[agentultra]

This is the worst possible take. It dismisses an entire branch of science that has been studying neurology for decades. Biological brains exist, we study them, and no they are not like computers at all.

There have been charlatans repeating this idea of a “computational interpretation,” of biological processes since at least the 60s and it needs to be known that it was bunk then and continues to be bunk.

Update: There's no need for Chinese Room thought experiments. The outcome isn't what defines sentience, personhood, intelligence, etc. An algorithm is an algorithm. A computer is a computer. These things matter.

[WarmWash]

>Biological brains exist, we study them, and no they are not like computers at all.

You are confusing the way computation is done (neuroscience) with whether or not computation is being done (transforming inputs into outputs).

The brain is either a magical antenna channeling supernatural signals from higher planes, or it's doing computation.

I'm not aware of any neuroscientists in the former camp.

[goatlover]

Neuroscience isn't a subset of computer science. It's a study of biological nervous systems, which can involve computational models, but it's not limited to that. You're mistaking a kind of map (computation) for the territory, probably based on a philosophical assumption about reality.

At any rate, biological organisms are not like LLMs. The nervous systems of human may perform some LLM-like actions, but they are different kinds of things.

[agentultra]

> The brain is either a magical antenna channeling supernatural signals

There’s the classic thought-terminating cliche of the computational interpretation of consciousness.

If it isn’t computation, you must believe in magic!

Brains are way more fascinating and interesting than transistors, memory caches, and storage media.

[coldtea]

>This is the worst possible take. It dismisses an entire branch of science that has been studying neurology for decades. Biological brains exist, we study them, and no they are not like computers at all.

They're not like computers in a superficial way that doesn't matter.

They're still computational apparatus, and have a not that dissimilar (if way more advanced) architecture.

Same as 0 and 1s aren't vibrating air molecules. They can still encode sound however just fine.

>Update: There's no need for Chinese Room thought experiments. The outcome isn't what defines sentience, personhood, intelligence, etc. An algorithm is an algorithm. A computer is a computer. These things matter.

Not begging the question matters even more.

This is just handwaving and begging the question. 'An algorithm is an algorithm' means nothing. Who said what the brain does can't be described by an algorithm?

[tux1968]

> An algorithm is an algorithm. A computer is a computer. These things matter.

Sure. But we're allowed to notice abstractions that are similar between these things. Unless you believe that logic and "thinking" are somehow magic, and thus beyond the realm of computation, then there's no reason to think they're restricted to humanity.

It is human ego and hubris that keeps demanding we're special and could never be fully emulated in silicon. It's the exact same reasoning that put the earth at the center of the universe, and humans as the primary focus of God's will.

That said, nobody is confused that LLM's are the intellectual equal of humans today. They're more powerful in some ways, and tremendously weaker in other ways. But pointing those differences out, is not a logical argument in proving their ultimate abilities.

[Octoth0rpe]

> Unless you believe that logic and "thinking" are somehow magic, and thus beyond the realm of computation

Worth noting that significant majority of the US population (though not necessarily developers) does in fact believe that, or at least belongs to a religious group for which that belief is commonly promulgated.

[goatlover]

I think computation is an abstraction, not the reality. Same with math. Reality just is, humans come up with maps and models of it, then mistake the maps for the reality, which often causes distortions and attribution errors across domains. One of those distortions is thinking consciousness has to be computable, when computation is an abstraction, and consciousness is experiential.

But it's a philosophical argument. Nothing supernatural about it either.

[stickynotememo]

Worth noting that this is the thesis of Seeing Red: A study in consciousness. I think you will find it a good read, even if I disagreed with some of the ideas.

[rolph]

silicon is not a dynamic structure, silicon does not reengineer and reconfigure itself in response to success/failure or rules discovery.

[cshores]

Worth separating “the algorithm” from “the trained model.” Humans write the architecture + training loop (the recipe), but most of the actual capability ends up in the learned weights after training on a ton of data.

