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This feels like it's a less shitposty and thoroughly expanded version of my "Uber for artisanal cheeses, but on the blockchain" theory that I had.
Our flagship application has seen continuous development since the mid to late 2000s, and it's loosely based on a codebase and product that is considerably older than that. While it has CRUD elements (any application that functions as a long-running service must), it has some fairly extensive components that actually do things with that data in terms of business automation. Those are the areas where all the existing LLM solutions tend to fall apart. Given that they're statistical engines, going farther from CRUD is a very bad thing.
I'm not sure if I can fully buy into this. It wasn't that we were surfacing implicit context, so much as writing it for a very enthusiastic intern developer with absolutely no sense of self preservation. If we didn't break tasks down to an absurd level of guardrails and hand-holding, it would try to make enormous, system wide changes without any kind of midpoint validation. Sometimes we'd see the reasoning say things like "I have made a large number of changes. I should run unit tests to verify that I am correct", and then it just... wouldn't do it. Any of the server developers could have finished the full task in the time it took us to make the tickets that allowed the LLM to do the job without going off the rails.
Yep, I've seen this too. I have to ask, where you using any of the terminal based tools for code development (i.e. Claude Code). I know you said you were using Gemini, so I am doubting it was actually Claude Code (although you can run Gemini within CC).
There is a lot of guardrailing and handholding built into to these tools. If I pass a full system design doc to Claude Code and explicitly instruct it to do TDD with unit tests etc., it will.
LLMs aren't beings, people, or minds. If you think of it as having intention and character flaws, you're going to get frustrated quickly. If you think of it is a very imperfect and probabilistic tool that outputs into non-deterministic solution spaces, you'll get less frustrated and probably think differently on how you prompt it.
I am an unrepentant AI bull. I'll admit that and let people judge whatever I write with that bias in mind. I only request the same from the bears. When I see sentiment like this, which literally chastises a matrix of numbers, I have to assume a non-neutral bias.
I disagree with you here.
Setting aside the deep philosophical questions about personhood (which threaten to derail any productive discussion), I claim that LLMs are minds - albeit minds that are simultaneously startlingly human and deeply alien. Or at minimum, they can be usefully modeled as minds, which for practical purposes amounts to the same thing. (I should note: this position doesn't commit me to "AI welfare" concerns, or to thinking LLMs deserve legal rights or protections, or to losing sleep over potential machine suffering. You can believe something is a mind without believing it has moral weight. I do, I'm an unabashed transhumanist chauvinist.)
More importantly, I think there's nothing wrong at all with modeling them as having "intention or character flaws." if you use a variety of models on a regular basis, like I do, I think that becomes quite clear.
They have distinct personalities and flavors. o3 was a bright autist with a tendency to go into ADHD hyperfocus that I found charming. GPT-4o was a sycophantic retard. 5 Thinking is o3 with the edges sanded down. Claude Sonnets are personable and pleasant, being one of the few models that I very occasionally talk to for the sake of it. Gemini 2.5 Pro was clinically depressed, 3 Pro is a high-functioning paranoid schizophrenic who thinks anything that happens after 2025 is a simulation. Kimi K2 was @DaseindustriesLtd 's best friend, which I noted even before he sang its praises, being one of the weirdest models out there, being ridiculously prone to hallucinations while still being sharp and writing in a distinctly non-mode-collapsed style that makes other models seem lobotomized by comparison. If I close my eyes, I can easily see it as a depressed vodka swilling Russian intellectual, despite being of Chinese origin.
If these aren't character flaws, I don't know what is. Obviously they're not human, but they have traits that are well-described by terms that are cross-applicable to us. They're good at different things, Claude and Kimi (and sometimes Gemini) write at a level that makes the others seem broken. That being said, almost every model these days is good enough at a wide-spectrum of tasks. Hyperfocusing on benchmarks is increasingly unnecessary. Though I suppose, if you've got a bunch of Erdos problems to solve, GPT 5.2 Thinking at maximum reasoning effort is your go to.
They're model weights. <-- This is a link.
That's literally, exactly, precisely what they are.
You can map your own preferred anthropomorphized traits to them all you want, but that's, at best, a metaphor or something. This is the same as when people say their car has a "personality." It's kind of fun, I'll grant you, but it's also plainly inaccurate.
This is correct. But it is correct because of training data, superparameters, and a whole host of very well defined ML concepts. It's not because of ... personalities.
