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I used to think image generation was cool back when it was still in the "generating 64x64 pictures of cats" stage. I still think it's really cool, but I do struggle to see it being a net positive for society. So far it has seemed to replace the use of royalty free stock images from google more than it has replaced actual artists, but this could definitely change in the future.

There are some nicer applications of image generation too, like dlss upscaling or frame generation, but I can't think of all that much else honestly.

I think we should avoid simplifying it to VLMs, LMs, Medical AI and AI for disabled people.

For instance, most automatic text capture ais (optical Character Recognition, or OCR) are powered by the same machine learning algorithms. Many of the finer-capability robot systems also utilize machine learning (Boston Dynamics utilizes machine learning for instance). There's also the ability to ID objects within footage, as well as spot faces and referencing it with a large database in order to find the person with said face.

All these are Machine Learning AI systems.

I think it would also be prudent to cease using the term 'AI' when what we actually are discussing is machine learning, which is a much finer subset. Simply saying 'AI' diminishes the term's actual broader meaning and removes the deeper nuance the conversation deserves.

Here are some terms to use instead

• Machine Learning = AI systems which increase their capability through automated iterative refinement.
• Evolutionary Learning = a type of machine learning where many instances of randomly changed AI models (called a 'generation') are run simultaneously, and the most effective is/are used as a baseline for the next 'generation'
• Neural Network = a type of machine learning system which utilizes very simple nodes called 'neurons' for processing. These are often used for image processing, LMs, and OCR.
• Convolution Neural Network (CNN) = a Neural network which has an architecture of neuron 'fliters' layered over each other for powerful data processing capabilities.

This is not exhaustive but hopefully will help in talking about this topic in a more definite and nuanced fashion. Here is also a document related the different types of neural networks

Mr crabs would use unethical llms, very accurate

I wish people stopped treating these fucking things as a knowledge source, let alone a reliable one. By definition they cannot distinguish facts, only spit out statistically correct-sounding text.

Are they of help to your particular task? Cool, hope the model you're using hasn't been trained on stolen art, or doesn't rely on traumatizing workers on the global south (who are paid pennies btw) to function.

Also, y'know, don't throw gasoline to an already burning planet if possible. You might think you need to use a GPT for a particular task or funny meme, but chances are you actually don't.

That's about it for me I think.

edit: when i say "you" in this post i don't mean actually you OP, i mean in general. sorry if this seems rambly im sleep deprived as fuckj woooooo

There are so many different things that are called AI, the term AI doesn't have any meaning whatsoever. Generally it seems to mean anything that includes machine learning somewhere in the process, but it's largely a marketing term.

Stealing art is wrong. Using ridiculous amounts of power to generate text is ridiculous. Building a text model that will very confidently produce misinformation is pretty dumb.

There are things that are called AI that are fine, but most aren't.

I'll just repeat what I've said before, since this seems like a good spot for this conversation.

I'm an idiot with no marketable skills. I want to write, I want to draw, I want to do a lot of things, but I'm bad at all of them. gpt like ai sounds like a good way for someone like me to get my vision out of my brain and into the real world.

My current project is a wiki of lore for a fictional setting, for a series of books that I will never actually write. My ideal workflow involves me explaining a subject as best I can to the ai (an alien technology or a kingdom's political landscape, or drama between gods, or whatever), telling the ai to ask me questions about the subject at hand to make me write more stuff, repeat a few times, then have the ai summarize the conversation back to me. I can then refer to that summary as I write an article on the subject. Or, me being lazy, I can just copy-pasta the summary and that's the article.

As an aside, I really like chatgpt 4o for lore exploration, but I'd prefer to run an ai on my own hardware. Sadly, I do not understand github and my brain glazes over every time I look at that damn site.

It is way too easy for me to just let the ai do the work for me. I've noticed that when I try to write something without ai help, it's worse now than it was a few years ago. generative ai is a useful tool, but it should be part of a larger workflow, it should not be the entire workflow.

If I was wealthy, I could just hire or commission some artists and writers to do the things. From my point of view, it's the same as having the ai do the things, except it's slower and real humans benefit from it. I'm not wealthy though, hell, I struggle to pay rent.

The technology is great, the business surrounding it is horrible. I'm not sure what my point is.

I honestly am skeptical about the medical stuff. Machine learning can't even do the stuff it should be good at reliably, specifically identifying mushrooms/mycology in general.

My biggest problem with AI is how it was pushed and marketed to us in ways that don't make sense / are unethical. Even the environmental concerns would be ameliorated if AI weren't being pushed into everything. (Using "AI" here to refer to things like LM, image, and art generators,etc.)

