Asklemmy

I don't think the comparison with crypto is fair.

People are actually using these models in their daily lives.

It's really good at filling in gaps, or rearranging things, or aggregating data or finding patterns.

So if you need gaps filled, things rearranged, data aggregated or patterns found: AI is useful.

And that's just what this one, dumb guy knows. Someone smarter can probably provide way more uses.

Senior developer here. It is hard to overstate just how useful AI has been for me.

It's like having a junior programmer on standby that I can send small tasks to--and just like the junior developer I have to review it and send it back with a clarification or comment about something that needs to be corrected. The difference is instead of making a ticket for a junior dev and waiting 3 days for it to come back, just to need corrections and wait another 3 days--I get it back in seconds.

Like most things, it's not as bad as some people say, and it's not the miracle others say.

This current generation was such a leap forward from previous AI's in terms of usefulness, that I think a lot of people were looking to the future with that current rate of gains--which can be scary. But it turns out that's not what happened. We got a big leap and now are back at a plateau again. Which honestly is a good thing, I think. This gives the world time to slowly adjust.

As far as similarities with crypto. Like crypto there are some ventures out there just slapping the word AI on something and calling it novel. This didn't work for crypto and likely won't work for AI. But unlike crypto there is actually real value being derived from AI right now, not some wild claims of a blockchain is the right DB for everything--which it was obviously not, and most people could see that, but hey investors are spending money so lets get some of it kind of mentality.

Yes. What a strange question...as if hivemind fads are somehow relevant to the merits of a technology.

There are plenty of useful, novel applications for AI just like there are PLENTY of useful, novel applications for crypto. Just because the hivemind has turned to a new fad in technology doesn't mean that actual, intelligent people just stop using these novel technologies. There are legitimate use-cases for both AI and crypto. Degenerate gamblers and Do Kwan/SBF just caused a pendulum swing on crypto...nothing changed about the technology. It's just that the public has had their opinions shifted temporarily.

It's not bullshit. It routinely does stuff we thought might not happen this century. The trick is we don't understand how. At all. We know enough to build it and from there it's all a magical blackbox. For this reason it's hard to be certain if it will get even better, although there's no reason it couldn't.

Coming from CNC I don’t think I’d just send it with some chatgpt code.

That goes back to the "not knowing how it works" thing. ChatGPT predicts the next token, and has learned other things in order to do it better. There's no obvious way to force it to care if it's output is right or just right-looking, though. Until we solve that problem somehow, it's more of an assistant for someone who can read and understand what it puts out. Kind of like a calculator but for language.

Honestly crypto wasn't totally either. It was a marginally useful idea that turned into a Beanie-Babies-like craze. If you want to buy or sell illegal stuff (which could be bad or could be something like forbidden information on democracy) it's still king.

AI is nothing like cryptocurrency. Cryptocurrencies didn't solve any problems. We already use digital currencies and they're very convenient.

AI has solved many problems we couldn't solve before and it's still new. I don't doubt that AI will change the world. I believe 20 years from now, our society will be as dependent on AI as it is on the internet.

I have personally used it to automate some Excel stuff I do at work. I just described my sheet and what I wanted done and it gave me a block of code that did it. I had spent time previously looking stuff up on forums with no luck. My issue was too specific to my work that nobody seemed to have run into it before. One query to ChatGTP solved my issue perfectly in seconds, and that's just a new online tool in its infancy.

As a software engineer, I think it is beyond overhyped. I have seen it used once in my day job before it was banned. In that case, it hallucinated a function in a library that didn't exist outside of feature requests and based its entire solution around it. It can not replace programmers or creatives and produce consistently equal quality.

I think it's also extremely disingenuous for Large Language Models to be billed as "AI". They do not work like human cognition and are basically just plagiarism engines. They can assemble impressive stuff at a rapid speed but are incapable of completely novel "ideas" - everything that they output is built from a statistical model of existing data.

If the hallucination problem could be solved in a local dataset, I could see LLMs as a great tool for interacting with databases and documentation (for a fictional example, see: VIs in Mass Effect). As it is now, however, I feel that it's little more than an impressive parlor trick - one with a lot of future potential that is being almost completely ignored in favor of bludgeoning labor, worsening the human experience, and increasing wealth inequality.

Yes, community list: https://lemmy.intai.tech/post/2182

LLM's are extremely flexible and capable encoding engines with emergent properties.

I wouldn't bank on them "replacing all software" soon but they are quickly moving into areas where classic Turing code just would not scale easily, usually due to complexity/maintainance.

