The small help it gives does not equal the vast evil done to the environment, communities, and actual makers and creators.

Broadly speaking, fuck AI

It’s a tool, much like when Google Search first started. LLMs can find things standard ways of doing research cannot. AlphaFold is a useful tool for protein modelling and experimental design, but everything it generates needs validation.

If you have a large dataset you can train to predict things not in the database. But again, everything generated needs to be validated.

AGI doesn’t exist and is not being developed, but the idiots with all the money and power believe it is. Their stupidity and insistence on feeding all our resources to this stuff is gonna kill us all.

I feel like it’s making people dumber. I keep getting screenshots of Google ai summary from people as if that’s the answer and they’re confident in it. I keep finding those are not correct. For me, ai has created more work because I can no longer trust my colleagues statements.

I refuse to use AI as a tool for anything other than making tools.

I can’t write LISP but I use AutoCAD. I use an LLM to write LISP routines.

I spent MONTHS looking for a way to catalog my plant collection. Tried a dozen open source projects and none did what I wanted it to do. So I used Claude to make a simple database website…and it was able to add a ton of pipe dream features.

Nothing I make is for sale and I don’t claim it as my own. They’re tools for ME to use. And the important part is that once the tool is done, the LLM gets closed.

• How come the most memory-inefficient ML model we have ended up being the most powerful one. Can we rewrite the universe so modern advanced AI is based on network inference or ensemble models or sth
• How come AI has taken over the economy, and it doesn’t seem like a bubble (or at least not the crypto type of bubble)
• I’m a bit surprised that the most predominant use of AI/LLM seem to be… as a search engine wrapper. Thankfully ChatGPT is getting better at it, their default model has a built-in search engine integration now. This is kind of important since the company is getting big enough that their model bears social responsibilities…
• I have an asshole-ish work environment where the head honchos only cares about professionalism and efficiency… so I have no shame using AI for work. They don’t deserve my best tbh
• In terms of actual usage for my work, AI outputs can be anywhere from very good to very bad in an instant, and sometimes it’s hard to tell the two apart…
• It’s surprisingly helpful as a primer to help me with things I’m not good at; researching niche information, finding resources
• For personal usage, I’m still hoping that there is a way to work AI into some type of a home automation loop… I haven’t found that sweet spot yet. Maybe it’s just my lack of skill at the moment. Hopefully I can hook together some shitty models with search engine skills (on my own SearXNG) as a semi-useful agent

On one side…

On the other…

I’m a shameless local LLM shill. I have one loaded right now, experimenting with it.

I also thought Sam Altman was a psychopath before that was the popular opinion, and have never subscribed to OpenAI or even used their free UIs. Not once. Not even the “original” GPT 3.5.

I don’t plan on ever doing it. I will rail against them.

In other words, the sides aren’t mutually exclusive.

One can hate “AI” with a burning passion, using the term AI pejoratively. And be passionate about local ML.

Artificial intelligence is good at doing boring repetitive tasks or point out things for a human to look at when there is too much data for us to scrutinise.

If you do not have the skill to verify the output you are almost certainly getting garbage out of it.

The fact that they cram AI into everything is because they are throwing AI at the wall and seeing what sticks. Spending millions on a 1% chance that you will make billions makes economical sense if you can afford to lose.

“Everyone is trying to use a Magnifying Glass to do everything from change flathead screws to preparing food, from levering open crates to surgical incisions.”

In other words: The base algorithms and techniques are very interesting and have valid applications in a narrow range of fields, being useful for pattern recognition, generation, and analysis.

The problem is everything else. Everyone is trying to use that one tool for things it is neither effective nor practical nor appropriate to use it on, and then being shocked when this has widespread negative outcomes for both themselves and everyone around them. Separately but parallel, the drive to find useful applications of it (in areas where there aren’t) is causing companies and individuals to engage in grossly unethical behavior.

Even in the fields where it is most useful, you have to be cautious about not treating it as a “truth machine”. A speaker I heard put it simply: “AI cheats.” It will latch on to the most prominent patterns, not necessarily the ones you want it to analyze.

