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”
Yeah… It’s machine learning with a hype team.
There are some great applications, but they are very narrow
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.
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.
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.
This could very well be another case of being so close to a breakthrough. Two years since GPT-3 came out is nothing. If you were paying any sort of attention you would see there are promising papers coming out almost every week.
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.
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.
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.
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.
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.
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”
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.
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. 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.
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.
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.
NO KIDDING YOU WORLD-DESTROYING MONEYHUNGRY COCKROACHES
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…
