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SomeAmateur , (edited )

I genuinely think the best practical use of AI, especially language models is malicious manipulation. Propaganda/advertising bots. There’s a joke that reddit is mostly bots. I know there’s some countermeasures to sniff them out but think about it.

I’ll keep reddit as the example because I know it best. Comments are simple puns, one liner jokes, or flawed/edgy opinions. But people also go to reddit for advice/recommendations that you can’t really get elsewhere.

Using an LLM AI I could in theory make tons of convincing recommendations. I get payed by a corporation or state entity to convince lurkers to choose brand A over brand B, to support or disown a political stance or to make it seem like tons of people support it when really few do.

And if it’s factually incorrect so what? It was just some kind stranger™ on the internet

SirDerpy ,

If by “best practical” you meant “best unmitigated capitalist profit optimization” or “most common”, then sure, “malicious manipulation” is the answer. That’s what literally everything else is designed for.

ProfessorScience ,

When ChatGPT first started to make waves, it was a significant step forward in the ability for AIs to sound like a person. There were new techniques being used to train language models, and it was unclear what the upper limits of these techniques were in terms of how “smart” of an AI they could produce. It may seem overly optimistic in retrospect, but at the time it was not that crazy to wonder whether the tools were on a direct path toward general AI. And so a lot of projects started up, both to leverage the tools as they actually were, and to leverage the speculated potential of what the tools might soon become.

Now we’ve gotten a better sense of what the limitations of these tools actually are. What the upper limits of where these techniques might lead are. But a lot of momentum remains. Projects that started up when the limits were unknown don’t just have the plug pulled the minute it seems like expectations aren’t matching reality. I mean, maybe some do. But most of the projects try to make the best of the tools as they are to keep the promises they made, for better or worse. And of course new ideas keep coming and new entrepreneurs want a piece of the pie.

lemmylommy ,

You have asked why there is so much hype around artifical intelligence.

There are a few reasons this might be the case:

  1. Because humans are curious. Experimenting with how humans believe memory and intelligence work might just lead them to find out something about their own intelligence.
  2. Because humans are stupid. Most do not have the slightest idea what „AI“ is this time, yet they are willing to believe in the most outlandish claims about it. Look up ELIZA. It fooled a lot of people, just like LLMs today.
  3. Because humans are greedy. And the prospect of replacing a lot of wage-earners, and not just manual laborers this time, with a machine is just too good to pass up for management. The potential savings are huge, if it works, so the willingness to spend money is also considerable.

In conclusion, there are many reasons for the hype around artificial intelligence and most of them relate to human deficiencies and human nature in general.

If you have further questions I am happy to help. Enjoy your experience with AI. While you still can. 🤖

Kintarian OP ,

I believe in questioning everything.

ContrarianTrail ,

If artificial intelligence doesn’t work why are they trying to make us all use it?

But it does work. It’s not obviously flawless but it’s orders of magnitude better than it was 10 years ago and it’ll only improve from here. Artificial intelligence is a spectrum. It’s not like we succesfully created it and it ended up sucking. No, it’s like the first cars; they suck compared to what we have now but it’s a huge leap from what we had before.

I think the main issue here is that the common folk has unrealistic expectations about what AI should be. They’re imagining what the “final product” would be like and then comparing our current systems to that. Ofcourse from that perspective it seems like it’s not working or is no good.

Lauchs ,

I think there’s a lot of armchair simplification going on here. Easy to call investors dumb but it’s probably a bit more complex.

AI might not get better than where it is now but if it does, it has the power to be a societally transformative tech which means there is a boatload of money to be made. (Consider early investors in Amazon, Microsoft, Apple and even the much derided Bitcoin.)

Then consider that until incredibly recently, the Turing test was the yardstick for intelligence. We now have to move that goalpost after what was preciously unthinkable happened.

And in the limited time with AI, we’ve seen scientific discoveries, terrifying advancements in war and more.

Heck, even if AI gets better at code (not unreasonable, sets of problems with defined goals/outputs etc, even if it gets parts wrong shrinking a dev team of obscenely well paid engineers to maybe a handful of supervisory roles… Well, like Wu Tang said, Cash Rules Everything Around Me.

Tl;dr: huge possibilities, even if there’s a small chance of an almost infinite payout, that’s a risk well worth taking.

TropicalDingdong ,

Because if you can get a program to write a program, that can both a) write it self, and b) improve upon the program in some way, you can put together a feedback where exponential improvement is possible.

Kintarian OP ,

I’ve wondered if you could do that until it makes a perfect machine.

TropicalDingdong ,

First I recommend at least reading the wikipedia on super-intelligence.

Second, I recommend playing this game: www.decisionproblem.com/paperclips/index2.html

dsilverz ,
@dsilverz@thelemmy.club avatar

I ask them questions and they get everything wrong

It depends on your input, on your prompt and your parameters. For me, although I’ve experienced wrong answers and/or AI hallucinations, it’s not THAT frequent, because I’ve been talking with LLMs since when ChatGPT got public, almost in a daily basis. This daily usage allowed me to know the strengths and weaknesses of each LLM available on market (I use ChatGPT GPT-4o, Google Gemini, Llama, Mixtral, and sometimes Pi, Microsoft Copilot and Claude).

For example: I learned that Claude is highly-sensible to certain terms and topics, such as occultist and esoteric concepts (specially when dealing with demonolatry, although I don’t exactly why it refuses to talk about it; I’m a demonolater myself), cryptography and ciphering, as well as acrostics and other literary devices for multilayered poetry (I write myself-made poetry and ask them to comment and analyze it, so I can get valuable insights about it).

