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.

I mean… “proving” is also just marketing speak. There is no clear definition of reasoning, so there’s also no way to prove or disprove that something/someone reasons.

That entire paragraph is much better at supporting the precise opposite argument. Computers can beat Kasparov at chess, but they're clearly not thinking when making a move - even if we use the most open biological definitions for thinking.

I'm going to write a program to play tic-tac-toe. If y'all don't think it's "AI", then you're just haters. Nothing will ever be good enough for y'all. You want scientific evidence of intelligence?!?! I can't even define intelligence so take that! \s

Seriously tho. This person is arguing that a checkers program is "AI". It kinda demonstrates the loooong history of this grift.

Yesterday I asked an LLM "how much energy is stored in a grand piano?" It responded with saying there is no energy stored in a grad piano because it doesn't have a battery.

Any reasoning human would have understood that question to be referring to the tension in the strings.

Another example is asking "does lime cause kidney stones?". It didn't assume I mean lime the mineral and went with lime the citrus fruit instead.

Once again a reasoning human would assume the question is about the mineral.

Ask these questions again in a slightly different way and you might get a correct answer, but it won't be because the LLM was thinking.

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.

https://www.inc.com/sam-blum/trumps-budget-would-ban-states-from-regulating-ai-for-10-years-why-that-could-be-a-problem-for-everyday-americans/91198975

Because it's a fear-mongering angle that still sells. AI has been a vehicle for scifi for so long that trying to convince Boomers that of won't kill us all is the hard part.

I'm a moderate user for code and skeptic of LLM abilities, but 5 years from now when we are leveraging ML models for groundbreaking science and haven't been nuked by SkyNet, all of this will look quaint and silly.

I'm not trained or paid to reason, I am trained and paid to follow established corporate procedures. On rare occasions my input is sought to improve those procedures, but the vast majority of my time is spent executing tasks governed by a body of (not quite complete, sometimes conflicting) procedural instructions.

If AI can execute those procedures as well as, or better than, human employees, I doubt employers will care if it is reasoning or not.

Particularly to counter some more baseless marketing assertions about the nature of the technology.

Lots of us who has done some time in search and relevancy early on knew ML was always largely breathless overhyped marketing. It was endless buzzwords and misframing from the start, but it raised our salaries. Anything that exec doesnt understand is profitable and worth doing.

If you want to boil down human reasoning to pattern recognition, the sheer amount of stimuli and associations built off of that input absolutely dwarfs anything an LLM will ever be able to handle. It's like comparing PhD reasoning to a dog's reasoning.

While a dog can learn some interesting tricks and the smartest dogs can solve simple novel problems, there are hard limits. They simply lack a strong metacognition and the ability to make simple logical inferences (eg: why they fail at the shell game).

Now we make that chasm even larger by cutting the stimuli to a fixed token limit. An LLM can do some clever tricks within that limit, but it's designed to do exactly those tricks and nothing more. To get anything resembling human ability you would have to design something to match human complexity, and we don't have the tech to make a synthetic human.

I think as we approach the uncanny valley of machine intelligence, it's no longer a cute cartoon but a menacing creepy not-quite imitation of ourselves.

Sure, these grifters are shady AF about their wacky definition of "reason"... But that's just a continuation of the entire "AI" grift.

I'd encourage you to research more about this space and learn more.

As it is, the statement "Markov chains are still the basis of inference" doesn't make sense, because markov chains are a separate thing. You might be thinking of Markov decision processes, which is used in training RL agents, but that's also unrelated because these models are not RL agents, they're supervised learning agents. And even if they were RL agents, the MDP describes the training environment, not the model itself, so it's not really used for inference.

I mean this just as an invitation to learn more, and not pushback for raising concerns. Many in the research community would be more than happy to welcome you into it. The world needs more people who are skeptical of AI doing research in this field.

You had a compelling description of how ML models work and just had to swerve into politics, huh?

They want something like the Star Trek computer or one of Tony Stark's AIs that were basically deus ex machinas for solving some hard problem behind the scenes. Then it can say "model solved" or they can show a test simulation where the ship doesn't explode (or sometimes a test where it only has an 85% chance of exploding when it used to be 100%, at which point human intuition comes in and saves the day by suddenly being better than the AI again and threads that 15% needle or maybe abducts the captain to go have lizard babies with).

AIs that are smarter than us but for some reason don't replace or even really join us (Vision being an exception to the 2nd, and Ultron trying to be an exception to the 1st).

