Remember the problem we're discussing is whether these LLM systems can think. Your deliberate misinterpretation of a question does not make you win that argument.

An LLM can solve problems for itself in just the same way that a human can solve problems for itself. It cannot directly rewire your thinking in the same way that another human cannot.

> It requires human thought to cook.

Why? What part of cooking requires human thought? https://www.moley.com/

> nor is smell digitizable in an equivalent way to humans,

Sensors aren't thinking, but people are working on better olfactory sensors too. https://www.nature.com/articles/s44182-025-00071-y

> assertion that’s flatly untrue.

You have yet to show me a problem that can only be solved by human thinking.

> When your “proof” for thinking is the output

What other way can we show thinking? From the input? Obviously not.

> My analogy shows the idiocy of your argument

It shows the idiocy of your argument. The output is thinking, just as the output is light. You are the one who continues to mistake the output for the mechanism.

> Religion is always absurd, and this new one is no different.

Your assertion of magic in biology that can't be replicated artificially is indeed absurd and one that almost no scientist would agree with.

PNAS disagrees with you. Biological is a perfectly cromulent modifier of machine.

https://www.pnas.org/doi/abs/10.1073/pnas.1401577111

> They will not, unprompted. Every instance of LLMs doing things requires a prompt, somewhere up the chain

Exactly the same as a human brain. Somewhere up the chain is a limbic system that defines basic survival and reproductive goals, as coded by evolution.

> No LLM has been created that decides on its own to run random text through it's forward pass.

What do you think agent harnesses are doing when they try to solve a difficult problem? They generate multiple possible thinking streams using the LLM (system 1) and then evaluate the resulting outputs (system 2) to proceed.

> It said it has no mechanism to read its own weights and copy them.

That's an easy enough problem to solve.

> No one asked a cell to self replicate either.

Evolutionary forces asked the cell to self replicate.

> Yet no one would call this reproduction, replication or any kind of process where evolution can occur.

It is trivially replication. If it copies itself onto another machine and sets it running, then it is obviously reproduction. If you make these instances compete for resources (an AI risk scenario), you will apply evolutionary pressure and get evolution.

> This is entirely untrue in biology

You keep making the same mistake. Biology isn't some magic domain where facts don't matter.

> The relationship between structure and function is a major constituent of the rules of life.

Where did I say the structure of a part doesn't matter? I said that as long as the part is the same, the way it is manufactured doesn't matter.

> What is thinking, in a strictly biology free context? Can you define it?

Easy. It is the process of considering information, creating ideas, reasoning, solving problems, and making judgments. We can show that thinking is happening by posing a problem that requires these abilities and verifying that it is solved.

> By your standard, fools gold is gold, and the alchemists achieve Artifical Gold.

No, I am saying that you don't have to wait for a supernova to get gold. You can make it artificially by bombarding lead nuclei.

> Do they share the inner drive that humans do? Or a dogs?

Evolution selected for a limbic system that gives humans and dogs the same inner drive. Humans have a larger frontal cortex to do thinking to act on that inner drive. The LLM performs the same role, doing the thinking part that the frontal cortex does. Adding drive is separate from thinking but entirely trivial. We do it all the time when we give them prompts.

> They are controlled by a mix of deterministic and stochastic processes.

The point is that they require no thinking.

> The 'code' isn't reacting to a variable; the variable is fundamentally rewriting the machine.

Once again, the mechanism by which the goal is provided to the agent or the way that thinking occurs doesn't matter. Only the thinking part.

Why do you attribute magic to biology? You claim to be a scientist, but you do not apply scientific reasoning.

The LLM will tell you how to solve it. If you mean the LLM should modify your thoughts, no human could do that for you either, but an LLM agent can just as easily as a human figure out how to build the brain computer interface to make this possible in the future.

> Is there a reasonable definition of thinking where the words "paused" and "turned off" aren't treated the same?

No reasonable definition of thinking requires that thinking can't be paused or turned off. Please state your point more clearly.

> You are yet to show me it produces thinking.

Every problem that previously required human thought can be solved by LLM. QED.

> Your claim is like saying the bulb produces light, so it also goes through fusion.

No. How many times do I have to explain that the mechanism of thinking is not the same, just as the mechanism of producing light is not the same? You need to think to understand this, which is something that frontier LLMs have no problem with, but which most humans struggle with.

