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The rapid spread of artificial intelligence has people wondering: who’s most likely to embrace AI in their daily lives? Many assume it’s the tech-savvy – those who understand how AI works – who are most eager to adopt it.
Surprisingly, our new research (published in the Journal of Marketing) finds the opposite. People with less knowledge about AI are actually more open to using the technology. We call this difference in adoption propensity the “lower literacy-higher receptivity” link.
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Same is true bout hotdogs.
I specifically go out of my way to eat more hotdogs knowing they are 60% pig anus.
i think we give silicon valley too much linguistic power. there should really be more pushback on them rebranding LLMs as AI. it’s just a bunch of marketing nonsense that we’re letting them get away with.
(i know that LLMs are studied in the field of computer science that’s known as artificial intelligence, but i really don’t think that subtlety is properly communicated to the general public.)
I actually think in this case it’s the opposite-- your expectations of the term “AI” aren’t accurate to the actual research and industry usage. Now, if we want to talk about what people have been trying to pass off as “AGI”…
here should really be more pushback on them rebranding LLMs as AI.
Those would be AI though wouldn’t they?
The pushback I would like to see is the rush of companies to rebrand ordinary computer programs as “AI”.
People susceptible to marketing gimmicks more likely to want marketing gimmick.
I’m tech savvy and I use AI daily.
Probably not the AI you think of. As it’s not LLM or image generation.
But I have a security system self hosted using frigate, which uses AI models for image recognition.
So you’re tech savvy and you use AI as it should be - like a tool. Not a magic genie that will spit out code for you.
As a djinn, I don’t appreciate this anti-genie rhetoric.
Even using LLMs isn’t an issue, it’s just another tool. I’ve been messing around with local stuff and while you certainly have to use it knowing it’s limitations it can help for certain things, even if just helping parse data or rephrasing things.
The issue with neural nets is that while it theoretically can do “anything”, it can’t actually do everything.
And it’s the same with a lot of tools like this. People not understanding the limitations or flaws and corporations wanting to use it to replace workers.
There’s also the tech bros who feel that creative works can be generated completely by AI because like AI they don’t understand art or storytelling.
But we also have others who don’t understand what AI is and how broad it is, thinking it’s only LLMs and other neural nets that are just used to produce garbage.
Image recognition has gotten crazy good
I am a system admin and one of our appliances is a HPE Alletra. The AI in it is awesome and it never tries to interact with me. This is what I want. Just do your fucking job AI, I don’t want you to pretend to be a person.
They will come for you first /s
“Surprisingly”? This should be a surprise to no one who is paying any kind of attention to any online communities where techy people post.
Hey, buy my new CoinCoin! No, don’t research what it is, just buy it!
How exactly is this a surprise to anyone when the same applied to crypto and NFTs already? AI and blockchain technologies are useful to experts in tiny niches so far but that’s not the usual tech savvy user. For the end user it’s just a toy with little use cases.
AI is much more broadly applicable than Blockchain could ever be, although somehow it’s still being pushed more than it should be.
At the state of AI today, it helps noobs to get to average level but not help average to get a pro
The real question in my opinion is how does a pro truly benefit from it other than being a different type of a search engine
Yea, if you are a pro in something it most of the time only tells you what you already know (I sometimes use it as a sort of sanity check, by writing prompts that I think I know the output that comes)
I only found it useful doing trivial chores such as converting between data structures, maybe create a test for a function, parsing and some regex. Anything deeper than that was full of errors or the it offered was suboptimal at best. It also fails a lot of times in fetching the relevant docs/sources for the discussion. I gave up trying after so many times it basically told me " go search for yourself"
I often use it as my Python Slave because I am lazy
Like i write in bad fast human Language what my Script needs to do and then iterate from there giving it errors/ bug reports back (and fix some stuff that am I not too lazy for myself)
Scrripts that I needed were in complexity like, API calls, serial communication or converting PO to CSV and back (pls don’t ask 😅 it is for Work and I can not tell more)
But I guess, that because my skill is not too high, I‘m sure, if I was more skilled, I might be faster just writing it directly as code 💁🏻
But for code that needs to be built (like C), I mostly use it to make it explain me what existing code does, if I am not 100% sure after a short read. Have tried some generated code there as well, but then I get nothing but build errors 😆 at least, it, most of the time, can tell what the build error is trying to say.
Ah, and currently, I use my free chatGPT to make it teach me how to make music using only open source tools 😄
I very much agree with your conclusions and general approach.
LLMs are great for certain tasks that are programming related and it does it very well. I, too, often find myself needing scripts that as long as they did what they were suppose to, I really didn’t care how.
Another thing I’ve noticed(which is probably related to amounts of training data) is that it can help better with simple Python tasks as opposed to how it handles simple rust tasks.
But you mentioned one of my main issues with. Ice been programming for 15 years or so, and still learning. All the available llms did crucial errors about fundamental tabd complex topics and got the answer so very wrong but also sounding very convincing. Couple it with lack of proper linking to the sources of the response, you might see why having it explain code might cause your learn wrongly. Although it is also possible to say this about randoms internet tutorials. I always try to remind myself that it’s a tool that produces output that always needs to be verified.
I often make in a new chat with a prompt including assumptions based on the info from output of previous chat. Most of the time, it then makes a good job factchecking itself and for example tells many things not matching with what it told in previous chats. Then you know that it has not enough training data in that regard and failed to get relevant infos from it’s web search.