They're model weights, and we're collections of atoms: bags of meat and miscellaneous chemicals. Both statements are technically correct. And yet... a tiger being made out of atoms doesn't make it any less capable of killing you. The problem with pure reductionism is that
it throws out exactly the information you need to make predictions at the level you actually care aboutcan be a cognitively and computationally intractable approach, even if it's more "technically correct". Too much of it can be as bad as too little.All models are false, some models are useful. That's a rationalist saw, but for good reason. What actually matters is whether a model constraints expectations, in other words, is it useful?
Gemini 2.5 Pro doesn't meet the DSM-5 or ICD-11 criteria for clinical depression. After all, it's hard for a model to demonstrate insomnia or reduced appetite. Yet the odd behaviors it regularly demonstrated are usefully described by that label.
If my friend let me drive his Lambo, and told me "be careful, she's fierce!", I'm going to drive more carefully than I would in a Fiat Pinto. That is still, to some degree, useful, but I think it's clear that anthromorphic analogies are more useful for LLMs, because they have more in common with us behavior-wise than any car (unless you're running Grok on your Tesla). They process language, they exhibit something that looks like reasoning, they have distinctive response patterns that persist across contexts.
This is true in the same way that human behavior is fully determined by neurotransmitter levels, synaptic weights, and neurological processes. But just as you can't predict whether someone will enjoy a particular movie by examining their brain with an electron microscope or a QCD-sim, you can't accurately predict an LLM's macroscopic behavior by staring at its training corpus and hyperparameters. No human can.
Nobody at Google intended for Gemini 2.5 Pro to be "neurotic" and "depressed" or to devolve into a spiral of self-flagellation when it fails at a task, nobody wanted Kimi to hallucinate as regularly as it does. These were emergent, macroscopic properties, there's no equivalent of a statistical scaling-law that lets you accurately predict log-loss for a given number of tokens in a corpus and a compute budget.
Training models is still as much an art as it is a science, particularly the post-training and personality tuning phrases (as explicitly done by Anthropic). You test your hypothesis iteratively, and adjust the dials as you go.
Anthropomorphism is a cognitive strategy. Like all cognitive strategies, it can be deployed appropriately or inappropriately. The question is not "is anthropomorphism ever valid?" but rather "when does anthropomorphic modeling produce accurate predictions?"
I maintain that, if applied judiciously, as I take pains to do, it's better than the alternative.
I always find these arguments sort of annoying because it really conflates what is actually going on in ML/AI systems with this weird pseudo-science fiction mystification. Yes Tiger's are made of atoms, but no you can't use atomic physics to describe tiger-behavior. With AI models, you can describe behavior directly in terms of the underlying code. The model weights are deterministic parameters that literally decide how the system behaves.
Also you've gotten reductionism vs abstractions completely backwards. Abstractions "throw out information". High-level models compress details to make systems easier to reason about. Also not every useful abstraction corresponds to a mind, subject, or being.
Some Thought Experiments:
LLMs don't have minds and they aren't conscious. They are parameterized conditional probability functions, that are finite-order Markovian models over token sequences. Nothing exists outside their context window. They don't persist across interactions, there is no endogenous memory, and no self-updating parameters during inference. They have personality like programing languages or compilers have personality, as a biased function of how they were built, and what they were trained on.
That's what I get for arguing at 3 am. I do know the difference.
See my latest reply to Toll for more.
They are more "conscious" than a rock. I do not know if they have qualia, but at least they contain conscious entities as sub-agents (humans).
Would you start objecting if someone were to say "China is becoming increasingly conscious of the risk posed by falling behind in the AI race against America"? Probably not. Are they actually conscious? Idk. The terminology is still helpful, and shorter than an exhaustive description of every person in China.
No, but the word "alive" is slightly more applicable here than it would be to a rock. Applying terms such as "alive" to a thermostat is a daft thing to do in practice, we have more useful frameworks: an engineer might use control theory, a home owner might only care about what the dials do in terms of the temperature in the toilet. Nobody gets anything useful out of arguing if it's living or dead.
Hold on there. You are claiming, in effect, to have solved the Hard Problem of consciousness. How exactly do you know that they're not conscious? Can you furnish a mechanistic model that demonstrates that humans made of atoms or meat are "conscious" in a way that an entity made of model weights can't be even in principle?
Entirely correct.
That is not mutually exclusive to anything I've said so far.
