Apple just proved AI "reasoning" models like Claude, DeepSeek-R1, and o3-mini don't actually reason at all. They just memorize patterns really well.
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This has been known for years, this is the default assumption of how these models work.
You would have to prove that some kind of actual reasoning capacity has arisen as... some kind of emergent complexity phenomenon.... not the other way around.
Corpos have just marketed/gaslit us/themselves so hard that they apparently forgot this.
Define, "reasoning". For decades software developers have been writing code with conditionals. That's "reasoning."
LLMs are "reasoning"... They're just not doing human-like reasoning.
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Employers who are foaming at the mouth at the thought of replacing their workers with cheap AI:
🫢
Can’t really replace. At best, this tech will make employees more productive at the cost of the rainforests.
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In fact, simple computer programs do a great job of solving these puzzles...
Yes, this shit is very basic. Not at all "intelligent."
But reasoning about it is intelligent, and the point of this study is to determine the extent to which these models are reasoning or not. Which again, has nothing to do with emotions. And furthermore, my initial question about whether or not pattern following should automatically be disqualified as intelligence, as the person summarizing this study (and notably not the study itself) claims, is the real question here.
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But it still manages to fuck it up.
I've been experimenting with using Claude's Sonnet model in Copilot in agent mode for my job, and one of the things that's become abundantly clear is that it has certain types of behavior that are heavily represented in the model, so it assumes you want that behavior even if you explicitly tell it you don't.
Say you're working in a yarn workspaces project, and you instruct Copilot to build and test a new dashboard using an instruction file. You'll need to include explicit and repeated reminders all throughout the file to use yarn, not NPM, because even though yarn is very popular today, there are so many older examples of using NPM in its model that it's just going to assume that's what you actually want - thereby fucking up your codebase.
I've also had lots of cases where I tell it I don't want it to edit any code, just to analyze and explain something that's there and how to update it... and then I have to stop it from editing code anyway, because halfway through it forgot that I didn't want edits, just explanations.
To be fair, the world of JavaScript is such a clusterfuck... Can you really blame the LLM for needing constant reminders about the specifics of your project?
When a programming language has five hundred bazillion absolutely terrible ways of accomplishing a given thing—and endless absolutely awful code examples on the Internet to "learn from"—you're just asking for trouble. Not just from trying to get an LLM to produce what you want but also trying to get humans to do it.
This is why LLMs are so fucking good at writing rust and Python: There's only so many ways to do a thing and the larger community pretty much always uses the same solutions.
JavaScript? How can it even keep up? You're using yarn today but in a year you'll probably like, "fuuuuck this code is garbage... I need to convert this all to [new thing]."
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No, it shows how certain people misunderstand the meaning of the word.
You have called npcs in video games "AI" for a decade, yet you were never implying they were somehow intelligent. The whole argument is strangely inconsistent.
"Artificial" has several meanings.
One is:
not being, showing, or resembling sincere or spontaneous behavior : fake
AI in video games literally means "fake intelligence"
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This is why I say these articles are so similar to how right wing media covers issues about immigrants.
There's some weird media push to convince the left to hate AI. Think of all the headlines for these issues. There are so many similarities. They're taking jobs. They are a threat to our way of life. The headlines talk about how they will sexual assault your wife, your children, you. Threats to the environment. There's articles like this where they take something known as twist it to make it sound nefarious to keep the story alive and avoid decay of interest.
Then when they pass laws, we're all primed to accept them removing whatever it is that advantageous them and disadvantageous us.
Unlike fear-mongering from the right about immigrants, current iterations of AI development:
- literally consume the environment (they are using electricity and water)
- are taking jobs and siphoning money from the economy towards centralized corporate revenue streams that don't pay a fair share of taxes
- I don't know of headlines claiming they will sexually assault you, but many headlines note that they can be used as part of sophisticated catfishing scams, which they are
All of these things aren't scare tactics. They're often overblown and exaggerated for clicks, but the fundamental nature of the technology and corporate implementation of it indisputable.
Open-source AI can change the world for the better. Corporate-controlled AI in some limited cases will improve the world, but without reasonable regulations they will severely harm it first.
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Define reason.
Like humans? Of course not. They lack intent, awareness, and grounded meaning. They don’t “understand” problems, they generate token sequences.
as it is defined in the article
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Brother you better hope it does because even if emissions dropped to 0 tonight the planet wouldnt stop warming and it wouldn't stop what's coming for us.
If the situation gets dire, it's likely that the weather will be manipulated. Countries would then have to be convinced not to use this for military purposes.
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Define, "reasoning". For decades software developers have been writing code with conditionals. That's "reasoning."
LLMs are "reasoning"... They're just not doing human-like reasoning.
Howabout uh...
The ability to take a previously given set of knowledge, experiences and concepts, and combine or synthesize them in a consistent, non contradictory manner, to generate hitherto unrealized knowledge, or concepts, and then also be able to verify that those new knowledge and concepts are actually new, and actually valid, or at least be able to propose how one could test whether or not they are valid.