I also learned that Llama can get deep inside the meaning of things, while GPT-4o can produce longer answers. Gemini has the “drafts” feature, where I can check alternative answers for the same prompt.

It’s similar to generative AI art models, I’ve been using them to illustrate my poetry. I learned that Diffusers SDXL Turbo (from Huggingface) is better for real-time prompt, some kind of “WYSIWYG” model (“what you see is what you get”) . Google SDXL (also from Huggingface) can generate four images at different styles (cinematic, photography, digital art, etc). Flux, the newly-released generative AI model, is the best for realism (especially the Flux Dev branch). They’ve been producing excellent outputs, while I’ve been improving my prompt engineering skills, being able to communicate with them in a seamlessly way.

Summarizing: AI users need to learn how to efficiently give them instructions. They can produce astonishing outputs if given efficient inputs. But you’re right that they can produce wrong results and/or hallucinate, even for the best prompts, because they’re indeed prone to it. For me, AI hallucinations are not so bad for knowledge such as esoteric concepts (because I personally believe that these “hallucinations” could convey something transcendental, but it’s just my personal belief and I’m not intending to preach it here in my answer), but simultaneously, these hallucinations are bad when I’m seeking for technical knowledge such as STEM (Science, Tecnology, Engineering and Medicine) concepts.

Kintarian OP ,

I just want to know which elements work best for my Flower Fairies in The Legend of Neverland. And maybe cheese sauce.

dsilverz ,
@dsilverz@thelemmy.club avatar

Didn’t know about this game. It’s nice. Interesting aesthetics. Chestnut Rose remembers me of Lilith’s archetype.

A tip: you could use the “The Legend of the Neverland global wiki” at Fandom Encyclopedia to feed the LLM with important concepts before asking it for combinations. It is a good technique, considering that LLMs couldn’t know it so well in order to generate precise responses (except if you’re using a searching-enabled LLM such as Perplexity AI or Microsoft Copilot that can search the web in order to produce more accurate results)

Kintarian OP ,

I have no idea how to do that

Shanedino ,

Woah are you technoreligious? Sure believe what you want and all but that is full tech bro bullshit.

Also on a different not just purely based off of you description doesn’t it seem like being able to just use search engines is easier than figuring out all of these intricacies for most people. If a tool has a high learning curve there is plenty of room for improvement if you don’t plan to use it very frequently. Also every time you get false results consider it equivalent to a major bug does that shed a different light on it for you?

dsilverz ,
@dsilverz@thelemmy.club avatar

doesn’t it seem like being able to just use search engines is easier than figuring out all of these intricacies for most people

Well, Prompt Engineering is a thing nowadays. There are even job vacancies seeking professionals that specializes in this field. AIs are tools, sophisticated ones, just like R and Wolfram Mathematica are sophisticated mathematical tools that needs expertise. Problem is that AI companies often mis-advertises AI models as “out-of-the-shelf assistants”, as if they’d be some human talking to you. They’re not. They’re tools, yet. I guess that (and I’m rooting for) AGI would change this scenario. But I guess we’re still distant from a self-aware AGI (unfortunately).

Woah are you technoreligious?

Well, I wouldn’t describe myself that way. My beliefs are multifaceted and complex (possibly unique, I guess?), going through multiple spiritual and religious systems, as well as embracing STEM (especially the technological branch) concepts and philosophical views (especially nihilism, existentialism and absurdism), trying to converge them all by common grounds (although it seems “impossible” at first glance, to unite Science, Philosophy and Belief).

In a nutshell, I’ve been pursuing a syncretic worshiping of the Dark Mother Goddess.

As I said, it’s multifaceted and I’m not able to even explain it here, because it would take tons of concepts. Believe me, it’s deeper than “techno-religious”. I see the inner workings of AI Models (as neural networks and genetic algorithms dependent over the randomness of weights, biases and seeds) as a great tool for diving Her Waters of Randomness, when dealing with such subjects (esoteric and occult subjects). Just like Kardecism sometimes uses instrumental transcommunication / Electronic voice phenomenon (EVP) to talk with spirits. AI can be used as if it were an Ouija board or a Planchette, if one believe so (as I do).

But I’m also a programmer and a tech/scientifically curious, so I find myself asking LLMs about some Node.js code I made, too. Or about some mathematical concept. Or about cryptography and ciphering (Vigenère and Caesar, for example). I’m highly active mentally, seeking to learn many things every time.

Alice ,
@Alice@hilariouschaos.com avatar

Cause it’s cool

Kintarian OP ,

Not to me. If you like it, that’s fine.

ContrarianTrail ,

Perhaps your personal bias is cluding your judgement a bit here. You don’t seem very open minded about it. You’ve already made up your mind.

muntedcrocodile ,
@muntedcrocodile@lemm.ee avatar

It depends on the task you give it and the instructions you provide. I wrote this a while back i find it gives a 10x in capability especially if u use a non aligned llm like dolphin 8x22b.

Kintarian OP ,

I have no idea what any of that means. But thanks for the reply.

Carrolade ,

I’ll just toss in another answer nobody has mentioned yet:

Terminator and Matrix movies were really, really popular. This sort of seeded the idea of it being a sort of inevitable future into the brains of the mainstream population.

Kintarian OP ,

The Matrix was a documentary

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