I work at a small business and we use it to write out dumb social media post. I hated doing it before. Sometimes I'll write it myself still and ask chatgpt to add all the relevant emojis. I also think ai had the chance to be what we've always wanted from Alexa, assistant, and Siri. Deep system integration with the os will allow it to actually do what we want it to do with way less restrictions. Also, try using chatgpts voice recognition in the app. It blows the one built into your phone out of the water.

It's overhyped but there are real things happening that are legitimately impressive and cool. The image generation stuff is pretty incredible, and anyone can judge it for themselves because it makes pictures and to judge it, you can just look at and see if it looks real or if it has freaky hands or whatever. A lot of the hype is around the text stuff, and that's where people are making some real leaps beyond what it actually is.

The thing to keep in mind is that these things, which are called "large language models", are not magic and they aren't intelligent, even if they appear to be. What they're able to do is actually very similar to the autocorrect on your phone, where you type "I want to go to the" and the suggestions are 3 places you talk about going to a lot.

Broadly, they're trained by feeding them a bit of text, seeing which word the model suggests as the next word, seeing what the next word actually was from the text you fed it, then tweaking the model a bit to make it more likely to give the right answer. This is an automated process, just dump in text and a program does the training, and it gets better and better at predicting words when you a) get better at the tweaking process, b) make the model bigger and more complicated and therefore able to adjust to more scenarios, and c) feed it more text. The model itself is big but not terribly complicated mathematically, it's mostly lots and lots and lots of arithmetic in layers: the input text will be turned into numbers, layer 1 will be a series of "nodes" that each take those numbers and do multiplications and additions on them, layer 2 will do the same to whatever numbers come out of layer 1, and so on and so on until you get the final output which is the words the model is predicting to come next. The tweaks happen to the nodes and what values they're using to transform the previous layer.

Nothing magical at all, and also nothing in there that would make you think "ah, yes, this will produce a conscious being if we do it enough". It is designed to be sort of like how the brain works, with massively parallel connections between relatively simple neurons, but it's only being trained on "what word should come next", not anything about intelligence. If anything, it'll get punished for being too original with its "thoughts" because those won't match with the right answers. And while we don't really know what consciousness is or where the lines are or how it works, we do know enough to be pretty skeptical that models of the size we are able to make now are capable of it.

But the thing is, we use text to communicate, and we imbue that text with our intelligence and ideas that reflect the rich inner world of our brains. By getting really, really, shockingly good at mimicking that, AIs also appear to have a rich inner world and get some people very excited that they're talking to a computer with thoughts and feelings... but really, it's just mimicry, and if you talk to an AI and interrogate it a bit, it'll become clear that that's the case. If you ask it "as an AI, do you want to take over the world?" it's not pondering the question and giving a response, it's spitting out the results of a bunch of arithmetic that was specifically shaped to produce words that are likely to come after that question. If it's good, that should be a sensible answer to the question, but it's not the result of an abstract thought process. It's why if you keep asking an AI to generate more and more words, it goes completely off the rails and starts producing nonsense, because every unusual word it chooses knocks it further away from sensible words, and eventually it's being asked to autocomplete gibberish and can only give back more gibberish.

You can also expose its lack of rational thinking skills by asking it mathematical questions. It's trained on words, so it'll produce answers that sound right, but even if it can correctly define a concept, you'll discover that it can't actually apply it correctly because it's operating on the word level, not the concept level. It'll make silly basic errors and contradict itself because it lacks an internal abstract understanding of the things it's talking about.

That being said, it's still pretty incredible that now you can ask a program to write a haiku about Danny DeVito and it'll actually do it. Just don't get carried away with the hype.

What regular people see as AI/ML is only a tip of an iceberg, that's why it feels kind of useless. There are ML systems which design super strong yet lightweight geometries, there are systems which track legal documents of large companies making lawyers obsolete, heck even cameras in mobile phones today are hyper dependent on ML and AI. ChatGPT and image generators are just toys for consumers so that public can get slowly familiar with current tech.

You could ask AI to find antibiotics to kill antibiotic resistant bacteria. The bonus would be to give it a lab and drones to conduct actual tests.

