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

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

#201
post #138

Earlier quoted context omitted.

It's the most incredible coincidence. Three million paying OpenAI customers spend $20 per month (compare: NetFlix standard: $15.49/month) thinking they're chatting with something in natural language that actually understands what they're saying, but it's just statistics and they're only getting high-probability responses without any understanding behind it! Can you imagine spending a full year showing up to talk to a…

Maps are useful, but they don't understand the geography they describe. LLMs are maps of semantic structures and as such, can absolutely be useful without having an understanding of that which they map. If LLMs were capable of understanding, they wouldn't be so easy to trick on novel problems.

> Maps are useful, but they don't understand the geography they describe. LLMs are maps of semantic structures and as such, can absolutely be useful without having an understanding of that which they map.

That's a really interesting analogy I've never heard before! That's going to stick in my head right alongside Simon Willison's "calculator for words".

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

#202
post #118

Earlier quoted context omitted.

Jokes on you. Every time you played ball you were secretly learning about ballistic trajectories and estimating velocities using visual cues such as apparent angular size and parallax.

The brain uses heuristics for that

Being a father to two young kids, I can confidently say we aren’t born with those heuristics already tuned.

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

#203
post #185

Earlier quoted context omitted.

> Got it, so an LLM only understands my words if it has full mastery of every new problem domain within a few thousand milliseconds of the first time the problem has been posed in the history of the world. That's not what I said. Please try to have a good faith discussion. Sarcastically misrepresenting what I said does not contribute to a healthy discussion. There have been plenty of examples of taking simple, easy,…

Sounds like you want the LLM to get the answer right in all simple, easy cases before you will say it understands words. I hate to break it to you but people do not meet that standard either and misunderstand each other plenty. For three million paying customers, ChatGPT understands their questions well enough and they are happy to pay more than for any other widespread Internet service for the chance to ask it quest…

> I hate to break it to you but people do not meet that standard either and misunderstand each other plenty

Sure, and there are ways to tell when people don't understand the words they use.

One of the ways to check how well people understand a word or concept is to ask them a question they haven't seen the answer for.

It is the difference in performance on novel tasks that allows us to separate understanding from memorization in both people and computer models.

The confusing thing here is that these LLMs are capable of memorization at a scale that makes the lack of understanding less immediately apparent.

> You're entitled to your own standard of what it means to understand words but for millions of people it's doing great at it.

It's not mine, the distinction I am drawing is widespread and common knowledge. You see it throughout education and pedagogy.

> It is as though you said a dog couldn't really play chess if it plays legal moves all day every day from any position and for millions of people, but sometimes fails to see obvious mates in one in novel positions that never occur in the real world.

While I would say chess engines can play chess, I would not say the chess engines understands chess. Conflating utility with understanding simply serves to erase an important distinction.

I would say that LLMs can talk and listen. And perhaps even that it understand how people use language. Indeed, as you say, millions people show this every day. I would however not say that LLMs understand what they are saying or hearing. The words are themselves meaningless to the LLM beyond their use in matching memorized patterns.

Edit: Let me qualify my claims a little further. There may indeed be some words that are understood by some LLMs, but it seems pretty clear there are definitely some important ones that aren't. Given the scale of memorized material, demonstrating understanding is hard but assuming it is not safe.

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

#204
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…

Not just that the brain of a newborn comes pretrained with billions of years of evolution. There is an energy cost associated with that which must be taken into account

Also our brains and our language are co-optimised to be compatible.

ChatGPT has to deal with the languages we already created, it doesn't get to co-adapt.

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

#205

Earlier quoted context omitted.

> 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.

Also DeepBlue isn't an ML it's an "expert system, relying upon rules and variables defined and fine-tuned by chess masters and computer scientists" from Wikipedia. AlphaGo (or AlphaGo Zero) would be a better example.

> AlphaGo (or AlphaGo Zero) would be a better example.

Yes, they are better examples, but still not great examples: neither of them are LLMs.

In general, I have very high hopes for AI, but I would be surprised if LLMs are the one universal hammer for every nail. (We already have lots of other network architectures.)

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

#206

Earlier quoted context omitted.

> 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.

