Ironically, pre-LLM era photoshop may have already used AI (image-processing) techniques behind the scenes.

I know. It’s just that the phrasing is kinda weird.

The article’s title is:

Iran’s women’s team decline to sing national anthem before Asian Cup tie

The post title made it sound like they are disrespecting South Korea or something…

Super Smash Bros Ultimate. The final smashes are all the same. I miss the final smashes of Super Smash Bros Brawl.

Disclaimer: I am honestly a layman in this field. I may get a bunch of stuff wrong, but am happy to learn from experts. Feel free to point mistakes out and destroy me in the replies.

Simplifying and phrasing my understanding, an LLM works like - Given a prompt: Write a program to check if input is an odd number (converts the prompt to embedding), then the LLM plays a dice game/probability game of: given prompt, then generate a set of new tokens.

This feels like an oversimplification. Unfortunately, I can’t think of a good analogy without anthromorphosising LLMs.

IMO this anime scene works well enough as an analogy at a super high level: anime_irl

“Comprehending what other people is saying is one step” - encoder

“Thinking about how to answer is one more step” - working with the feature representation

“Putting the things that popped into my mind into words is another step” - decoder

Now my question is, how are the current LLM’s are able to parse through a bunch of search results and play the above dice game?

By current LLMs, I am going to assume that you are not referring to the raw models, but platforms like ChatGPT, Perplexity, etc with UIs for you to interact with the underlying models.

There are fundamentally two different problems here: searching the web for answers, and putting the answers into words.

Like at times it reads through say 10 URLs and generate results, how are they able to achieve this?

If I ask you: “What is the colour of fire engines?”, I imagine you would answer “Red”, sometimes “Yellow”, off the top of your head.

What if I ask you “What are the 10 longest rivers in the world”? I believe you won’t be able to give me an answer right away. What you can do is a web search, find the answer, then present the results to me. You can give it to me in 10 short bullets points, or you can come up with an essay with paragraphs describing each river.

You probably got my point by now, but to make it explicit: finding an answer and putting it into words are two different processes. They are independent of each other, so the final text output can be as long or as short as need be.

For these LLM platforms, when the model “doesn’t know” the answer, they probably have a subroutine that searches the web, then feed the answer to the underlying model. The model then packages the search results into readable form - in words instead of vectors - to you.

What’s the engineering behind generating such huge verbose of texts?

Sorry but I can’t think of a good answer to this at the moment; leaving it to others for now - unless I managed to think of something good.

Cause I always argue about the theoretical limitations of LLM, but now that these “agents” are able to manage huge verbose of text I dont seem to have a good argument. So what exactly is happening? And what is the limit of AI non theortical limit of AI?

Same for this question.

Hope the partial answer helps; tried my best to ELI5.

Just to reiterate, this is a conspiracy theory. I wouldn’t put too much weight into it.

After a quick search, the official reason is that ani.social is full of CSAM. Which is outright false.

My conspiracy theory is that those Chinese agents hate the growing soft power of Japan through anime.

I started with lemmy.world, the biggest generalist instance, for an easy starting point. I thought I would be interacting in programming and anime threads.

In the end, I end up discussing mostly weeb stuff, so ani.social looks more appropriate.

Also, I don’t know the specifics, but if ani.social triggered lemmy.ml enough for lemmy.ml to defederate from ani.social, it must be doing something right.

In my experience, the instance and community moderators of ani.social are based. I barely see any drama unlike some other instances. I’d say I chose well.

The world is ran by a small group of “elites”.

deleted by creator

see: previous discussion

“AI is whatever hasn’t been done yet.”

• Larry Tesler

💩/10 for easy teabagging.

algorithmic approaches that are only colloquially referred to as “AI”. Artificial Intelligence is still science fiction

That’s why this joke definition of AI is still the best: “AI is whatever hasn’t been done yet.”

I have forgotten all working definitions of AI that CS professors gave except for this one 🙃

As in, I agree with your point. I just want to give a shoutout to the non-ML-based AI.

Let’s not forget about traditional AI, which have served us well for so long that we stopped thinking of them as AI.

AI is a super broad field that encompasses so many tech. It is not limited to the whatever the tech CEOs are pushing.

In this comment section alone, we see a couple examples of AI used in practical ways.

On a more personal level, surely you’d have played video games before? If you had to face any monster / bot opponents / etc, those are all considered AI. Depending on the game, stages / maps / environments may be procedurally generated - using AI techniques!

There are many more examples - e.g. pathfinding in map apps, translation apps -, just that we are all so familiar with them that we stopped thinking of them as AI.

So there are plenty of evidence for AI’s usefulness.

Because AI - in a very broad sense - is useful.

forced exploitation of untold millions of artists and creative laborers, without even so much as consent, let alone compensation…

In this case, is it AI that you truly hate?

I think this comment said it best.

Earth is in space, so technically…