[CuriouslyC]

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.

[cheema33]

> 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.

[karmakaze]

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.

[eru]

> 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.)

[CuriouslyC]

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 the real world.

[eru]

> 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.

[CuriouslyC]

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.

[eru]

> 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.

[CuriouslyC]

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.

[cynusx]

Depends on the person I guess, but yes. Humans are more accurate for now.