Arguably this is or involves meta-cognition, but that is what I would say... is the difference between what we typically think of as 'machine reasoning', and 'human reasoning'.
Now I will grant you that a large amount of humans essentially cannot do this, they suck at introspecting and maintaining logical consistency, that they are just told 'this is how things work', and they never question that untill decades later and their lives force them to address, or dismiss their own internally inconsisten beliefs.
But I would also say that this means they are bad at 'human reasoning'.
Basically, my definition of 'human reasoning' is perhaps more accurately described as 'critical thinking'.
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10^36 flops to be exact
That sounds really floppy.
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To be fair, the world of JavaScript is such a clusterfuck... Can you really blame the LLM for needing constant reminders about the specifics of your project?
When a programming language has five hundred bazillion absolutely terrible ways of accomplishing a given thing—and endless absolutely awful code examples on the Internet to "learn from"—you're just asking for trouble. Not just from trying to get an LLM to produce what you want but also trying to get humans to do it.
This is why LLMs are so fucking good at writing rust and Python: There's only so many ways to do a thing and the larger community pretty much always uses the same solutions.
JavaScript? How can it even keep up? You're using yarn today but in a year you'll probably like, "fuuuuck this code is garbage... I need to convert this all to [new thing]."
That's only part of the problem. Yes, JavaScript is a fragmented clusterfuck. Typescript is leagues better, but by no means perfect. Still, that doesn't explain why the LLM can't recall that I'm using Yarn while it's processing the instruction that specifically told it to use Yarn. Or why it tries to start editing code when I tell it not to. Those are still issues that aren't specific to the language.
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Just like me
python code for reversing the linked list.
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Apple is significantly behind and arrived late to the whole AI hype, so of course it's in their absolute best interest to keep showing how LLMs aren't special or amazingly revolutionary.
They're not wrong, but the motivation is also pretty clear.
“Late to the hype” is actually a good thing. Gen AI is a scam wrapped in idiocy wrapped in a joke. That Apple is slow to ape the idiocy of microsoft is just fine.
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Brother you better hope it does because even if emissions dropped to 0 tonight the planet wouldnt stop warming and it wouldn't stop what's coming for us.
If emissions dropped to 0 tonight, we would be substantially better off than if we maintain our current trajectory. Doomerism helps nobody.
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This is why I say these articles are so similar to how right wing media covers issues about immigrants.
Maybe the actual problem is people who equate computer programs with people.
Then when they pass laws, we’re all primed to accept them removing whatever it is that advantageous them and disadvantageous us.
You mean laws like this? jfc.
Literally what I'm talking about. They have been pushing anti AI propaganda to alienate the left from embracing it while the right embraces it. You have such a blind spot you this, you can't even see you're making my argument for me.
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No, it shows how certain people misunderstand the meaning of the word.
You have called npcs in video games "AI" for a decade, yet you were never implying they were somehow intelligent. The whole argument is strangely inconsistent.
Strangely inconsistent + smoke & mirrors = profit!
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But for something like solving a Towers of Hanoi puzzle, which is what this study is about, we're not looking for emotional judgements - we're trying to evaluate the logical reasoning capabilities. A sociopath would be equally capable of solving logic puzzles compared to a non-sociopath. In fact, simple computer programs do a great job of solving these puzzles, and they certainly have nothing like emotions. So I'm not sure that emotions have much relevance to the topic of AI or human reasoning and problem solving, at least not this particular aspect of it.
As for analogizing LLMs to sociopaths, I think that's a bit odd too. The reason why we (stereotypically) find sociopathy concerning is that a person has their own desires which, in combination with a disinterest in others' feelings, incentivizes them to be deceitful or harmful in some scenarios. But LLMs are largely designed specifically as servile, having no will or desires of their own. If people find it concerning that LLMs imitate emotions, then I think we're giving them far too much credit as sentient autonomous beings - and this is coming from someone who thinks they think in the same way we do! The think like we do, IMO, but they lack a lot of the other subsystems that are necessary for an entity to function in a way that can be considered as autonomous/having free will/desires of its own choosing, etc.
In fact, simple computer programs do a great job of solving these puzzles.....
If an AI is trained to do this, it will be very good, like for example when a GPT-2 was trained to multiply numbers up to 20 digits.
https://nitter.net/yuntiandeng/status/1836114419480166585#m
Here they do the same test to GPT-4o, o1-mini and o3-mini
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Why would they "prove" something that's completely obvious?
The burden of proof is on the grifters who have overwhelmingly been making false claims and distorting language for decades.
Not when large swaths of people are being told to use it everyday. Upper management has bought in on it.
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LOOK MAA I AM ON FRONT PAGE
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LOOK MAA I AM ON FRONT PAGE
Yah of course they do they’re computers