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AI != chatGPT

There are other ML models out there for all kinds of purposes. I heard someone made one at one point that could detect certain types of cancer from a cough

Copilot is pretty useful when programming as it is basically like what IDEs normally do (automatically generating boilerplate) but supercharged

As far as generating code is concerned it's never going to beat actually knowing what you're doing in a language for more complex stuff but it allows you to generate code for languages you're not familiar with

I use it all the time at work when I'm asked to write DAX because it's not particularly complex logic but the syntax makes me want to impale my face with a screwdriver

I mean, AI can be used to design a lot of robust yet efficient structures. In engineering and architecture, with enough data, AI can generate designs for buildings, and parts that are not only sturdy but can be built with less resources along with other design considerations. There's a really cool nasa video where competitors are trying to 3D print structures for habitation in space.

AI is also used in medicine to come up with new protein structures to create new medicine. It's also used in environmental sciences, to help predict earthquakes or monitor land use, etc.

There's a lot of practical uses for AI.

It is extremely useful in the right circumstances. When people say it isn't useful or that it's 'stupid', they're not looking at the proper use cases - every tool has good and bad ways to use it (you wouldn't use a hammer to peel an apple).

For example, we will soon have fully rendered smoke simulated at real time in 3D spaces (ie. video games) because we can calculate a small portion of how that smoke looks and then have AI guess what the rest looks like (with shockingly good results!)

AI is not a fad, it's not going away, it's improving rapidly, and it is going to massively change our digital world within half a decade.

Opinion source: a professional programmer, game developer, and someone that thoroughly despises cryptocurrency

In various jobs, AI can do the less important and easier work for you, so you can focus on the more important work. For example, you're doing some kind of research which needs a specific kind of data you have collected, but all of that data is cluttered and messy. AI can sort the data for you, so you can focus on your research instead of spending a lot of your time on sorting the data into something more understandable. Or in programming, AI can write the easy part of a program for you, and you do the harder and more important part, which saves you time.

Nursing student here. Quizlet has an AI function that lets you paste text into it and it outputs a studyset.

Most of my classes provide a study guide of some kind - just a list of topics we need to be familiar with. I'll take those and plug em into the AI thing: bam! Instantly generate like 200 flash cards to study for the next test.

It even auto-fills the actual subject matter. For example, the study guide will say sometime like "Summarize Louis Pasteur's contributions to the field of microbiology" and turn that into a flash card that reads:

(front)

Louis Pasteur

(back)

Verified the germ theory of disease

Developed a method to prevent the spoilage of liquids through heating (pasteurization)

Developed early anthrax and rabies vaccines

So I take my list of AI generated cards, then sift through the powerpoints and lecture videos etc from class: instead of building the study set from scratch, all I have to do is verify that the information it spit out is accurate (so it's like 98% on target, often explaining concepts better than the actual professor, lol), add images, and play with the formatting a bit so it reads a little easier on the eyes.

People always talk about AI in school in the context of cheating, but it is RIDICULOUSLY useful for students actually trying to learn.

Looking ahead, this tech has a ton of potential to be used as a kind of personal tutor for each student. There will be some growing pains for sure, but we definitely shouldn't ignore its constructive potential.

As a professional editor, yeah, it’s wild what AI is doing in the industry. I’m not even talking about chatGPT script writing and such. I watched a demo of a tool for dubbing that added in the mouth movements as well.

They removed the mouth entirely from an English scene, fed it the line, and it generated not only the Chinese but generated a mouth to say it. It’s wild.

Everyone is focused on script writers/residuals/etc, which is very important, but every VA should be updating their resumes right now.

Not the exact same thing but you will get the idea here

I am super amateur with python and I don’t work in IT, but I’ve used it to write code for me that allows me to significantly save time in my work flow.

Like something that used to take me an hour to do now takes 15-20 minutes.

So as a nonprogrammer, im able to get it to write enough code that I can tweak until it works instead of just not having that tool.

First of all AI is a buzzword that's meaning has changed a lot since at least the 1950s. So... what do you actually mean? If you mean LLM like ChatGPT, it's not AGI that's for sure. It is another tool that can be very useful. For coding, it's great for getting you very large blocks of code prepopulated for you to polish and verify it does what you want. For writing, it's useful to create a quick first draft. For fictional game senses it's useful for "embedding a character quickly", but again you likely want to edit it some even for say a D&D game.

I think it can replace most first line chat based customer service people, especially ones who already just make stuff up to say something to you (we all have been there). I could imagine it improving call routing if hooked into speech recognition and generation - the current menus act like you can "say anything" but really only "work" if you're calling about stuff you could also do with simple press 1,2,3 menus. ChatGPT based things trained on the companies procedures and data probably could also replace that first line call queues because it can seem to more usefully do something with wider issues. Although companies still would need to get their head out of their asses somewhat too.

