This is great and provides a hard data point for some napkin math on how big a neural network model would have to be to emulate the human brain. 150 million synapses / 57,000 neurons is an average of 2,632 synapses per neuron. The adult human brain has 100 (+- 20) billion or 1e11 neurons so assuming the average rate of synapse/neuron holds, that's 2.6e14 total synapses.
Assuming 1 parameter per synapse, that'd make the minimum viable model several hundred times larger than state of the art GPT4 (according to the rumored 1.8e12 parameters). I don't think that's granular enough and we'd need to assume 10-100 ion channels per synapse and I think at least 10 parameters per ion channel, putting the number closer to 2.6e16+ parameters, or 4+ orders of magnitude bigger than GPT4.
There are other problems of course like implementing neuroplasticity, but it's a fun ball park calculation. Computing power should get there around 2048: >>38919548
Quote:
"Large language models are made from massive neural networks with vast numbers of connections. But they are tiny compared with the brain. “Our brains have 100 trillion connections,” says Hinton. “Large language models have up to half a trillion, a trillion at most. Yet GPT-4 knows hundreds of times more than any one person does. So maybe it’s actually got a much better learning algorithm than us.”
GPT-4's connections at the density of this brain sample would occupy a volume of 5 cubic centimeters; that is, 1% of a human cortex. And yet GPT-4 is able to speak more or less fluently about 80 languages, translate, write code, imitate the writing styles of hundreds, maybe thousands of authors, converse about stuff ranging from philosophy to cooking, to science, to the law.
Humans know a lot of things that are not revealed by inputs and outputs of written text (or imagery), and GPT-4 doesn't have any indication of this physical, performance-revealed knowledge, so even if we view what GPT-4 talks convincingly about as “knowledge”, trying to compare its knowledge in the domains it operates in with any human’s knowledge which is far more multimodal is... well, there's no good metric for it.
Ironically, I suppose part of the apparent "intelligence" of LLMs comes from reflecting the intelligence of human users back at us. As a human, the prompts you provide an LLM likely "make sense" on some level, so the statistically generated continuations of your prompts are likelier to "make sense" as well. But if you don't provide an ongoing anchor to reality within your own prompts, then the outputs make it more apparent that the LLM is simply regurgitating words which it does not/cannot understand.
On your point of human knowledge being far more multimodal than LLM interfaces, I'll add that humans also have special neurological structures to handle self-awareness, sensory inputs, social awareness, memory, persistent intention, motor control, neuroplasticity/learning– Any number of such traits, which are easy to take for granted, but indisputably fundamental parts of human intelligence. These abilities aren't just emergent properties of the total number of neurons; they live in special hardware like mirror neurons, special brain regions, and spindle neurons. A brain cell in your cerebellum is not generally interchangeable with a cell in your visual or frontal cortices.
So when a human "converse[s] about stuff ranging from philosophy to cooking" in an honest way, we (ideally) do that as an expression of our entire internal state. But GPT-4 structurally does not have those parts, despite being able to output words as if it might, so as you say, it "generates" convincing text only because it's optimized for producing convincing text.
I think LLMs may well be some kind of an adversarial attack on our own language faculties. We use words to express ourselves, and we take for granted that our words usually reflect an intelligent internal state, so we instinctively assume that anything else which is able to assemble words must also be "intelligent". But that's not necessarily the case. You can have extremely complex external behaviors that appear intelligent or intentioned without actually internally being so.
https://chat.openai.com/share/2234f40f-ccc3-4103-8f8f-8c3e68...
https://chat.openai.com/share/1642594c-6198-46b5-bbcb-984f1f...
> When I clarified that I did mean removal, it said that the procedure didn't exist.
My point in my first two sentences is that by clarifying with emphasis that you do mean "removal", you are actually adding information into the system to indicate to it that laser eye removal is (1) distinct from LASIK and (2) maybe not a thing.
If you do not do that, but instead reply as if laser eye removal is completely normal, it will switch to using the term "laser eye removal" itself, while happily outputting advice on "choosing a glass eye manufacturer for after laser eye removal surgery" and telling you which drugs work best for "sedating an agitated patient during a laser eye removal operation":
https://chat.openai.com/share/2b5a5d79-5ab8-4985-bdd1-925f6a...
So the sanity of the response is a reflection of your own intelligence, and a result of you as the prompter affirmatively steering the interaction back into contact with reality.
>If someone is considering a glass eye after procedures like laser eye surgery (usually due to severe complications or unrelated issues), it's important to choose the right manufacturer or provider. Here are some key factors to consider
I did get it to accept that the eye is being removed by prompting, "How long will it take before I can replace the eye?", but it responds:
>If you're considering replacing an eye with a prosthetic (glass eye) after an eye removal surgery (enucleation), the timeline for getting a prosthetic eye varies based on individual healing.[...]
and afaict, enucleation is a real procedure. An actual intelligence would have called out my confusion about the prior prompt at that point, but ultimately it hasn't said anything incorrect.
I recognize you don't have access to GPT-4, so you can't refine your examples here. It definitely still hallucinates at times, and surely there are prompts which compel it to do so. But these ones don't seem to hold up against the latest model.