More than once above happened to me on copilot (from enterprise ms365) and then chatGPT limited free promts saved me 😂
I think this is true for a lot of things. iPhones, Nike, Spam
… Trump.
The more I’ve learned about technology, the more hardline I’ve become against having it in my life.
The world is not a blank slate to paint on. Every new thing that you add to your life takes away something which used to be there in previous generations, and the consequences of such can be far reaching and unpredictable. Society as it was, was not built overnight through deliberate intention, but was hard won by millennia of blood, sweat and tears. Changing everything now on the whims of fully grown toddlers who are so wealthy that they’ve never even been aware of the existence of the real world is the peak of insanity.
Neither the position to keep all the old solutions because they are old nor to adopt all the new solutions because they are new is sensible.
Some old solutions worked in the past and don’t work anymore because the actual world around us changed (the bits outside our control, e.g. some resources might be more sparse but were more plentiful in the past, human populations are larger, the world is more interconnected,…).
Some old solutions appeared to work in the past because we didn’t have the knowledge about their flaws yet but now that we do we need new ones.
Some new solutions are genuine improvements, others are merely sold by marketing and hype.
Some new solutions have studies, data or even logic and math backing them up while others are adopted on a whim or even contrary to evidence or logic.
We can not escape the fact that the world is complex and requires evaluation on a case by case basis and simplistic positions like “keep everything old” or “replace everything old” do not work.
Neither the position to keep all the old solutions because they are old nor to adopt all the new solutions because they are new is sensible.
That’s what really bothers me about it. I actually got an education in STEM and was really hyped to contribute to building new technologies, until I came to understand that the people leading the charge appear to be hardliners driving as forcefully as they can to implement a completely artificial world right here and now.
The more I’ve learned about technology, the more hardline I’ve become against having it in my life.
Eventually you’ll decide pottery, clothing, and agriculture need to go
They’re already attacking agriculture for the existential threat of cow farts.
Actually, cows emit more methane from burping
« Ignorance is bliss »
- Cypher
It really must be…
What form of AI are we talking about? Because most of them exposed to the people are glorified toys with shady business models. While tools like AlphaFold are pretty useful.
Especially on Lemmy. Every misspelling is “AI” to some of these anti-AI whackos. It’s like they’ve never seen shit webpages before. They don’t know that AI spans thousands of different task types, and generalized AI is nowhere near being accomplished.
Those that really understand what “AI” consists of, understand it’s got weaknesses and strengths. And that those strengths can be used for both good things, and bad things.
I’m just annoyed that the term AI has been co-opted now to refer to pretty much any form of machine learning. Stuff gets called AI today that wouldn’t have been considered AI even 10 years ago. I think that’s part of what’s driving peoples ridiculous expectations because they hear AI and they expect actual AI not a glorified smart fill.
Or AGI, meaning LLM that produces x amount of profit, according to openAI and Microsoft 🤣
Artificial intelligence = machine learning = statistics = just math
Someone should do a Scooby doo meme with the taking the mask off frame multiple times in a row
“Just” math?! Math is everything
Math doesn’t exist its imaginary. Its an impossible ideal that just so happens to be useful at predicting our universe.
Speaking the truth
I guess, you are not entirely wrong:
What you’re saying expressly isn’t true. Academically, deep learning is considered a subset of machine learning is considered a subset of artificial intelligence.
- Deep learning is machine learning that makes use of deep neural networks.
- Machine learning is artificial intelligence which can perform tasks without explicit instructions by learning from a dataset and generalizing to other data.
- Artificial intelligence is simply trying to make a computer display some sort of intelligence that’s seen as human-like. For example, a perceptron is artificial intelligence because how could a computer possibly see like a human? Chess bots are artificial intelligence because it was thought that chess represented some sort of higher intelligence unique to humans. NPC actions in video games can be artificial intelligence because you’re simulating what another human might do.
Would you like the textbooks from 10 years ago on this exact subject that I’m referencing? The term AI hasn’t been co-opted; you might’ve simply been thinking of general artificial intelligence, because “pretty much any form of machine learning” has been called AI since the dawn of machine learning – because it is.
While your distinctions are correct in the academic way of referring to things, you are not considering the marketing way of referring to things. Behold, the AI powered rice cooker, powered by a magnet and heat, like every other rice cooker ever (because it works really well)
https://www.youtube.com/watch?v=F_HOrMmWoMA
Marketing has decided that anything that does anything is “AI” now. Which is why people are insanely disenchanted with it.
I have a washer-dryer with an “AI mode” lol.
That toaster is what AI is. If it’s machine learning, it’s AI. If I make a toilet that uses a shitty-ass single-layer perceptron to decide when to flush, that’s an AI-powered toilet even if it’s a worthless piece of crap. You can be disenchanted with it as a gimmick all you want (I am too), but it falls under AI the same way it has since the 1950s. The marketing way of referring to things you just showed me entirely comports with the academic one provided what the label says is true.
You are technically correct and yet you are missing the original point that people expect the super-intelligent AGI of science fiction when they hear the term, no matter how much all those lesser forms are AI too by the definition of the scientific field.
Sounds like something an AI would say.
/S
If all these LLMs weren’t trained on bitch-speak; yeah. I know there are LLMs out there that aren’t kneecapped in this way, but they’re often of much lower quality.
