#chatgpt ;)

[gezin-yazar]

[kareguya]

Audrey

[animentality]

[memendoemori]

Good morning everybody

[softwaring]

this reply kills me 😭 article link

[whydidisavethistomyphone]

[thehungrycity]

[dduane]

Well, this would be interesting...

[purpleartrowboat]

ai makes everything so boring. deepfakes will never be as funny as clipping together presidential speeches. ai covers will never be as funny as imitating the character. ai art will never be as good as art drawn by humans. ai chats will never be as good as roleplaying with other people. ai writing will never be as good as real authors

[postmodernmulticoloredcloak]

anyway in case you don’t know it yet

[mostly-funnytwittertweets]

[river-taxbird]

AI hasn't improved in 18 months. It's likely that this is it. There is currently no evidence the capabilities of ChatGPT will ever improve. It's time for AI companies to put up or shut up.

I'm just re-iterating this excellent post from Ed Zitron, but it's not left my head since I read it and I want to share it. I'm also taking some talking points from Ed's other posts. So basically:

We keep hearing AI is going to get better and better, but these promises seem to be coming from a mix of companies engaging in wild speculation and lying.

Chatgpt, the industry leading large language model, has not materially improved in 18 months. For something that claims to be getting exponentially better, it sure is the same shit.

Hallucinations appear to be an inherent aspect of the technology. Since it's based on statistics and ai doesn't know anything, it can never know what is true. How could I possibly trust it to get any real work done if I can't rely on it's output? If I have to fact check everything it says I might as well do the work myself.

For "real" ai that does know what is true to exist, it would require us to discover new concepts in psychology, math, and computing, which open ai is not working on, and seemingly no other ai companies are either.

Open ai has already seemingly slurped up all the data from the open web already. Chatgpt 5 would take 5x more training data than chatgpt 4 to train. Where is this data coming from, exactly?

Since improvement appears to have ground to a halt, what if this is it? What if Chatgpt 4 is as good as LLMs can ever be? What use is it?

As Jim Covello, a leading semiconductor analyst at Goldman Sachs said (on page 10, and that's big finance so you know they only care about money): if tech companies are spending a trillion dollars to build up the infrastructure to support ai, what trillion dollar problem is it meant to solve? AI companies have a unique talent for burning venture capital and it's unclear if Open AI will be able to survive more than a few years unless everyone suddenly adopts it all at once. (Hey, didn't crypto and the metaverse also require spontaneous mass adoption to make sense?)

There is no problem that current ai is a solution to. Consumer tech is basically solved, normal people don't need more tech than a laptop and a smartphone. Big tech have run out of innovations, and they are desperately looking for the next thing to sell. It happened with the metaverse and it's happening again.

In summary:

Ai hasn't materially improved since the launch of Chatgpt4, which wasn't that big of an upgrade to 3.

There is currently no technological roadmap for ai to become better than it is. (As Jim Covello said on the Goldman Sachs report, the evolution of smartphones was openly planned years ahead of time.) The current problems are inherent to the current technology and nobody has indicated there is any way to solve them in the pipeline. We have likely reached the limits of what LLMs can do, and they still can't do much.

Don't believe AI companies when they say things are going to improve from where they are now before they provide evidence. It's time for the AI shills to put up, or shut up.

[animentality]

[noosphe-re]

"There was an exchange on Twitter a while back where someone said, ‘What is artificial intelligence?' And someone else said, 'A poor choice of words in 1954'," he says. "And, you know, they’re right. I think that if we had chosen a different phrase for it, back in the '50s, we might have avoided a lot of the confusion that we're having now." So if he had to invent a term, what would it be? His answer is instant: applied statistics. "It's genuinely amazing that...these sorts of things can be extracted from a statistical analysis of a large body of text," he says. But, in his view, that doesn't make the tools intelligent. Applied statistics is a far more precise descriptor, "but no one wants to use that term, because it's not as sexy".

'The machines we have now are not conscious', Lunch with the FT, Ted Chiang, by Madhumita Murgia, 3 June/4 June 2023

[porcupine-girl]

An important message to college students: Why you shouldn't use ChatGPT or other "AI" to write papers.

Here's the thing: Unlike plagiarism, where I can always find the exact source a student used, it's difficult to impossible to prove that a student used ChatGPT to write their paper. Which means I have to grade it as though the student wrote it.

So if your professor can't prove it, why shouldn't you use it?

Well, first off, it doesn't write good papers. Grading them as if the student did write it themself, so far I've given GPT-enhanced papers two Ds and an F.

If you're unlucky enough to get a professor like me, they've designed their assignments to be hard to plagiarize, which means they'll also be hard to get "AI" to write well. To get a good paper out of ChatGPT for my class, you'd have to write a prompt that's so long, with so many specifics, that you might as well just write the paper yourself.

ChatGPT absolutely loves to make broad, vague statements about, for example, what topics a book covers. Sadly for my students, I ask for specific examples from the book, and it's not so good at that. Nor is it good at explaining exactly why that example is connected to a concept from class. To get a good paper out of it, you'd have to have already identified the concepts you want to discuss and the relevant examples, and quite honestly if you can do that it'll be easier to write your own paper than to coax ChatGPT to write a decent paper.

The second reason you shouldn't do it?

IT WILL PUT YOUR PROFESSOR IN A REALLY FUCKING BAD MOOD. WHEN I'M IN A BAD MOOD I AM NOT GOING TO BE GENEROUS WITH MY GRADING.

I can't prove it's written by ChatGPT, but I can tell. It does not write like a college freshman. It writes like a professional copywriter churning out articles for a content farm. And much like a large language model, the more papers written by it I see, the better I get at identifying it, because it turns out there are certain phrases it really, really likes using.

Once I think you're using ChatGPT I will be extremely annoyed while I grade your paper. I will grade it as if you wrote it, but I will not grade it generously. I will not give you the benefit of the doubt if I'm not sure whether you understood a concept or not. I will not squint and try to understand how you thought two things are connected that I do not think are connected.

Moreover, I will continue to not feel generous when calculating your final grade for the class. Usually, if someone has been coming to class regularly all semester, turned things in on time, etc, then I might be willing to give them a tiny bit of help - round a 79.3% up to a B-, say. If you get a 79.3%, you will get your C+ and you'd better be thankful for it, because if you try to complain or claim you weren't using AI, I'll be letting the college's academic disciplinary committee decide what grade you should get.

Eventually my school will probably write actual guidelines for me to follow when I suspect use of AI, but for now, it's the wild west and it is in your best interest to avoid a showdown with me.

[probablyasocialecologist]

The problem here isn’t that large language models hallucinate, lie, or misrepresent the world in some way. It’s that they are not designed to represent the world at all; instead, they are designed to convey convincing lines of text. So when they are provided with a database of some sort, they use this, in one way or another, to make their responses more convincing. But they are not in any real way attempting to convey or transmit the information in the database. As Chirag Shah and Emily Bender put it: “Nothing in the design of language models (whose training task is to predict words given context) is actually designed to handle arithmetic, temporal reasoning, etc. To the extent that they sometimes get the right answer to such questions is only because they happened to synthesize relevant strings out of what was in their training data. No reasoning is involved […] Similarly, language models are prone to making stuff up […] because they are not designed to express some underlying set of information in natural language; they are only manipulating the form of language” (Shah & Bender, 2022). These models aren’t designed to transmit information, so we shouldn’t be too surprised when their assertions turn out to be false.

ChatGPT is bullshit