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Why your brain is 3 milion more times efficient than GPT-4

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171–180 of 213 posts

Re: Why your brain is 3 milion more times efficient than GPT-4

#171

Earlier quoted context omitted.

I mean I can definitely remember lots of cases for myself, in school especially, when I made the same mistake again repeatedly despite being corrected every time. I'm sure today's language models pale in comparison to your flawless genius, but you seriously underestimate the average person's idiocy. Agreed that the lack of some mid tier memory is definitely a huge problem, and the current solutions that try to addres…

It lacks more than memory, it makes the mistake again later even when the previous prompt is in its current token limit.

Sure, it happens. How often it happens really depends on so many factors though.

For example, I have this setup where a model has some actions defined in its system prompt that it can output when appropriate to trigger actions, and the interesting bit is that initially I was using openhermes-mistral which is famous for its extreme attention to the system prompt, and it almost never made any mistakes when calling the definitions. Later I swapped it with llama-3 which is way smarter, but isn't tuned to be nearly as attentive and far more often likes to make up alternatives and don't get fuzzy matched properly. Someone anthropomorphizing it might say it lacks discipline.

Re: Why your brain is 3 milion more times efficient than GPT-4

#172
post #24
post #21

FTFY: ONLY 3 million times. At the current pace of development, AI will catch-up in a decade or less.

How does that math work out? The developments during the last year has been... Abysmal? The hype and marketing bull is increasing exponentially though.

> How does that math work out?

He asked chatgpt to do the math.

Re: Why your brain is 3 milion more times efficient than GPT-4

#173
post #31

The comparison doesn't really hold. He is comparing energy spend during inference in humans with energy spend during training in LLM's. Humans spend their lifetimes training their brain so one would have to sum up the total training time if you are going to compare it to the training time of LLM's. At age 30 the total energy use of the brain sums up to about 5000 Wh, which is 1440 times more efficient. But at age 30…

You're doing apples and oranges. Humans who spend a long time doing inference have not fully learned the thing being inferred - unlike LLMs, when we are undertrained, rather than a huge spike in error rate, we go slower. When humans are well trained, human inference absolutely destroys LLMs.

> When humans are well trained, human inference absolutely destroys LLMs.

This isn't an apt comparison. You are comparing a human trained in a specific field to an LLM trained on everything. When an LLM is trained with a narrow focus as well, human brain cannot compete. See Garry Kasparov vs Deep Blue. And Deep Blue is very old tech.

Re: Why your brain is 3 milion more times efficient than GPT-4

#174

I don't care. I've come to the conclusion that gpt and gemini and all the others are nothing but conversational search engines. They can give me ideas or point me in the right direction but so do regular search engines. I like the conversation ability but, in the end, I cannot trust their results and still have to research further to decide for myself if their results are valid.

You should not dismiss all LLMs unless you have tried the best one. Gemini is not the best LLM. Try Meta AI, which is free, and ChatGPT premium first.

Re: Why your brain is 3 milion more times efficient than GPT-4

#177
post #34

Earlier quoted context omitted.

No, only a brain can "think" and be original. A computer is limited to what we input to it. An "AI" simply recapitulates what it was trained on.

A brain is an electrochemical network made of cells; artificial neural networks are a toy model of these. Each neurone is itself a complex combination of chemicals cycles; these can be, and have been, simulated. The most complex chemicals in biology are proteins; these can be directly simulated with great difficulty, and we've now got AI that have learned to predict them much faster than the direct simulations on a c…

I think the real question is "How can we make a computer think without trying to fully simulate a brain?"

Re: Why your brain is 3 milion more times efficient than GPT-4

#178
post #31

The comparison doesn't really hold. He is comparing energy spend during inference in humans with energy spend during training in LLM's. Humans spend their lifetimes training their brain so one would have to sum up the total training time if you are going to compare it to the training time of LLM's. At age 30 the total energy use of the brain sums up to about 5000 Wh, which is 1440 times more efficient. But at age 30…

Humans spend their lifetimes training their brain I don't think this is true personally, ideally as children, we spend out time having fun and learning about the world is a side effect. This borg like thinking applied to intelligence because we have LLMs is unusual to me. I learned surfing through play and enjoyment, not through training like a robot. We can train for something with intention, but I think that is mos…

That's like saying that you eat because it tastes good.

Re: Why your brain is 3 milion more times efficient than GPT-4

#180
post #165
post #143

Earlier quoted context omitted.

Amusingly, the author does not appear to fully understand the meaning of "axiom". While practice, axioms are often statements that we all agree on and accept as true, that isn't necessarily true and isn't the core of it's meaning. Axioms are something we postulate as true, without providing an argument for its truth, for the purposes of making an argument. In this case, the assertion isn't really used as part of a ar…

> Axioms are something we postulate as true, without providing an argument for its truth, for the purposes of making an argument. Uhm… no? They are literally things that can't be proven but allow us to prove a lot of other things.

"unprovability" is not a property that it is necessary to prove to pick something as an axiom.

There is generally a project to reduce axioms to the simplest and weakest forms required to make a proof. This is does result in axioms that are unprovable but does not mean the "unprovable" is a necessary property of axioms.

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