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”
If Goldman Sachs told me the sky was blue, I would go outside, check, and get an eye exam.
OK boomer
NO KIDDING YOU WORLD-DESTROYING MONEYHUNGRY COCKROACHES
I mean they aren’t wrong. From an efficiency standpoint, current AI is like using a 350hp car engine to turn a childs rock tumbler, or spin art thingy. Sure, it produces some interesting outputs, at the cost of way too much energy for what is being done. That is the current scenario of using generalized compute or even high end GPUs for AI.
Best I can tell is, the “way forward” is further development of ASICs that are specific to the model being run. This should increase efficiency, decrease the ecological impact (less electricity usage) and free up silicon and components, possibly decreasing price and increasing availablity of things like consumer graphics cards again (but I won’t hold my breath for that part).
I don’t care what they think. What have they ever done for me?
Heartbreaking: The Worst Person You Know Just Made A Great Point
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.
Yeah but it’s Goldman Sachs saying it. Presumably because they haven’t invested in AI.
Perhaps we could get a non-biased opinion and also from an actual expert rather than some finance ghoul who really doesn’t know anything?
I’d say they know a thing or two about finance… so maybe they didn’t invest because they see it as overhype?
The problem is experts in AI are biased towards AI (it pays their salaries).
Presumably because they haven’t invested in AI.
Presumably is carrying all the weight of your whole post here
Perhaps we could get a non-biased opinion and also from an actual expert rather than some finance ghoul who really doesn’t know anything?
I also hate banks, but usually those guys can sniff out market failures way ahead of the rest of us. All their bacon rides on that, after all
It’s noteworthy because it’s Goldman Sachs. Lots of money people are dumping it into AI. When a major outlet for money people starts to show skepticism, that could mean the bubble is about to pop.
You dare to challenge Goldman Sacks?
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”
I was fully on board until, like, a year ago. But the more I used it, the more obviously it came undone.
I initially felt like it could really help with programming. And it looked like it, too - when you fed it toy problems where you don’t really care about how the solution looks, as long as it’s somewhat OK. But once you start giving it constraints that stem from a real project, it just stops being useful. It ignores constraints (use this library, do not make additional queries, …), and when you point out its mistake and ask it to to better it goes “oh, sorry! Here, let me do the same thing again, with the same error!”.
If you’re working in a less common language, it even dreams up non-existing syntax.
Even the one thing it should be good at - plain old language - it sucks ass at. It’s become so easy to spot LLM garbage, just due to its style.
Worse, asking it to proofread a text for spelling and grammar mistakes, but to explicitly do not change the wording or style, there’s about a 50/50 chance it will either
- change your wording or style, or
- point out errors that are not even in the original text in the first place!
I could honestly go on and on, but what it boils down to is: it is able to string together words that make it sound like it knows what it is doing, but it is just that, a facade. And it looks like for more and more people, the spell is finally breaking.
@coffee_with_cream@sh.itjust.works @technology@LemmyWorld@mastodon.world I don’t hate it but do think it’s overhyped by wallstreet’s usual infinite growth assumption
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.
Goldman Sachs is overhyped and unreliable.
I do find the similarities between the function of AI and the function of a corporation to be quite interesting…
It’s all the bullshitting going on in both.
Never thought I’d agree with Goldman Sachs.
Even a stopped clock is right twice a day. Provided it’s an analog clock.
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 fell for another tech bro middle-manning unsolicited solutions into already working systems.
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.
@simple@lemm.ee
@technology@lemmy.world @tek@calckey.world
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.
(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.
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.
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…
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. No one believed it could ever be solved despite being so close. He solved it and the rewards were astronomical.
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.
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.
I mean if you ignore all the papers that point out how dubious the gen AI benchmarks are, then it is very impressive.
I don’t think they were really trying, it was just an easy way to get funds no?
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.
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.
Can’t believe you get downvoted for saying that. No worries though as the haters will all be proven wrong eventually.
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.
Haha, 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.
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?
