of the AI. The latter is what is being sold to make the enormous cost of hosting and training AI worth it.