Up until this point, I agree.
This puts humans on too high a pedestal: LLMs aren't magic, and we're not magic either.
(There's other reasons for me to think Transformers aren't the answer, but not this kind of reasoning).
Up until this point, I agree.
This puts humans on too high a pedestal: LLMs aren't magic, and we're not magic either.
(There's other reasons for me to think Transformers aren't the answer, but not this kind of reasoning).
"Trees aren't special", "Dolphins aren't special", "Koala's suck, let's put a mine here instead", "Pigs don't have emotions or are dumb, so it's fine to factory farm" etc.
(My gut feeling says "LLMs are not conscious", but my gut has had a lot of false beliefs over the years as well as correct ones, so I give it a corresponding level of trust).
Similarly with other properties of intelligence and the brain that we like to think are mysterious and deep.
When you think about it, a bird is “magic” in the sense there is a whole universe and eco system to give that bird the platform for existence. A real living bird isn’t just a concept.
So sometimes I wonder if we just say we’re insignificant because it’s a simpler way to think. It makes the idea of death and loss easier to bear.
If I tell myself I’m just a spec of dust and that I’m bit special, it can be quite comforting.
Conceptually we understand things about how birds work but the fact there is a blob of millions or billions of cells functioning to produce a bird, which can fly, completely autonomously is quite peculiar and there is a type of magic or wonder to it all which makes me think birds are both special and magic if you think differently about existence and not just the intellectual concept of a bird.
On the other hand. Take that weather model and render its output into a stereoscopic 3D world with photorealistic particle systems and whatever. To someone wearing a Vision Pro or similar high-def VR headset, the model is now “the weather” in the system their senses occupy. It’s missing a lot of actual sensory cues — the rain isn’t wet, the wind won’t chill your skin, and so on. But it’s close enough for some convincing applications. A caveman with no experience with technology would undoubtedly believe himself transported into a different world with real weather.
LLMs are a bit like that now. Their simulation abilities took such a sudden leap, we’re like cavemen wearing headsets.
A (philosophical) dualist can easily say that no computation is ever intelligent. I don't think this can ever be said by a (philosophical) materialist.
We pretty much are compared to present-day neural architectures. How many simulated neurons and synapses are in the largest architectures, and how do those numbers compare to humans?
Also, modern LLMs built on the transformers architecture no longer use the neuron-inspired perceptron style topology for most of their compute.
I’ve heard that spiking NNs are supposed to mimic organic brains more closely, but I haven’t read into them much yet.
Usually, linear perceptrons and ReLUs or GeLUs are used. Due to the enormous compute requirements to evaluate models of interesting size, other types of neuronal networks and activation functions have received very little attention (pun intended) so far.
Using non fully connected layers is as well. Our brains likely aren’t fully connected, but the connections that matter are made stronger through living life and learning.
If you squint, it’s kind of like training a dense series of linear layers, but that’s not what we’re doing anymore (for the better)
Comparing NNs to organic brains is an apples to oranges comparison, is what I’m saying.
I think the biggest difference is that they need far more examples than we need, to learn anything.
The comparison would therefore be with a mid-sized rodent, horse, or raven rather than a human.
(But even that's misleading, because the LLM doesn't have to use tokens to represent "contract left supracoracoideus" and "lay egg").
Edit: also, I've not heard much suggestion that anyone knows how certain genes do things like giving humans the inherent capability to recognise and create smiles or other similar reflexes, so we don't really know how much of our brains a pre-trained by evolution; furthermore, I think organic life is more sample-efficient for learning things than any AI so far.
Tokens are allowed to be blocks of pixels, for example. No reason we couldn't have a token be a specific muscle or sensory nerve.
What I'm saying is that Large Language Models don't have a body, so no nerves and muscles to have to be represented within them; conversely, organic life does have those things and thus organic brains must spend some of their complexity on those things.
This means they have the possibility to equal us for language even with no capacity for vision, walking, tying shoelaces, or playing catch.