Slightly apples to oranges comparison. The brain has an incredibly complex architecture, which evolved over millions of years. On top of that, it then develops

Slightly apples to oranges comparison. The brain has an incredibly complex architecture, which evolved over millions of years. On top of that, it then develops throughout a human's lifespan. The brain we observe is a "finished product", and even then it has ~150 trillion synapses to do computations [0]. Even massive neural networks have a relatively simple architecture before they are trained. Part of the training process is effectively learning more complex architectures, which are manifested by changing weights. What I'm getting it is that artificial neural networks aren't equivalent to the brain - ANNs are both learning their own structure, on top of the circuits actually doing computations. They are doing the work of millions of years of evolution, genetics, developmental biology, interaction with the environment etc. Perhaps it's to be expected that ANNs will need orders of magnitude greater number of parameters than a brain. An interesting development is meta-learning, where we separate the process for learning the architecture (this could be using deep learning, but not necessarily) with the network actually doing computation (equivalent to the brain). > A language model must be based on the fundamental notion that there are nouns (things), verbs (processes) and adjectives (attributes). I agree, but how does the brain represent these concepts? Some would argue that ANNs do have these concepts, just hidden away in abstract vector representations. Take the visual system, which has been extensively studied - we see the brain represents contrast, edges, shapes and so on very similarly to convolutional NNs. [0] It's likely that this number doesn't come close to capturing the brain's complexity, as it doesn't incorporate parameters like long-term potentiation/depression, synchronization, firing rates, habituation vs sensitization, immunomodulation and likely so much more we haven't yet discovered.