Inference is mostly matrix math + a few standard ops, and the behavior isn’t hand-coded rule-by-rule. The “algorithm” part is more like instincts in animals: it sets up the learning dynamics and some biases, but it doesn’t get you very far without what’s learned from experience/data.

Also, most “knowledge” comes from pretraining; RL-style fine-tuning mostly nudges behavior (helpfulness/safety/preferences) rather than creating the base capabilities.

[Kim_Bruning]

> Biological brains exist, we study them, and no they are not like computers at all.

Technically correct? I think single bioneurons are potentially Turing complete all by themselves at the relevant emergence level. I've read papers where people describe how they are at least on the order of capability of solving MNIST.

So a biological brain is closer to a data-center. (Albeit perhaps with low complexity nodes)

But there's so much we don't know that I couldn't tell you in detail. It's weird how much people don't know.

* https://arxiv.org/abs/2009.01269 Can Single Neurons Solve MNIST? The Computational Power of Biological Dendritic Trees

* https://pubmed.ncbi.nlm.nih.gov/34380016/ Single cortical neurons as deep artificial neural networks (this one is new to me, I found it while searching!)

[agentultra]

Obviously any kind of model is going to be a gross simplification of the actual biological systems at play in various behaviors that brains exhibit.

I'm just pointing out that not all models are created equal and this one is over used to create a lot of bullshit.

Especially in the tech industry where we're presently seeing billionaires trying to peddle a new techno-feudalism wrapped up in the mystical hokum language of machines that can, "reason."

I don't think the use of the computational interpretation can't possibly lead to interesting results or insights but I do hope that the neuroscientists in the room don't get too exhausted by the constant stream of papers and conference talks pushing out empirical studies.

[Kim_Bruning]

> There have been charlatans repeating this idea of a “computational interpretation,” of biological processes since at least the 60s and it needs to be known that it was bunk then and continues to be bunk.

I do have to react to this particular wording.

RNA polymerase literally slides along a tape (DNA strand), reads symbols, and produces output based on what it reads. You've got start codons, stop codons, state-dependent behavior, error correction.

That's pretty much the physical implementation of a Turing machine in wetware, right there.

And then you've got Ribosomes reading RNA as a tape. That's another time where Turing seems to have been very prescient.

And we haven't even gotten into what the proteins then get up to after that yet, let alone neurons.

So calling 'computational interpretation' bunk while there's literal Turing machines running in every cell might be overstating your case slightly.

[gf000]

To the best of our knowledge, we live in a physical reality with matter that abides by certain laws.

So personal beliefs aside, it's a safe starting assumption that human brains also operate with these primitives.

A Turing machine is a model of computation which was in part created so that "a human could trivially emulate one". (And I'm not talking about the Turing test here). We also know that there is no stronger model of computation than what a Turing model is capable of -> ergo anything a human brain could do, could in theory be doable via any other machine that is capable of emulating a Turing machine, be it silicon, an intricate game of life play, or PowerPoint.

[goatlover]

It's better to say we live in a reality where physics provides our best understanding of how that fundamental reality behaves consistently. Saying it's "physical" or follows laws (causation) is making an ontological statement about how reality is, instead of how we currently understand it.

Which is important when people make claims that brains are just computers and LLMs are doing what humans do when we think and feel, because reality is computational or things to that effect.

[namero999]

That's a very superficial take. "Physical" and "reality" are two terms that must be put in the same sentence with _great_ care. The physical is a description of what appears on our screen of perception. Jumping all the way to "reality" is the same as inferring that your colleague is made of luminous RGB pixels because you just had a Zoom call with them.

[rolph]

the deepest laws of physics are immutable, the derivative rules based assemblages are not.

human brains break the rules, on a regular basis.

if you cant reach the banana, you break the constraints, once you realize the crates about the room can be assembled to create a staircase.