1. Deep blue isn't a LLM. I don't care how well you train a LLM, it's not going to be more efficient than an optimally trained human, not even close. It's actually arrogant as hell to assume that we can achieve a higher level of energy efficiency than billions of years of evolution, particularly so early in the game. 2. Chess is a closed form system with a finite and relatively small number of position compared with…

> It's actually arrogant as hell to assume that we can achieve a higher level of energy efficiency than billions of years of evolution, particularly so early in the game.

You are right that LLMs are still far off from the performance of the human brain. Both in absolute terms, and also relative to the power used.

However, I don't see anything arrogant here. We have lots of machines that can do many tasks more energy efficient (and better) than humans. Both mechanical and intellectual tasks.

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

#207
post #206

Earlier quoted context omitted.

1. Deep blue isn't a LLM. I don't care how well you train a LLM, it's not going to be more efficient than an optimally trained human, not even close. It's actually arrogant as hell to assume that we can achieve a higher level of energy efficiency than billions of years of evolution, particularly so early in the game. 2. Chess is a closed form system with a finite and relatively small number of position compared with…

> It's actually arrogant as hell to assume that we can achieve a higher level of energy efficiency than billions of years of evolution, particularly so early in the game. You are right that LLMs are still far off from the performance of the human brain. Both in absolute terms, and also relative to the power used. However, I don't see anything arrogant here. We have lots of machines that can do many tasks more energy…

It's not arrogance to think you can create a tool that does one thing the brain does better than the brain for less power. It's arrogance to think that you can do everything the brain does for less power. Living organisms have been relentlessly honed for the ability to efficiently solve varied problems across ~10^40 experiments over the age of the earth. If some marginally intelligent monkeys think they can build an error corrected, digital system that encompasses all of that functionality while using less power, I'd say that's obviously arrogance, particularly if it hasn't been the subject of a civilizational drive for a few millennia already.

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

#208
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…

Not just that the brain of a newborn comes pretrained with billions of years of evolution. There is an energy cost associated with that which must be taken into account

Those are sunk costs

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

#209
post #206

Earlier quoted context omitted.

> It's actually arrogant as hell to assume that we can achieve a higher level of energy efficiency than billions of years of evolution, particularly so early in the game. You are right that LLMs are still far off from the performance of the human brain. Both in absolute terms, and also relative to the power used. However, I don't see anything arrogant here. We have lots of machines that can do many tasks more energy…

It's not arrogance to think you can create a tool that does one thing the brain does better than the brain for less power. It's arrogance to think that you can do everything the brain does for less power. Living organisms have been relentlessly honed for the ability to efficiently solve varied problems across ~10^40 experiments over the age of the earth. If some marginally intelligent monkeys think they can build an…

> Living organisms have been relentlessly honed for the ability to efficiently solve varied problems across ~10^40 experiments over the age of the earth.

Evolution has been optimising them for creating descendants, not general problem solving with minimum energy expenditure.

No one expects that LLMs can solve all problems: they can't. They can only predict text, nothing else. They can't fight off a virus infection or evade a lion. Specifically, LLMs can't reproduce at all either, yet alone efficiently. Reproduction is what evolution is all about.

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

#210
post #209

Earlier quoted context omitted.

It's not arrogance to think you can create a tool that does one thing the brain does better than the brain for less power. It's arrogance to think that you can do everything the brain does for less power. Living organisms have been relentlessly honed for the ability to efficiently solve varied problems across ~10^40 experiments over the age of the earth. If some marginally intelligent monkeys think they can build an…

> Living organisms have been relentlessly honed for the ability to efficiently solve varied problems across ~10^40 experiments over the age of the earth. Evolution has been optimising them for creating descendants, not general problem solving with minimum energy expenditure. No one expects that LLMs can solve all problems: they can't. They can only predict text, nothing else. They can't fight off a virus infection or…

Life is optimized for _SURVIVAL_ which means being able to navigate the environment, find and find/utilize resources and ensure that they continue to exist. Reproduction is just a strategy for that.

LLMs are human thinking emulators. They're absolutely garbage compared to "system 1" thinking in humans, which is massively more efficient. They're more comparable to "system 2" human thought, but even there I doubt they're close to humans except for cases where the task involves a lot of mundane, repetitive work - even for complex logic and problem solving tasks I'd be willing to bet that the average competitive mathematician is still an order of magnitude more efficient than a LLM SoTA at problems they could both solve.

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