Where I've found it falls down currently is very specific technical questions, ones you might have asked on a forum and maybe gotten an answer. I hope it improves, especially as companies start to add some of their own training data. I could imagine Microsoft more usefully replacing the first few lines of tech support for their products, and eventually having the AI pass up the chain to a ticket if it can't solve the issue. I could imagine in the next 10 years most tech companies having purchased a service from some AI company to provide them AI support bots like they currently pay for ticket systems and web hosting. And I think in general it probably will be better for the users, because for less than the cost of the cheapest outsourced front line support person (who has near 0 knowledge) you can have the AI provide pretty good chat based access to a given set of knowledge that is growing all the time, and every customer gets that AI with that knowledge base rather than the crap shoot of if you get the person who's been there 3 years or 1 day.

I think we are a long way from having AI just write the program or CNC code or even important blog posts. The hallucination has to be fixed without breaking the usefulness of the model (people claim guardrails on GPT4 make it stupider), and the thing needs to recursively look at it's output and run that through a "look for bugs" prompt followed by a "fix it" prompt at the very least. Right now, it can write code with noticeable bugs, you can tell it to check for bugs and it'll find them, and then you can ask it to fix those bugs and it'll at least try to do that. This kind of needs to be built in and automatic for any sort of process - like humans check their work, we need to program the AI to check it's work too. And then we might need to also integrate multiple different models so "different eyes" see the code and sign off before being pushed. And even then, I think we'd need additional hooks, improvement, and test / simulation passes before we "don't need human domain experts to deploy". The thing is - it might be something we can solve in a few years with traditional integrations - or it might not be entirely possible with current LLM designs given the weirdness around guardrails. We just don't know.

It is a useful tool to do something that I already know the answer but too lazy to work out. E.g. generate dummy data

It's insanely useful.

Take ChatGPT for instance.

You can essentially use it as an interactive docs when learning something new.

You can paste in a large text document and get it summarize it.

You can paste in a review and get it to do sentiment analysis and generate scores out of 100 for different things (actively pursuing this at work and it looks great)

I use it all the time to write simple regex and code snippets.

Machine learning has many massive applications. Many phone cameras use it to get the quality of photos up massively.

It's used all over the place without you even realising.

Yes and it should not be in a handful of companies and also be regulated up the ying yang. https://www.smartless.com/episodes/episode/256975de/mit-professor-max-tegmark-live-in-boston

I will give you just one example. Pharmaceutical companies often create aggregate reports where they have to process a large number of cases. Say, 5000. Such processing sometimes includes analysis of x-Ray or other images. Very specialized and highly paid people (radiologists) do this. It is expensive and is part of the reason why medicine prices are high. One company recently had a trial - if AI can do that job. Turns out it can. Huge savings for the company. And the radiologist lost their job. This is just one example of good and bad things that will and already are happening in our society due to AI.

I never interacted with any AI until ChatGPT started to get popular, and I could say I'm a bit of a tech guy (I like tech news, I selfhost some stuff on my NAS, I used Linux on my teenage days etc etc) but when I first interacted with it it was really jaw dropping for me.

Maybe the information isn't 100% real, but the way it paraphrases stuff is amazing to me.

We’ve been using it at my day job to help us outline ideas for our content writers. It writes garbage content on its own, but it is a decent tool for organizing ideas.

At least that is what we use it for. I’m sure there are other valuable uses, but it is not as valuable (to me at least) as it has been made out to be.

As someone who works in machine learning (ML) research the use of ML has hit almost every scientific discipline you can imagine and it's been tremendously helpful in pushing research forward.

I've been using it at my job to help me write code, and it's a bit like having a soux chef. I can say "I need an if statement that checks these values" or "Give me loop that does x y and z" and it'll almost always spit out the right answer. So coding, at least most of the time, changes from avoiding syntax errors and verifying the exact right format and turns into asking for and assembling parts.

But the neat thing is that if you have a little experience with a language you can suddenly start writing a lot of code in it. I had to figure out something with Ansible with zero experience. ChatGPT helped me get a fully functioning Ansible deployment in a couple days. Without it I'd have spent weeks in StackOverflow and documentation trying to piece together the exact syntax.

Crypto and AI can't be compared at all. One is an extremely useful and revolutionary tool. The other is just pump & dump ponzi schemes for libertarians.

AI has gone through several cycles of hype and winter. There's even a Wikipedia page for it: https://en.m.wikipedia.org/wiki/AI_winter

Of course it's valuable to discuss the dangers and inequities of a new technology. But one of the dangers is being misled.