Interesting, thanks for sharing.
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So for those not familar with machine learning, which was the practical business use case for "AI" before LLMs took the world by storm, that is what they are describing as reinforcement learning. Both are valid terms for it.
It's how you can make an AI that plays Mario Kart. You establish goals that grant points, stuff to avoid that loses points, and what actions it can take each "step". Then you give it the first frame of a Mario Kart race, have it try literally every input it can put in that frame, then evaluate the change in points that results. You branch out from that collection of "frame 2s" and do the same thing again and again, checking more and more possible future states.
At some point you use certain rules to eliminate certain branches on this tree of potential future states, like discarding branches where it's driving backwards. That way you can start opptimizing towards the options at any given time that get the most points im the end. Keep the amount of options being evaluated to an amount you can push through your hardware.
Eventually you try enough things enough times that you can pretty consistently use the data you gathered to make the best choice on any given frame.
The jank comes from how the points are configured. Like AI for a delivery robot could prioritize jumping off balconies if it prioritizes speed over self preservation.
Some of these pitfalls are easy to create rules around for training. Others are far more subtle and difficult to work around.
Some people in the video game TAS community (custom building a frame by frame list of the inputs needed to beat a game as fast as possible, human limits be damned) are already using this in limited capacities to automate testing approaches to particularly challenging sections of gameplay.
So it ends up coming down to complexity. Making an AI to play Pacman is relatively simple. There are only 4 options every step, the direction the joystick is held. So you have 4^n^ states to keep track of, where n is the number of steps forward you want to look.
Trying to do that with language, and arguing that you can get reliable results with any kind of consistency, is blowing smoke. They can't even clearly state what outcomes they are optimizing for with their "reward" function. God only knows what edge cases they've overlooked.
My complete out of my ass guess is that they did some analysis on response to previous gpt output, tried to distinguish between positive and negative responses (or at least distinguish against responses indicating that it was incorrect). They then used that as some sort of positive/negative points heuristic.
People have been speculating for a while that you could do that, crank up the "randomness", have it generate multiple responses behind the scenes and then pit those "pre-responses" against each other and use that criteria to choose the best option of the "pre-responses". They could even A/B test the responses over multiple users, and use the user responses as further "positive/negative points" reinforcement to feed back into it in a giant loop.
Again, completely pulled from my ass. Take with a boulder of salt.
To be a little nitpicky most of the AI that can play Mario kart are trained not with a reinforcement learning algorithm, but woth a genetic algorithm, which is a sort of different thing.
Reinforcement learning is rather like how you teach a child. Show them a bunch of good stuff, and show them a bunch of bad stuff, and tell them which is the good stuff and which is the bad stuff.
Genetic algorithms are where you just leave it alone, simulate the evolutionary process on an accelerated time scale, and let normal evolutionary processes take over. Much easier, and less processor intensive, plus you don't need huge corpuses of data. But it takes ages, and it also sometimes results in weird behaviors because evolution finds a solution you never thought of, or it finds a solution to a different problem to the one you were trying to get it to find a solution to.
... sometimes results in weird behaviors because evolution finds a solution you never thought of, or it finds a solution to a different problem to the one you were trying to get it to find a solution to.
Those outcomes seem especially beneficial.
But it takes ages, ...
Is this process something that distributed computing could be leveraged for, akin to SETI@home?
Again, completely pulled from my ass. Take with a boulder of salt.
You're under arrest. That's ass-salt.
Technophobes are trying to downplay this because "AI bad", but this is actually a pretty significant leap from GPT and we should all be keeping an eye on this, especially those who are acting like this is just more auto-predict. This is a completely different generation process than GPT which is just glorified auto-predict. It's the difference between learning a language by just reading a lot of books in that language, and learning a language by speaking with people in that language and adjusting based on their feedback until you are fluent.
If you thought AI comments flooding social media was already bad, it's soon going to get a lot harder to discern who is real, especially once people get access to a web-connected version of this model.
All signs point to this being a finetune of gpt4o with additional chain of thought steps before the final answer. It has exactly the same pitfalls as the existing model (9.11>9.8 tokenization error, failing simple riddles, being unable to assert that the user is wrong, etc.). It's still a transformer and it's still next token prediction. They hide the thought steps to mask this fact and to prevent others from benefiniting from all of the finetuning data they paid for.
