The irony of this post. Brains are sparser than transformers, not denser. That allows you to learn symbolic concepts instead of generalising from billions of spurious correlations. Sure, that works when you've memorised the internet but falls over quickly when out of domain. Humans, by contrast, don't fall over when the domain shifts, despite far less training data. We generalise using symbolic concepts precisely because our architecture and training procedure looks nothing like a transformer. If your brain were a scaled up transformer, you'd be dead. Don't take this the wrong way, but it's you who needs to read some neurology instead of pretending to have understanding you haven't earned. "Just an emergent propery of billions of connected weights" is such an outdated view. Embodied cognition, extended minds, collective intelligence - a few places to start for you.

We don't learn by gradient descent, but rather by experiencing an environment in which we perform actions and learn what effects they have. Reinforcement learning driven by curiosity, pain, pleasure and a bunch of instincts hard-coded by evolution. We are not limited to text input: we have 5+ senses. We can output a lot more than words: we can output turning a screw, throwing a punch, walking, crying, singing, and more. Also, the words we do utter, we can utter them with lots of additional meaning coming from the tone of voice and body language.

We have innate curiosity, survival instincts and social instincts which, like our pain and pleasure, are driven by gene survival.

We are very different from language models. The ball in your court: what makes you think that despite all the differences we think the same way?

> Where is the concrete evidence that human intelligence can be simulated by a Turing Machine?

Short of building such a machine I can’t see how you’d produce evidence of that, let alone “concrete” evidence.

Regardless, we don’t know of any measurable physical process that the brain could be using that is not computable. If we found one (in the brain or elsewhere), we’d use it to construct devices that exceeded the capacity of Turing machines, and then use those to simulate human brains.

Nobody is saying humans are simply a big LLM, just that despite the means being different (brain vs digital weights) there are enough parallels to show that human cognition is as simple as common sense implies.

It's all just a dense network of weights and biases of different sorts.