This is a most excellent place for technology news and articles.
That’s standard for emerging technologies. They tend to be loss leaders for quite a long period in the early years.
It’s really weird that so many people gravitate to anything even remotely critical of AI, regardless of context or even accuracy. I don’t really understand the aggressive need for so many people to see it fail.
For me personally, it's because it's been so aggressively shoved in my face in every context. I never asked for it, and I can't escape it. It actively gets in my way at work (github copilot) and has already re-enabled itself at least once. I'd be much happier to just let it exist if it would do the same for me.
And crashing the markets in the process... At the same time they came out with a bunch of mambo jumbo and scifi babble about having a million qbit quantum chip.... 😂
It is fun to generate some stupid images a few times, but you can't trust that "AI" crap with anything serious.
I was just talking about this with someone the other day. While it’s truly remarkable what AI can do, its margin for error is just too big for most if not all of the use cases companies want to use it for.
For example, I use the Hoarder app which is a site bookmarking program, and when I save any given site, it feeds the text into a local Ollama model which summarizes it, conjures up some tags, and applies the tags to it. This is useful for me, and if it generates a few extra tags that aren’t useful, it doesn’t really disrupt my workflow at all. So this is a net benefit for me, but this use case will not be earning these corps any amount of profit.
On the other end, you have Googles Gemini that now gives you an AI generated answer to your queries. The point of this is to aggregate data from several sources within the search results and return it to you, saving you the time of having to look through several search results yourself. And like 90% of the time it actually does a great job. The problem with this is the goal, which is to save you from having to check individual sources, and its reliability rate. If I google 100 things and Gemini correctly answers 99 of those things accurate abut completely hallucinates the 100th, then that means that all 100 times I have to check its sources and verify that what it said was correct. Which means I’m now back to just… you know… looking through the search results one by one like I would have anyway without the AI.
So while AI is far from useless, it can’t now and never will be able to be relied on for anything important, and that’s where the money to be made is.
Well duh
Very bold move, in a tech climate in which CEOs declare generative AI to be the answer to everything, and in which shareholders expect line to go up faster…
I half expect to next read an article about his ouster.
My theory is it's only a matter of time until the firing sprees generate enough backlog of actual work that isn't being realised by the minor productivity gains from AI until the investors start asking hard questions.
Maybe this is the start of the bubble bursting.
Is he saying it's just LLMs that are generating no value?
I wish reporters could be more specific with their terminology. They just add to the confusion.
Edit: he's talking about generative AI, of which LLMs are a subset.
LLMs in non-specialized application areas basically reproduce search. In specialized fields, most do the work that automation, data analytics, pattern recognition, purpose built algorithms and brute force did before. And yet the companies charge nx the amount for what is essentially these very conventional approaches, plus statistics. Not surprising at all. Just in awe of how come the parallels to snake oil weren't immediately obvious.
I think AI is generating negative value ... the huge power usage is akin to speculative blockchain currencies. Barring some biochemistry and other very, very specialized uses it hasn't given anything other than, as you've said, plain-language search (with bonus hallucination bullshit, yay!) ... snake oil, indeed.
Its a little more complicated than that I think. LLMs and AI is not remotely the same with very different use cases.
I believe in AI for sure in some fields, but I understand the skeptics around LLMs.
But the difference AI is already doing in the medical industry and hospitals is no joke. X-ray scannings and early detection of severe illness is the one being used specifically today, and will save thounsands of lives and millions of dollars / euros.
My point is, its not that black and white.
Correction, LLMs being used to automate shit doesn't generate any value. The underlying AI technology is generating tons of value.
AlphaFold 2 has advanced biochemistry research in protein folding by multiple decades in just a couple years, taking us from 150,000 known protein structures to 200 Million in a year.
Well sure, but you're forgetting that the federal government has pulled the rug out from under health research and therefore had made it so there is no economic value in biochemistry.
Yeah tbh, AI has been an insane helpful tool in my analysis and writing. Never would I have been able to do thoroughly investigate appropriate statisticall tests on my own. After following the sources and double checking ofcourse, but still, super helpful.
Thanks. So the underlying architecture that powers LLMs has application in things besides language generation like protein folding and DNA sequencing.
Image recognition models are also useful for astronomy. The largest black hole jet was discovered recently, and it was done, in part, by using an AI model to sift through vast amounts of data.
https://www.youtube.com/watch?v=wC1lssgsEGY
This thing is so big, it travels between voids in the filaments of galactic super clusters and hits the next one over.
AI is just what we call automation until marketing figures out a new way to sell the tech. LLMs are generative AI, hardly useful or valuable, but new and shiny and has a party trick that tickles the human brain in a way that makes people give their money to others. Machine learning and other forms of AI have been around for longer and most have value generating applications but aren't as fun to demonstrate so they never got the traction LLMs have gathered.
I'm afraid you're going to have to learn about AI models besides LLMs
alphafold is not an LLM, so no, not really
You are correct that AlphaFold is not an LLM, but they are both possible because of the same breakthrough in deep learning, the transformer and so do share similar architecture components.
It's always important to double check the work of AI, but yea it excels at solving problems we've been using brute force on