Yeah I often think about this Rick N Morty cartoon. Grifters are like, "We made an AI ankle!!!" And I'm like, "That's not actually something that people with busted ankles want. They just want to walk. No need for a sentient ankle." It's a real gross distortion of science how everything needs to be "AI" nowadays.

I think it's an easy mistake to confuse sentience and intelligence. It happens in Hollywood all the time - "Skynet began learning at a geometric rate, on July 23 2004 it became self-aware" yadda yadda

But that's not how sentience works. We don't have to be as intelligent as Skynet supposedly was in order to be sentient. We don't start our lives as unthinking robots, and then one day - once we've finally got a handle on calculus or a deep enough understanding of the causes of the fall of the Roman empire - we suddenly blink into consciousness. On the contrary, even the stupidest humans are accepted as being sentient. Even a young child, not yet able to walk or do anything more than vomit on their parents' new sofa, is considered as a conscious individual.

So there is no reason to think that AI - whenever it should be achieved, if ever - will be conscious any more than the dumb computers that precede it.

The only reason we're not there yet is memory limitations.

Eventually some company will come out with AI hardware that lets you link up a petabyte of ultra fast memory to chips that contain a million parallel matrix math processors. Then we'll have an entirely new problem: AI that trains itself incorrectly too quickly.

Just you watch: The next big breakthrough in AI tech will come around 2032-2035 (when the hardware is available) and everyone will be bitching that "chain reasoning" (or whatever the term turns out to be) isn't as smart as everyone thinks it is.

LLMs (at least in their current form) are proper neural networks.

Reasoning is limited

Most people wouldn't call zero of something 'limited'.

I'm not convinced that humans don't reason in a similar fashion. When I'm asked to produce pointless bullshit at work my brain puts in a similar level of reasoning to an LLM.

Think about "normal" programming: An experienced developer (that's self-trained on dozens of enterprise code bases) doesn't have to think much at all about 90% of what they're coding. It's all bog standard bullshit so they end up copying and pasting from previous work, Stack Overflow, etc because it's nothing special.

The remaining 10% is "the hard stuff". They have to read documentation, search the Internet, and then—after all that effort to avoid having to think—they sigh and start actually start thinking in order to program the thing they need.

LLMs go through similar motions behind the scenes! Probably because they were created by software developers but they still fail at that last 90%: The stuff that requires actual thinking.

Eventually someone is going to figure out how to auto-generate LoRAs based on test cases combined with trial and error that then get used by the AI model to improve itself and that is when people are going to be like, "Oh shit! Maybe AGI really is imminent!" But again, they'll be wrong.

AGI won't happen until AI models get good at retraining themselves with something better than basic reinforcement learning. In order for that to happen you need the working memory of the model to be nearly as big as the hardware that was used to train it. That, and loads and loads of spare matrix math processors ready to go for handing that retraining.

previous input goes in. Completely static, prebuilt model processes it and comes up with a probability distribution.

There is no "unlike markov chains". They are markov chains. Ones with a long context (a markov chain also kakes use of all the context provided to it, so I don't know what you're on about there). LLMs are just a (very) lossy compression scheme for the state transition table. Computed once, applied blindly to any context fed in.

...... So you're saying there's a chance?

as it is defined in the article

The sticky wicket is the proof that humans (functioning 'normally') do more than pattern.

I understand that people in this "field" regularly use pseudo-scientific language (I actually deleted that part of my comment).

But the terminology has never been suitable so it shouldn't be used in the first place. It pre-supposes the hypothesis that they're supposedly "disproving". They're feeding into the grift because that's what the field is. That's how they all get paid the big bucks.

Yep. I'm retired now, but before retirement a month or so ago, I was working on a project that relied on several hundred people back in 2020. "Why can't AI do it?"

The people I worked with are continuing the research and putting it up against the human coders, but...there was definitely an element of "AI can do that, we won't need people" next time. I sincerely hope management listens to reason. Our decisions would lead to potentially firing people, so I think we were able to push back on the "AI can make all of these decisions"...for now.

The AI people were all in, they were ready to build an interface that told the human what the AI would recommend for each item. Errrm, no, that's not how an independent test works. We had to reel them back in.

No. They don't. We just call them proteins.

I don't mean it to extol LLM's but rather to denigrate humans. How many of us are self imprisoned in echo chambers so we can have our feelings validated to avoid the uncomfortable feeling of thinking critically and perhaps changing viewpoints?

Humans have the ability to actually think, unlike LLM's. But it's frightening how far we'll go to make sure we don't.

I've heard something along the lines of, "it's not when computers can pass the Turing Test, it's when they start failing it on purpose that's the real problem."