It's weird how so many of these "technophobes" are IT professionals. Crazy that people would line up to go into a profession they so obviously hate and fear.
I've worked in tech for 20 years. Luddites are quite common in this field.
Read some history mate. The luddites weren't technophobes either. They hated the way that capitalism was reaping all the rewards of industrializion. They were all for technological advancement, they just wanted it to benefit everyone.
How much more time until they use the word “sentient”?
Until the bubble bursts
Is that even the goal? Do we want an AI that's self aware because I thought that basically the whole point was to have an intelligence without a mind.
We don't really want sapient AI because if we do that then we have to feel bad about putting it in robots and making them do boring jobs. Don't we basically want guildless servants, isn't that the point?
Yeah I was thinking more about it as marketing, than a real thing
For the servants bots, yes no sentience. For my in house AI assistant robot buddy/butler/nanny/driver - also yes no sentience.
I’m more concerned about them using the word “sapient.” My dog is sentient; it’s not a high bar to clear.
Not until it has senses, which it currently does not have.
It's a better prediction model. There's no reasoning because it's not understanding anything you're typing. We're not closer to general ai.
It may not be capable of truly understanding anything, but it sure seems to do a better job of it than the vast majority of people I talk to online. I might spend 45 minutes carefully typing out a message explaining my view, only for the other person to completely miss every point I made. With ChatGPT, though, I can speak in broken English, and it’ll repeat back the point I was trying to make much more clearly than I could ever have done myself.
I heard parrots are the pinnacle of conversation
I hate to say it bud, but the fact that you feel like you have more productive conversations with highly advanced autocomplete than you do with actual humans probably says more about you than it does about the current state of generative AI.
That's not what I said, though.
It's a (large) language model. It's good at language tasks. Helps to have hundreds of Gigs of written "knowledge" in ram. Differing success rates on how that knowledge is connected.
It's autocorrect so turbocharged, it can write math, and a full essay without constantly clicking the buttons on top of the iphone keyboard.
You want to keep a pizza together? Ah yes my amazing concepts of sticking stuff together tells me you should add 1/2 spoons of glue (preferably something strong like gorilla glue).
How to find enjoyment with rock? Ah, you can try making it as a pet, and having a pet rock. Having a pet brings many enjoyments such as walking it.
You want to keep a pizza together? Ah yes my amazing concepts of sticking stuff together tells me you should add 1/2 spoons of glue
That would be a good test to ask it that question and see if it comes up with a more coherent answer.
Thanks for illustrating my point.
This article from last year compares LLMs to techniques used by “psychics” (cold reading, etc).
https://softwarecrisis.dev/letters/llmentalist/
I think it’s a great analogy (and an interesting article).
OpenAI doesn't want you to know that though, they want their work to show progress so they get more investor money. It's pretty fucking disgusting and dangerous to call this tech any form of artificial intelligence. The homogeneous naming conventions to make this tech sound human is also dangerous and irresponsible.
It is literally artificial intelligence though. Just because chatGPT doesn't perform as a layperson imagined it would, it doesn't mean it's not AI. They just have an unrealistic expectation of what counts as AI along with the common misconception of AI and AGI being the same thing.
A chess playing robot uses artificial intelligence as well. It's a narrow AI, meaning it can do one thing really well but that doesn't translate to other things. AGI on the other hand stands for Artificial General Intelligence. Humans are an example of general intelligence meaning that we have the cognitive ability to perform well on several unrelated tasks.
Gave it a try just now. Pretty terrible result.
At the same time, o1 is not as capable as GPT-4o in a lot of areas. It doesn’t do as well on factual knowledge about the world. It also doesn’t have the ability to browse the web or process files and images. Still, the company believes it represents a brand-new class of capabilities. It was named o1 to indicate “resetting the counter back to 1.”
I think it’s more of a proof of concept then a fully functioning model at this point.
To be fair, I did ask it to fact check an article, so that was probably not the best first choice
Facts. A "reasoning AI" has problems with ... lemme check this again ... facts?
