Comment by supern0va | Hacker News Reader

Comment by supern0va | Hacker News Reader

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>I can just as well describe the future evolution of the internal combustion engine and claim it will get more and more efficient and eventually we will be able to burn oil so efficiently that our personal vehicles can fly through the atmosphere at twice the speed of sound.

This is a silly comparison. There is a certain quantity of energy stored in oil, so we know what peak efficiency looks like. We don't actually know what amount of energy is required to solve certain problems. We quite literally have models with quite a bit of capability that can run locally on a phone today, right alongside Stockfish, for example.

And this is to say nothing of work happening now on new hardware approaches, such as Normal Computing's work on thermodynamic matrix math: https://www.normalcomputing.com/blog/a-first-demonstration-o...

That said, this feels like a strange tangent: I'm not sure it's that important that the models be as energy efficient as a human brain. We don't avoid cars because they're less energy efficient than our legs. ;)

Point is that both are science fiction narratives and neither reflect reality in any way what-so-ever. How fast a car can drive and how much a LLMs can compute are bounded quantities, limited by the physical reality. In both cases we can imagine a world where this limit does not exist, but that is not the reality we live in.

This matters because unlike cars LLMs are only doing stuff we can already do using our brains, just several orders of magnitudes less efficiently. Cars can at least take us distances we would never be able to using our muscles. In comparison, if I need to compile CPython into a WASM binary I can simply download a library that does it, or copy paste code in a few seconds, for a million billionth of the energy it takes an LLM to do the same. Except when I download the library or copy-paste the code I (hopefully) attribute the original author and give them credit for their work.

>Point is that both are science fiction narratives and neither reflect reality in any way what-so-ever. How fast a car can drive and how much a LLMs can compute are bounded quantities, limited by the physical reality. In both cases we can imagine a world where this limit does not exist, but that is not the reality we live in.

I'm suggesting that while LLMs are bounded by physical reality, that you actually don't know what that bound is. Just a few years ago we would have thought it a fantasy to have a conversational model run on a phone.

Even if you could compute it now, that would still be tied to current architectures. With appropriate incentives, we'll continue developing hardware to make these models more efficient to execute. It's very likely that you'll be able to run a Fable caliber coding model on your phone in the next five years.

>This matters because unlike cars LLMs are only doing stuff we can already do using our brains, just several orders of magnitudes less efficiently. Cars can at least take us distances we would never be able to using our muscles.

But that's not largely true of cars. The majority of trips are five miles or less and could easily be replaced with a bicycle. While I might personally use a bicycle, the majority choose a car to save a bit of time and effort.

So, please continue to enjoy your car, and I will continue to enjoy ready access to an LLM for a variety of other tasks. My inference energy costs are almost certainly less than your vehicle usage. ;)

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