LMs give the appearance of understanding, but as soon as you try to use them for anything that you actually are knowledgable in, the facade crumbles.

Even for repetitive tasks, you have to do a lot of manual checking to ensure they did not start hallucinating half way through.

I agree 👍

Ultimately, the issue is our current societies being fucked. If AI were refined, sensibly monitored and generally used by people who can recognize mistakes (where it matters), and keep their fossil fuel usage in check, AI could be a big step towards gay space communism. Like, who wants to do menial labor? Let AI do it where sensible and pay the former workers the money that's saved by doing that. But as it is, it's mostly going to be used to further the agendas of authoritarians and capitalists.

This list is missing: AI generated images are not art.

There is an over arching issue with most of the extant models being highly unethical in where they got their data, effectively having made plagiarism machines.

It is not ok to steal the content of millions of small independent creators to create slop that drowns them out. Most of them were already offering their work for free. And I am talking about LMs here, writing is a skill.

Say what ever you want about big companies being bad for abusing IP laws, but this is not about the laws, not even paying people for their work, this is about crediting people when they do work, acknowledging that the work they did had value, and letting people know where they can find more.

Also, I don’t really buy the “it’s good for disabled people” that feels like using disabled people as a shield against criticism, and I’ve yet to see it brought up in good faith.

A lot of those points boil down to the same thing: "what if the AI is wrong?"

If it's something that you'll need to check manually anyway, or where a mistake is not a big deal, that's probably fine. But if it's something where a mistake can affect someone's well-being, that is bad.

Reusing an example from the pic:

• Predicting 3D structures of proteins, as in the example? OK! Worst hypothesis the researchers will notice that the predicted structure does not match the real one.
• Predicting if you have some medical problem? Not OK. A false negative can cost a life.

That's of course for the usage. The creation of those systems is another can of worms, and it involves other ethical concerns.

Genuinely, the only problem I see with the development of LLMs and AI in general is that said development has a massive tumor on its back called Corporate Interest. That's pretty much the one and only cause for absolutely every destructive, shady, or downright immoral aspect tied to these things nowadays...

As tools in and of themselves, yes! LLMs have an immense potential not of replacing people, but of helping people get stuff done faster, which in turn would give us a lot of extra time to polish the everloving spit out of the stuff we make!

LLM/AI research should be 100% non-profit and democratised, with well-established guidelines and full transparency, as I see it. This is a huge step in our development as a species, and Altman-likes are not the people who should be in charge of it.

Edit: as for VLMs, I kinda' see them as a fad, to be honest. It still irks me when anyone adds "art" to anything artificially generated at the moment, but I get the feeling people will tire of the novelty once the need for genuine art will cease being satisfied by the above-mentioned.

What does "AI for disabled people" entail? A lot of 'good AI' things I see are things I wouldn't consider AI, e.g. VLC's local subtitle generation.

Sounds like a pretty nuanced opinion to me. AI's biggest problem is that it's being driven by profit seeking companies that, as usual, have no interest in the damaging "externalities" that are involved. But anyone that says it has no application and all it does is hallucinate and waste energy is not aware of the progress being made.

Smorty!!!!
Thank you for this conversation

What I think is missing from your viewpoint (and from most people's, this is [IMO] a problem at scale) is the distinction between "simple" and broad machine learning, and the very specific things that are Large Language Models.

For example, there are no small Large Language Models, and I think that the oxymoron speaks for itself. Machine learning is a very good thing, and automated classification is definitely its best use case, but they are not a small version of ChatGPT, the same way that the average Joe is not a smaller version of a billionaire.

For more details, these small models are trained on a small set of data, how small depending on how specific the task is; as an example, I worked with models that detect manufacturing defects on production lines, and theses need a few hundreds images in order to produce good results, this make it very easy to produce the data ourselves, and it is relatively cheap to train energy-wise.

Compared to that, Large Language Models, and their audiovisual counterparts, operate on billions of data, and work on a task so general that they provide incredibly bad results. As a little statistical reminder, anything below 95% confidence is a bust, LLMs are way below that.

It's very important to distinguish the two, because all of the positives you list for AI are not about LLMs, but about simple machine learning. And this confusion is by design, techbros are trying to profit of the successes of other form of artificial intelligence by pretending that AI is this one single thing, instead of an entire class of things.

Otherwise, I generally agree with the rest of your points.

I think generative AI is mainly a tool of deception and tyranny. The use cases for fraud, dehumanization and oppression are plentiful. I think Iris Meredith does a good job of highlighting the threat at hand. I don’t really care about the tech in theory: what matters right now is who builds it and how it is being deployed onto the world.