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I’m using it to learn foreign language. Part of learning is using the language conversationally, but part of conversation with a language you aren’t fluent it is a barrier to using it because of social anxiety of using it wrong.
A foreign language chatbot won’t care if you screw up and won’t care how much delay there is in your response because you’re trying to string the next response back properly.
replace very deadly and low paying jobs (such as coal miners)
LLMs, neural networks, and machine learning have been used in the technical; data annalist, and scientific communities since forever.
The idea that chatbots are good for nothing is a minority opinion. AI hate comes from the top-down dramatic changes to the tech industry built on delusional hopes and fantasies.
Just like the Luddites before us, we don’t hate technology or progress, we resent the lumbering tyranny of capital that has already ruined our jobs, our hobbies, and threatens to make us all poorer and worse off.
I’ve had a progressive, disabling disease for the past 12 years that no one could diagnose. I have found that AI is very good at pulling in all sorts of case studies that correlate with my symptoms. After working with it over a period of months, carefully pushing back against any inconsistencies, checking its sources, etc. We were able to zero in on a very rare disease that seems to closely fit my situation.
Thank goodness I have a neurologist who is open to suggestions. I presented the evidence to him and now it’s his top consideration. He wants to send me to mayo clinic to be sure, but so far immunotherapies have been helping me which is even more evidence for it.
Only about 300 people in the US have this disease. I would have never figured it out without AI.
If you don’t mind me asking, what disease? I’ve found myself in a very similar position.
Isaacs syndrome. What happens is the immune system mistakenly attacks the machinery that re-polarizes the peripheral nerves after firing, so they fire constantly, which causes all sorts of problems. It’s an ALS mimic, so I was initially diagnosed with that. But after a long time of not dying, plus EMG inconsistencies, it became clear that was wrong.
I really wish you luck. It’s a hard and lonely road.
Wow. An actual, real life, good story involving generative AI doing what it’s supposed to do. Filtering heaps of data, searching for virtually invisible minutae, to make life more livable.
Thanks for sharing! I hope this healing journey obly gets better for you.
og ai - used in simulating folding proteins, logistical planning and agri forecasting
marketed ai, llm - good at understanding what you write even if it is gibberish. can maybe pick up key notes on legalese docs. could be used as good social engineering~ like how parents tell kids santa is real.
Most people on Lemmy would never admit that LLMs have any use case whatsoever. Even though they’ve literally solved math problems at the limits of modern research.
Do you have a reasurch paper on that?
https://openai.com/index/navier-stokes-solution/
https://openai.com/index/building-scientific-understanding-with-academic-communities/
https://en.wikipedia.org/wiki/OpenAI_bulk_release_of_mathematical_papers
Several research mathematicians have stated publicly that they believe the Navier Stokes proof to be correct: Luis Silvestre, Javier Gómez-Serrano, Steven Strogatz, Gonzalo Cao-Labora, and Sébastien Gouëzel. I have not heard much controversy about whether the results are correct or not, moreso that the proofs are poorly written and would not be accepted by a referee in their current state.
Folding@Home for protein folding simulations to cure diseases. Probably newer examples, so I’ll say medical research and simulation, vaguely.
I’ve admittedly accelerated my competence in daily driving Linux by using LLM like a search engine. I’m struggling to come up with much else that’s positive. Even that’s kinda neutral. It’s only true because search engines got worse for a myriad of reasons.
One thing to be clear when asking this question. Are you asking about all AI or do you mean current LLMs? Those are two very different things and will get you very different answers.
AI - can be good, Google’s alphafold worked on new medicine, there’s defect recognition models running in factories that increase consumer safety, and so much more. All of these have existed for a while or are still in development.
LLMs - well, I’m yet to see any actual net good from them in any way shape or form.
LLMs are pretty good for office jobs where you have huge amounts of documents to churn through, chunking them into a RAG, and then asking the documents questions about itself that you can then verify by getting the page and line number that it pulled the reference from is super handy.
We’ve had tools for fuzzy searching files for ages. Didn’t need to steal all human work and burn the planet to make search a tiny bit easier
You may be right, but the question was, “How do we use AI to help people?” Not, “Is AI ethical?”
But if using the AI perpetuates the worst side effects, then it’s not actually helping people in the long run, it’s making things the tiniest bit easier in the very moment at the expense of their future. Doesn’t sound helpful to me
Local LLMs, or SLMs, are surprisingly efficient at document handling with vague inputs, which was a weakness of traditional search algorithms. You can use a mid tier GPU for that.
When the bubble pops, that’s where the research community will go.
People in the Global South can use AI to improve their scamming methods and funnel money faster away from retirees in the West.
How the fuck is that helping people? Throwing people into poverty to fill the pockets of criminals who end up leaving lavish lives that the people they scammed it from couldn’t even dream of? I mean, it’s already happening, but fuck no.
I don’t know if I got upvotes for the sentiment or the sarcasm, but I sometimes like to use comments to point out the insanity of the far left attitude here. For some who’ve already posted, AI is an evil created by the West, and others using that evil to harm the West is fantasy.
There’s plenty of useful things AI can do, but it can also be used for harm. Harm does not become good because its victims belong to the group some impulsively hate without nuance.
I feel like text based LLMs have some uses, but the real cool stuff happens when you go into the analysis models. The classic example is detecting tumors in images, this method can be applied to any irregularities though, this may allow patients to get screened without the need of a doctor, but just a nurse or even entirely autonomously.
They can catch obvious stuff in a code review before someone wastes my time reviewing garbage. Basically any time the transactional cost of false positives or false negatives is close to zero, AI is fine.
That being said, I think there are a lot of hidden cognitive costs that we aren’t good at modeling or putting numbers on.
To help overturn wrongful convictions and fight human rights abuses: https://hrdag.org/tech-corner/
There are plenty; AI is used in Pharma research to create medications. AI is used to combat climate change, to help people with dementia, in protection of rainforests or endangered animals - I’ve seen dozens of projects or products that tangibly improve people’s lives.
That is true and a great use of AI, but none of those are genAI/LLMs.
I have that traditional ML techniques get bundles with genAI.
Worth mentioning that in most of these cases, it’s an application of AI doing what it’s actually good at (pattern recognition), which is then analyzed by actual people, rather than what people criticize it for (text/image generation) that produces slop.
I remember hearing about AI models being able to identify cancerous tumors before they manifest in ways that human doctors can identify them. AI is really good at pattern recognition in that way.
Use them to replace CEOs.
Which type? There’s quite a few, and some date back decades. Recurrent Neural Networks, for example, have been used by Google Translate since 2020.
But to provide a bit more of a direct answer, there are machine learning types for image analysis. One example that comes to mind is eye tracking models for vr headsets. You feed them camera feeds of your eyes, and they spit out an (X,Y) value for each. Steam Frame uses that for foveated rendering, and babble uses that to feed your look direction to your avatar.
Remote Sensing is also a large field. We do a lot of object detection and image classification on airborne and satellite images using convolutional neural networks.