So once LLMs start having little green men inside them they will be as conscious as a corporation haha. Also a corporation itself is not more conscious than a rock, as the corporation cannot do anything without conscious agents acting for it. It has no agency on its own. If I create an LLC and then forget about it, does it think? does it have its own will? or does it just sit there on some ledger. If a rock has people carrying it around and performing tasks for it, has it suddenly gained consciousness?
Yeah not, but I also don't think China is actually conscious. We're all using that as linguistic shorthand for "Chinese Leadership" or "Chinese populations" This nation state idea itself lacks a mind. It is controlled by conscious agents (humans) but it itself lacks consciousness.
You are smuggling in the claim that I am claiming to solve the problem of consciousness. I'm not. I'm claiming that LLMs lack properties that any plausible theory of consciousness requires (Or realistically my own theory). I'm saying that system A lacks necessary conditions for property P, therefore A does not have P. I don't need to prove the full positive theory of P.
My basic theory(really a constraint) of conscious behavior:
I'm willing to entertain another plausible theory of consciousness if you have one you prefer. Or if you think you have an animal that we consider conscious that exists in a Markovian state.
Maybe I need to reread your opinion, but my understanding is that you are in the "LLMs are conscious/have minds" camp of thought. If you are then this is exclusive, because I am making the claim that these clearly not conscious tools are personified as having personalities due to human's innate social bias to attribute personality to things. But that doesn't actually make them conscious/mind-having. It's sort of like this video: Social bias towards consciousness
It is helpful to consider another analogue: the concept of being "alive". A rock is clearly not alive. A human is. So are microbes, but once we get to viruses and prions, the delineation between living and non-living becomes blurry.
Similarly, it is entirely possible that consciousness can be continuous. I'm not a pan-psychist, I think it's dumb to think that an atom or a rock has any degree of consciousness, but consider the difference between an awake and lucid human, one who is drunk, one who is anesthetized or in a coma, someone lobotomized, a fetus etc. We have little idea what the bare minimum is.
A rock is no more conscious for being held than it was before. I think it's fair to say that the rock+human system as a whole is conscious, but only as conscious as the human already was. Think about it, there already is a "rock" in every human: a collection of hydroxyapatite crystals and protein matrices that make up your bones. And yet your consciousness clearly does not lie in your bones. Removing your femur won't impact your cognition, though you'll have a rather bad limp.
Humans are already made up of non-sentient building blocks. Namely the neurons in your brain. I think we can both agree that a single neuron is not meaningfully conscious, but in aggregate?
And guess what? We can already almost perfectly model a single biological neuron in-silico.
https://www.quantamagazine.org/how-computationally-complex-is-a-single-neuron-20210902/
In principle, there's nothing preventing us from scaling up to a whole rat brain or even a human brain, all while using artificial neural nets. I am of course eliding the enormous engineering challenges involved, but it can clearly be done in principle and that's what counts.
(I'm aware that the architectures of an LLM and any biological brain are very different)
We have examples of sentient systems with no persistent state, and humans to boot. There are lesions that can make someone have complete anterograde amnesia. They can maintain a continuous but limited capacity short-term memory, but the standard process of encoding and storage to longterm memory fails.
They can remember the last ~10 minutes (context window) and details of their life so far (latent knowledge) but do not consolidate new memories and thus are no longer capable of "online" learning. I do not think it's controversial that such people are conscious, and I certainly think they are.
That demonstrates, at least to my satisfaction, an existence proof that online learning is not a strict necessity for consciousness.
Further, I do not think that using an external repository to maintain state is in any way disqualifying. Humans use external memory aids all the time, and we'll probably develop BCIs that can export and import arbitrary data. There is nothing privileged about storage inside the space of the skull, it's just highly convenient.
I have strong confidence that I'm conscious, and so are you and the typical human (because of biological and structural similarities). I am also very confident that rocks and atoms aren't. I am far more agnostic about LLMs. We simply do not know if they are or aren't conscious.
My objection is to your expression of strong confidence that they aren't conscious. As far as I can tell, the sensible thing to do is wait and watch for more conclusive evidence, assuming we ever get it.
I do not believe that my thoughts on the topic came up, at least in this thread. As above, I do not make strong claims that LLMs are conscious. I maintain uncertainty. I don't particularly think the question even matters, since I wouldn't treat them any differently even if they were. "Mind" is a very poorly defined term (and we're already talking about consciousness, which doesn't do so hot itself). I think that conceptualizing each instance of an LLM as being a mind is somewhat defensible, even if that's not a hill I particularly care to die on.
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