this post was submitted on 12 Sep 2024
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For OpenAI, o1 represents a step toward its broader goal of human-like artificial intelligence. More practically, it does a better job at writing code and solving multistep problems than previous models. But it’s also more expensive and slower to use than GPT-4o. OpenAI is calling this release of o1 a “preview” to emphasize how nascent it is.

The training behind o1 is fundamentally different from its predecessors, OpenAI’s research lead, Jerry Tworek, tells me, though the company is being vague about the exact details. He says o1 “has been trained using a completely new optimization algorithm and a new training dataset specifically tailored for it.”

OpenAI taught previous GPT models to mimic patterns from its training data. With o1, it trained the model to solve problems on its own using a technique known as reinforcement learning, which teaches the system through rewards and penalties. It then uses a “chain of thought” to process queries, similarly to how humans process problems by going through them step-by-step.

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 this is the most important part (emphasis mine):

As a result of this new training methodology, OpenAI says the model should be more accurate. “We have noticed that this model hallucinates less,” Tworek says. But the problem still persists. “We can’t say we solved hallucinations.”

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[–] [email protected] 140 points 6 months ago (5 children)

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.

[–] [email protected] 48 points 6 months ago

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).

[–] [email protected] 28 points 6 months ago (2 children)

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.

[–] [email protected] 14 points 6 months ago (4 children)

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.

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[–] [email protected] 8 points 6 months ago (1 children)

Their work is making progress. What is irresponsible or dangerous? Im not understanding what you mean.

[–] [email protected] 9 points 6 months ago* (last edited 6 months ago) (9 children)

It's irresponsible because making it sound like it's true AI when it's not is going to make it difficult to pull the plug when things go wrong and you'll have the debate of whether it's sentient or not and if it's humane to kill it like a pet or a criminal. It's more akin to using rainbow tables to help crack passwords and claiming your software is super powerful when in reality it's nothing without the tables. (Very very rudimentary example that's not supposed to be taken at face value).

It's dangerous because talking about AI like it's a reasoning/thinking thing is just not true, and we're already seeing the big AI overlords try to justify how they created it with copyrighted material, which means the arguments over copyrighted material are being made and we'll soon see those companies claim that it's no different than a child looking up something on Google. It's irresponsible because it screws over creative people and copyright holders that genuinely made a product or piece of art or book or something in their own free time and now it's been ripped away to be used to create something else that will eventually push those copyright holders out.

The AI market is moving faster than the world is capable of keeping up with it, and that is a dangerous precedent to set for the future of this market. And for the record I don't think we're dealing with early generations of skynet or anything like that, we're dealing with tools that have the capability to create economical collapse on a scale we've never seen, and if we don't lay the ground rules now, then we will be in trouble.

Edit: A great example of this is https://v0.dev/chat it has the potential to put front end developers out of work and jobless. It's simple now but give it time and it has the potential to create a frontend that rivals the best UX designs if the prompt is right.

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[–] [email protected] 26 points 6 months ago (4 children)

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.

[–] [email protected] 22 points 6 months ago

I heard parrots are the pinnacle of conversation

[–] [email protected] 14 points 6 months ago (3 children)

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.

[–] [email protected] 8 points 6 months ago

That's not what I said, though.

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[–] [email protected] 9 points 6 months ago (1 children)

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.

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[–] [email protected] 24 points 6 months ago (1 children)

I wish more people would realize this! We’re years away from a truly reasoning computer.

Right now it’s all mimicry. Mimicry that hallucinates no less…

[–] [email protected] 20 points 6 months ago

I think most people do understand this and the naysayers get too caught up on the words being used, like how you still get people frothing over the mouth over the use of the word "intelligence" years after this has entered mainstream conversation. Most people using that word don't literally think ChatGPT is a new form of intelligent life.

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[–] [email protected] 73 points 6 months ago (3 children)

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!

[–] [email protected] 29 points 6 months ago (1 children)

It scores 83% on a qualifying exam for the international mathematics olympiad compared to the previous model's 13% so...

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[–] [email protected] 38 points 6 months ago (1 children)

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.

[–] [email protected] 32 points 6 months ago (2 children)

Again, completely pulled from my ass. Take with a boulder of salt.

You're under arrest. That's ass-salt.

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[–] [email protected] 30 points 6 months ago (1 children)

Can't wait to read about it telling someone to put glue on pizza.

[–] [email protected] 15 points 6 months ago (2 children)

This is smarter. Will tell you how to pump a Calzone full of glue.