Find the comment about psychics, it's exactly the situation we are currently in.
I'd recommend everyone saying "it can't understand anything and can't think" to look at this example:
https://x.com/flowersslop/status/1834349905692824017
Try to solve it after seeing only the first image before you open the second and see o1's response.
Let me know if you got it before seeing the actual answer.
This example doesn't prove what you think it does. It shows pattern detection - something computers are inherently very well suited for - but it doesn't demonstrate "reasoning" in any meaningful way.
You should really look at the full CoT traces on the demos.
I think you think you know more than you actually know.
trained to answer more complex questions, faster than a human can.
I can answer math questions really really fast. Not correct though, but like REALLY fast!
I'm the same with any programming question as long as the answer is Hello World
I'm getting so tired of the pessimists who are against AI. Granted, I can reflect and see my own similar attitude towards Trump: no matter what, I would never vote for him considering his history and who he is as a person. But treating the next generation of technology feels different than that to me; AI is the future, it's the next revolution. Sure, there are several real issues to criticize and question (copyright, compensation, hallucination come to mind) but instead shit here on Lemmy just gets downvoted to hell with no explanation. I know this comment will get downvoted, but I just wish we could have a discussion about the future without shutting down every practical comment wanting to talk about it.
I'm kinda in the same boat but on the other side. I always try to argue with people about this. It gets me a lot of flak on pro AI posts but that won't stop me. I usually get very aggressive replies and sometimes some fucked up dm's too.
I'm against it because we are already seeing the consequences of this technology and it's only getting worse. By the time laws catch up it's gonna be too late and the damage will be done. For some technologies that's not always the worst. But we already saw how long it took for anyone to do anything about the Internet when it came out, and we are still trying to this day. This shit is growing so fast we will all feel the whiplash. Sites like Facebook are getting absolutely flooded with so much AI that they are becoming almost unusable. And that's before we even get into the shady shit people use AI for like making porn of people they know with the click of a button. I recently read an article about how bad deepfake porn is in South Korea (found the article. https://www.nytimes.com/2024/09/12/world/asia/south-korea-deepfake-videos.html). And in places like the US, where a lot of these companies are based, they are so slow to do anything about a problem it's going to be too late by the time they get to it.
But besides all the awful things happening because of AI, I do have one personal gripe with the whole ordeal. Why are we so quick to replace the things we enjoy with AI? When I get home from work I like to make music and practice pixel art (I'm not very good at either yet). I'd much rather have AI replace my job than my hobbies. I'm down for things that are useful, but too much of this just gives me a bad gut feeling. Like their trying to replace people and not their jobs.
This may be the future. But it sounds like a pretty dystopian future to me. You already can't believe everything you see on the Internet and this will only make it worse.
More and more advanced tools for automation are an important part of creating a post-scarcity future. If we can combine that with tearing down our current economic system - which inherently requires and thus has to manufacture scarcity - we can uplift our species in ways we can currently only imagine.
But this ain't it bud. If I ask you for water and you hand me a glass of warm piss, I'm not "against drinking water" for refusing to gulp it down.
This isn't AI. It isn't - meaningfully and usefully - any form of automation at all. A bunch of conmen slapped the letters "AI" on the side of their bottle of piss and you're drinking it down like it's grandma's peach tea.
The people calling out the fundamental flaws with these products aren't doing so because we hate the entire concept of automation, any more than someone exposing a snake-oil salesman hates medicine. What we hate is being lied to. The current state of this technology is bullshit and hype. It is not fit for human consumption (other than recreationally) and the money being pumped into it could be put to far better uses. OpenAI may have lofty goals, but they have utterly failed at achieving them, and right now any true desire to create AGI has been totally subsumed by the need to keep pumping out slightly better looking versions of the same polished turd in order to convince investors to keep paying for their staggeringly high hosting costs.
“We have noticed that this model hallucinates less,” Tworek says. But the problem still persists. “We can’t say we solved hallucinations.”
On one hand, yeah, AI hallucinations.
On the other hand, have you met people?
Can't wait to read about it telling someone to put glue on pizza.
This is smarter. Will tell you how to pump a Calzone full of glue.
And provide the logical reasoning behind it!