I’ve been doing scientific software development for 20 years, and here’s my personal experience:

• Software development as it had been is already over due to AI. There’s no reason to write code yourself anymore in 99% of cases. Even highly technical stuff (GPU algorithms, for example) are no problem for the AI.

• Scientific work is very different than it used to be. The AI doesn’t have the initiative to just do it for you yet the way it can with writing software, but it’s an expert in every field so it provides an excellent foundation for your own novel ideas and it can often suggest new ideas from fields you aren’t personally knowledgeable about.

• Socializing is going to be very different soon. Right now the AI is already more interesting to talk to than most humans, but talking to it doesn’t feel like talking to a human and doesn’t satisfy the need for interpersonal interaction. I expect that to change. (I suspect that the current absence of a human-like AI is more because developing it is not good business than because it’s technically difficult.)

• A lot of AI critics have objectively false ideas of how well AI works. I think they either haven’t tried cutting-edge models recently or they have deliberately tried to make those models fail. You can break most things if you try; that doesn’t mean they don’t work well.

As I type this, an AI is working on a tricky problem in molecular dynamics for me. It has already found and fixed issues with the algorithm that my co-worker spent a month on, but it thinks that a different algorithm it came up with can do even better. After coming up with the idea, it’s independently implementing it, unit testing it, running simulations with it, and doing statistical analysis of those simulation results. If it gets errors, it can debug them on its own. If the results aren’t as good as it expected, it can iterate over different variants on its own. If the algorithm ends up not working, it can reason about why, from a scientific perspective. What the AI does in hours would have taken me weeks if I came up with the idea, which I didn’t.

Right now human experts can still do what AI does, just slower. I expect that in less than 5 years, that will probably no longer be true. Predicting the future after that point is nearly impossible. Will we all die? Maybe.

Its shit and I’ll be glad when it gets flushed.

There are a lot of things that AI can do better than any human.

Thinking, writing, conversing and art are NOT those things.

Let AI analyze, not create. End the slop.

I think LLMs are going to cause massive change, not all of it good.

Ultimately, I’m an optimist. I think in the long run, LLMs are going to enable us to do amazing things that we wouldn’t have been able to do without them. In the short term… I dunno. It’s going to be a rough transition.

I do think the people who think LLMs are going to keep getting better, leading to either some sort of techno-utopia, or kill us all off maybe don’t really understand how they work and what the implications are.

I also think the people who are categorically against AI are making a mistake out of fear, but that’s pretty understandable.

I don’t really use it personally (other than times I log in on a work computer, look something up, and Google’s AI search defaults). But I also don’t really condemn it as strongly as others seem to, I guess. It depends on how it’s used.

When it’s used to take work done by humans, then regurgitate its own version of that work to replace those jobs, that’s a problem. If actual artists, writers, designers, engineers, coders, etc. can no longer earn a living after being replaced by AI, we run the risk of complete cultural and developmental stagnation.

But I think my main point of disagreement with a lot of the AI conversations happening here revolves around how we look at waste and environmental impact. Not in the sense that AI isn’t still a problem in those aspects, but that it seems like a very convenient boogeyman for people to blame while ignoring the myriad other wasteful aspects of the world we live in.

Basically, with the environmental impact of data centers and energy costs of hardware in general, why do we focus so much on what that compute is used for, as opposed to addressing those issues in a more comprehensive sense? Does it matter if a data center is built for AI or for any other hosting provider? Or if someone runs a local AI model on their PC, is that any more detrimental to the environment than someone who plays video games for several hours each day?

I feel like there are lines that people who claim to primarily care about the environment are afraid to draw, when it’s easier to pin the blame wholly on AI. So if someone says that they used AI to help make their spreadsheets cleaner, to translate a website, or to summarize the content of a book, I don’t really jump straight to blanket criticism. Otherwise I’d have to take the same criticism towards people who host a plex server, who play MMOs, or who run Lemmy instances.