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[–] [email protected] 28 points 6 months ago (3 children)

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.

[–] [email protected] 31 points 6 months ago* (last edited 6 months ago) (1 children)

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 benefiting from all of the finetuning data they paid for.

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[–] [email protected] 13 points 6 months ago (1 children)

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.

[–] [email protected] 8 points 6 months ago (1 children)

I've worked in tech for 20 years. Luddites are quite common in this field.

[–] [email protected] 9 points 6 months ago (1 children)

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.

[–] [email protected] 7 points 6 months ago

I'm using the current-day usage of the term, but I think you knew that.

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[–] [email protected] 27 points 6 months ago (2 children)

So they slapped some reinforcement learning on top of their LLM and are claiming that gives it “reasoning capabilities”? Or am I missing something?

[–] [email protected] 16 points 6 months ago

It's like 3 lms on top of eachother in a trenchcoat, and appau a calculator so it gets math right

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[–] [email protected] 25 points 6 months ago (4 children)

How much more time until they use the word “sentient”?

[–] [email protected] 17 points 6 months ago

Until the bubble bursts

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[–] [email protected] 24 points 6 months ago (1 children)

“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?

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[–] [email protected] 21 points 6 months ago (1 children)

Lol Lemmy has the funniest ai haters they drown out any real criticism with stupid strawman nonsense

[–] Zos_Kia 11 points 6 months ago (2 children)
  • it's not actually AI
  • it's just fancy auto complete/ glorified Markov chains
  • it can't reason it's just a pLagIaRisM MaChiNe

Now if I want to win the annoying Lemmy bingo I just need to shill extra hard for more restrictive copyright law!

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[–] [email protected] 19 points 6 months ago (1 children)

That's not what reasoning is. Training is understanding what they're talking about and being able to draw logical conclusions based on what they've learned. It's being able to say, I didn't know but wait a second and I'll look it up," and then summing that info up in original language.

All Open AI did was make it less stupid and slap a new coat of paint on it, hoping nobody asks too many questions.

[–] [email protected] 8 points 6 months ago

And this is something data scientists have already been doing with existing LLMs.

[–] [email protected] 17 points 6 months ago (3 children)

I just love how people seem to want to avoid using the word lie.

It’s either misinformation, or alternative facts, or hallucinations.

Granted, a lie does tend to have intent behind it, so with ChatGPT, it’s probably better to say falsehood, instead. But either way, it’s not fact, it’s not truth, and people, especially schools, should stop using it as a credible source.

[–] [email protected] 20 points 6 months ago* (last edited 6 months ago) (1 children)

Being wrong is not the same as lying. When LLMs start giving wrong answers on purpose to mislead people we would have a big problem.

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[–] [email protected] 8 points 6 months ago

There was a recent paper that argues 'bullshitting' is the most apt analogy. I.e. telling something to satisfy the other person without caring about the truth content of what you say

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[–] [email protected] 15 points 6 months ago* (last edited 6 months ago) (3 children)

Dang, OpenAI just pulled an Apple. Do something other people have already done with the same results (but importantly before they made a big fuss about it), claim it's their innovation, give it a bloated name so people imagine it's more than it is and produce a graph comparing themselves to themselves, hoping nobody will look at the competition.

Just like Apple, they have their own selling point, but instead they seem to prefer making up stuff while forgetting why people use em.

On a side note they also pulled an Elon. Where's my AI companion that can comment on video in realtime and sing to me??? Ya had it "working" "live" a couple months ago, WHERE IS IT?!?

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[–] [email protected] 14 points 6 months ago (3 children)

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.

[–] [email protected] 8 points 6 months ago* (last edited 6 months ago)

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.

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[–] [email protected] 12 points 6 months ago (1 children)

I think I've used it if this is the latest available, and it's terrible. It keeps feeding me wrong information, and when you correct it, it says you're right... But if you ask it again, it again feeds you the wrong information.

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[–] [email protected] 11 points 6 months ago

Reinforcement learning my beloved ❤️

[–] [email protected] 8 points 6 months ago (2 children)

Gave it a try just now. Pretty terrible result.

[–] [email protected] 9 points 6 months ago (3 children)

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.

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[–] [email protected] 8 points 6 months ago* (last edited 6 months ago) (1 children)

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.

[–] [email protected] 18 points 6 months ago (1 children)

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.

[–] [email protected] 8 points 6 months ago (4 children)

You should really look at the full CoT traces on the demos.

I think you think you know more than you actually know.

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[–] [email protected] 7 points 6 months ago

Interesting, thanks for sharing.

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