That's because they want to use AI in a server scenario where clients login. That translated to American English and spoken with honesty means that they are spying on you. Anything you do on your computer is subject to automatic spying. Like you could be totally under the radar, but as soon as you say the magic words together bam!...I'd love a sling thong for my wife...bam! Here's 20 ads, just click to purchase since they already stole your wife's boob size and body measurements and preferred lingerie styles. And if you're on McMaster... Hmm I need a 1/2 pipe and a cap...Better get two caps in case you cross thread on.....ding dong! FBI! We know you're in there! Come out with your hands up!
this post was submitted on 26 Feb 2025
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R&D is always a money sink
It isn't R&D anymore if you're actively marketing it.
Uh... Used to be, and should be. But the entire industry has embraced treating production as test now. We sell alpha release games as mainstream releases. Microsoft fired QC long ago. They push out world breaking updates every other month.
And people have forked over their money with smiles.
Microsoft fired QC long ago.
I can't wait until my cousin learns about this, he'll be so surprised.
I'd tell him but he's at work. At Microsoft, in quality control.
Make sure to also tell him he's doing a shit job!
He's probably been fired long ago, but due to non-existant QC, he was never notified.
Especially when the product is garbage lmao
I've been working on an internal project for my job - a quarterly report on the most bleeding edge use cases of AI, and the stuff achieved is genuinely really impressive.
So why is the AI at the top end amazing yet everything we use is a piece of literal shit?
The answer is the chatbot. If you have the technical nous to program machine learning tools it can accomplish truly stunning processes at speeds not seen before.
If you don't know how to do - for eg - a Fourier transform - you lack the skills to use the tools effectively. That's no one's fault, not everyone needs that knowledge, but it does explain the gap between promise and delivery. It can only help you do what you already know how to do faster.
Same for coding, if you understand what your code does, it's a helpful tool for unsticking part of a problem, it can't write the whole thing from scratch
So why is the AI at the top end amazing yet everything we use is a piece of literal shit?
Just that you call an LLM "AI" shows how unqualified you are to comment on the "successes".
Not this again... LLM is a subset of ML which is a subset of AI.
AI is very very broad and all of ML fits into it.
A Large Language Model is not a Machine Learning program.
An LLM is a program that translates human speech into sentiment instead of trying to acheive literal translations. It's a layer that sits on other tech to make it easier for a program to talk with a person. It is not intelligent, an LLM does not learn.
You really don't know what you are talking about. A perfect example of how obfuscating tech to make it sound cool invites any random person to have an opinion on "AI"
When people say AI is not real or intelligent they are speaking from a computer scientist perspective instead of trying to make sense of something they don't understand from scratch.
For coding it's also useful for doing the menial grunt work that's easy but just takes time.
You're not going to replace a senior dev with it, of course, but it's a great tool.
My previous employer was using AI for intelligent document processing, and the results were absolutely amazing. They did sink a few million dollars into getting the LLM fine tuned properly, though.
YES
YES
FUCKING YES! THIS IS A WIN!
Hopefully they curtail their investments and stop wasting so much fucking power.
I think the best way I've heard it put is "if we absolutely have to burn down a forest, I want warp drive out of it. Not a crappy python app"
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.
Even your manual search results may have you find incorrect sources, selection bias for what you want to see, heck even AI generated slop, so the AI generated results will just be another layer on top. Link aggregating search engines are slowly becoming useless at this rate.
While that’s true, the thing that stuck out to me is not even that the AI was mislead by itself finding AI slop, or even somebody falsely asserting something. I googled something with a particular yea or no answer. “Does X technology use Y protocol”. The AI came back with “Yes it does, and here’s how it uses it”, and upon visiting the reference page for that answer, it was documentation for that technology where it explained very clearly that x technology does NOT use Y protocol, and then went into detail on why it doesn’t. So even when everything lines up and the answer is clear and unambiguous, the AI can give you an entirely fabricated answer.
AI is burning a shit ton of energy and researchers’ time though!
For a lot of years, computers added no measurable productivity improvements. They sure revolutionized the way things work in all segments of society for something that doesn’t increase productivity.
AI is an inflating bubble: excessive spending, unclear use case. But it won’t take long for the pop, clearing out the failures and making successful use cases clearer, the winning approaches to emerge. This is basically the definition of capitalism
What time span are you referring to when you say "for a lot of years"?
Vague memories of many articles over much of my adult life decrying the costs of whatever the current trend with computers is being higher than the benefits.
And I believe it, it’s technically true. There seems to be a pattern of bubbles where everyone jumps on the new hot thing, spend way too much money on it. It’s counterproductive, right up until the bubble pops, leaving the transformative successes.
Or I believe it was a long term thing with electronic forms and printers. As long as you were just adding steps to existing business processes, you don’t see productivity gains. It took many years for businesses to reinvent the way they worked to really see the productivity gains
JC Denton said it best in 2001:
I'm convinced the devs actually time traveled back from like 2035
Like all good sci-fi, they just took what was already happening to oppressed people and made it about white/American people, while adding a little misdirection by extrapolation from existing tech research. Only took about 20 years for Foucault's boomerang to fully swing back around, and keep in mind that all the basic ideas behind LLMs had been worked out by the 80s, we just needed 40 more years of Moore's law to make computation fast enough and data sets large enough.
Unlikely, all time travel technology will have been destroyed in the war, before 2035
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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.... 😂
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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.
I’ve basically given up hope of the bubble ever bursting, as the market lives in La La Land, where no amount of bad decision-making seems to make a dent in the momentum of “line must go up”.
Would it be cool for negative feedback to step in and correct the death spiral? Absolutely. But, I advise folks to not start holding their breath so soon…
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.
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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.
Because there’s already been multiple AI bubbles (eg, ELIZA - I had a lot of conversations with FREUD running on an Apple IIe). It’s also been falsely presented as basically “AGI.”
AI models trained to help doctors recognize cancer cells - great, awesome.
AI models used as the default research tool for every subject - very very very bad. It’s also so forced - and because it’s forced, I routinely see that it has generated absolute, misleading, horseshit in response to my research queries. But your average Joe will take that on faith, your high schooler will grow up thinking that Columbus discovered Colombia or something.
I just can't see AI tools like ChatGPT ever being profitable. It's a neat little thing that has flaws but generally works well, but I'm just putzing around in the free version. There's no dollar amount that could be ascribed to the service that it provides that I would be willing to pay, and I think OpenAI has their sights set way too high with the talk of $200/month subscriptions for their top of the line product.
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