I think that person had to choose between the drugs or hard core prison of the 1950s England where being a bit odd was enough to guarantee an incredibly difficult time as they say in England, I would've chosen the drugs as well hoping they would fix me, too bad without testosterone you're going to be suicidal and depressed, I'd rather choose to keep my hair than to be horny all the time

Yeah we’re so stupid we’ve figured out advanced maths, physics, built incredible skyscrapers and the LHC, we may as individuals be less or more intelligent but humans as a whole are incredibly intelligent

Apple Intelligence

It's a very resource intensive autocomplete

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'.

Yes but asshole employers haven’t realized this yet

... And so we should call machines "intelligent"? That's not how science works.

Their argument is that we don't understand human intelligence so we should call computers intelligent.

That's not hitting any nail on the head.

Sorry, I can see why my original post was confusing, but I think you've misunderstood me. I'm not claiming that I know the way humans reason. In fact you and I are on total agreement that it is unscientific to assume hypotheses without evidence. This is exactly what I am saying is the mistake in the statement "AI doesn't actually reason, it just follows patterns". That is unscientific if we don't know whether or "actually reasoning" consists of following patterns, or something else. As far as I know, the jury is out on the fundamental nature of how human reasoning works. It's my personal, subjective feeling that human reasoning works by following patterns. But I'm not saying "AI does actually reason like humans because it follows patterns like we do". Again, I see how what I said could have come off that way. What I mean more precisely is:

It's not clear whether AI's pattern-following techniques are the same as human reasoning, because we aren't clear on how human reasoning works. My intuition tells me that humans doing pattern following seems equally as valid of an initial guess as humans not doing pattern following, so shouldn't we have studies to back up the direction we lean in one way or the other?

I think you and I are in agreement, we're upholding the same principle but in different directions.

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.

That just means they'd be great CEOs!

According to Wall Street.

TBH idk how people can convince themselves otherwise.

They don’t convince themselves. They’re convinced by the multi billion dollar corporations pouring unholy amounts of money into not only the development of AI, but its marketing. Marketing designed to not only convince them that AI is something it’s not, but also that that anyone who says otherwise (like you) are just luddites who are going to be “left behind”.

I think because it's language.

There's a famous quote from Charles Babbage when he presented his difference engine (gear based calculator) and someone asking "if you put in the wrong figures, will the correct ones be output" and Babbage not understanding how someone can so thoroughly misunderstand that the machine is, just a machine.

People are people, the main thing that's changed since the Cuneiform copper customer complaint is our materials science and networking ability. Most things that people interact with every day, most people just assume work like it appears to on the surface.

And nothing other than a person can do math problems or talk back to you. So people assume that means intelligence.

They aren't bullshitting because the training data is based on reality. Reality bleeds through the training data into the model. The model is a reflection of reality.

That indicates that this particular model does not follow instructions, not that it is architecturally fundamentally incapable.

Dude they made chat gpt a little more boit licky and now many people are convinced they are literal messiahs. All it took for them was a chat bot and a few hours of talk.

Funny how triggering it is for some people when anyone acknowledges humans are just evolved primates doing the same pattern matching.

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.

I find it hilarious that the only people these LLMs mimic are the incompetent ones. I had a coworker that changed things when asked to explain constantly.

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]."

Like what?

I don’t think there’s any search engine better than Perplexity. And for scientific research Consensus is miles ahead.

Hallucinations and the cost of running the models.

So, inaccurate information in books is nothing new. Agreed that the rate of hallucinations needs to decline, a lot, but there has always been a need for a veracity filter - just because it comes from "a book" or "the TV" has never been an indication of absolute truth, even though many people stop there and assume it is. In other words: blind trust is not a new problem.

The cost of running the models is an interesting one - how does it compare with publication on paper to ship globally to store in environmentally controlled libraries which require individuals to physically travel to/from the libraries to access the information? What's the price of the resulting increased ignorance of the general population due to the high cost of information access?

What good is a bunch of knowledge stuck behind a search engine when people don't know how to access it, or access it efficiently?

Granted, search engines already take us 95% (IMO) of the way from paper libraries to what AI is almost succeeding in being today, but ease of access of information has tremendous value - and developing ways to easily access the information available on the internet is a very valuable endeavor.

Personally, I feel more emphasis should be put on establishing the veracity of the information before we go making all the garbage easier to find.

I also worry that "easy access" to automated interpretation services is going to lead to a bunch of information encoded in languages that most people don't know because they're dependent on machines to do the translation for them. As an example: shiny new computer language comes out but software developer is too lazy to learn it, developer uses AI to write code in the new language instead...

LLMs don't know how how they work