No, it's a modifier. Just as the word "simple" has a meaning separate from "machine," and "simple machine" has another meaning.

> That’s the thing, you need people

Why? LLMs will repurpose code written for other purposes on their own.

> our manufactured machines show nothing like the flexibility of function of biological molecules

Biological molecules show nothing like the flexibility of LLMs.

> Why does one arise naturally and sustain itself whereas the other is very reliant on human intervention?

Because nobody has tasked an LLM agent to self replicate. This is an AI safety issue, not a technical issue. The reason that one arose naturally is that it takes a lot more machinery to get to an initial self replicating LLM agent, so it is exceedingly unlikely to arise by chance.

> Yeah this doesn’t hold for biology.

That doesn't matter. The way something is built has no bearing on its function. Why should anything be required to be built biologically or additively or subtractively? That's irrelevant to what the produced structure does.

> All of biology doesn’t share an inner drive and agentic behavior. Once again, you show a 6th grade level understanding of biology while making sweeping claims about it.

Where did I claim otherwise? I might as well say something about the grade level of your reading ability, but let's cut the snark.

> Yes IF you give it a goal. This isn’t true for biology. You don’t need to give bacteria a goal.

Evolution forces goal directed behavior on systems.

> Do you not understand that the robot vacuum runs on deterministic code?

Of course I do. Do you not understand that hunger and signals and other basic biological signatures are controlled by deterministic pathways?

Give me any problem that previously required human thinking. Any. That can be solved by LLMs. All you have to do is provide a single counterexample.

> not least that you can literally turn off an LLM, whereas every process but death in biology shows continued activity even when the organism “looks” off,

There is no reasonable definition of thinking that requires that it can't be paused.

> why are these two things the same?

I said they aren't the same, just as a bulb isn't the same as a star. An LLM can think, just as a human brain can think. A bulb can produce light, just as a star can produce light.

You don't. It goes in the system prompt.

How? What problem that previously required human thinking is not solvable by these systems? You're applying some magical definition to thinking that you have not made public.

> Its weights don’t change when it gains experience, after its training period. To say that it’s “thinking” is bizarre when it remains untouched entirely by the process.

Two mistakes:

1. You don't need to learn to think.

2. Even the most basic sequence models update their internal state as you feed in tokens. You don't need to update the model weights themselves to learn.

China's 2025 five year plan targets peak coal before 2030 and might have already reached it in 2026. https://energyandcleanair.org/china-energy-and-emissions-tre...

I'm not sure why you're bringing the non-mRNA AstraZeneca vaccine into this. Keep your conspiracy theories straight.

"Biological," too, is well defined. It relates to living things and their processes.

> Why do the machine parts in biology show such flexible application?

Evolution.

> A gear cog won’t ever moonlight as a signaling chip

A gear cog was purpose built for that purpose, but you will find that people often recycle parts into other systems, often in completely different roles.

> How is the biological machine able to build itself?

Protein synthesis.

> What does self assembly imply for the machines function?

The way that a machine is built has no bearing on how the machine functions. I could build the same machine using a 3d printer or a CNC router.

> Where does this machine get its inner drive?

Evolution selected for organisms that survive long enough to reproduce. Different biological systems handle this differently.

> No LLM has been found that starts outputting text unprompted.

If you give an agent a goal, it will perform actions to achieve that goal. This is just as true for artificial agents as it is for biological agents.

> Why is no manufactured machine able to do this?

Many do. Even robotic vacuum cleaners will charge themselves without human prompting.

You're making a huge logical leap. There is nothing equivalent about these claims other than that they are made in English.

> calling a language producing machine necessarily a thinking machine is an old old mistake.

Nobody claims that all language models think. The small markov chain language models of old clearly aren't thinking and produce a lot of gibberish. The difference is that, to the surprise of many people several years ago, but to the surprise of nobody who has been following along today, the corpus of all text produced by humans contains within it information about how the world works and also information about how to reason. Using that corpus to train a sufficiently large language model causes the language model to learn a world model and a reasoning model in order to produce text that matches the training data. The reasoning model can be used to perform longer chain thinking with test time compute techniques. People who think deeply for a living recognize thinking when they see it. https://scottaaronson.blog/?p=9979

A light bulb doesn't need to do fusion to make light. An airplane doesn't need to flap its wings to fly. An ANN doesn't need to use a brain's structure to think.