Comment by xtracto
18 hours ago
Imagine the first time electric calculators calculated the square root of 5. I'm sure people would verify again and again if what the circuits calculated was right.
Then in the 80s, you presses 2 buttons and there you had it in your classroom without thinking twice if the electricity arrived correctly at the transistors.
How crazy will the world be once our [current gen] ANN are like that!
What an amazing thought.
It is insane how many times I see this false analogy repeated on HN over and over (analogy of a deterministic-by-design calculator device (or a compiler, etc.) and a non-deterministic-by-design LLM software).
LLMs are not non-deterministic by design. The randomness in the output is artificially injected for ergonomic reasons. (Yes, the non-determinism in production systems is different, but also not by design)
You don’t train calculators on how to add. All calculators will more or less come up with the same answer to some deterministic and quantifiable level of accuracy and precision.
Nothing is deterministic.
Nothing is stopping LLMs to be more deterministic/correct over time.
Also you yourself is nondeterministic :)
>Also you yourself is nondeterministic :)
All people are. That is how automation appeared to begin with - to provide deterministic behavior.
You're missing the forest for the trees here. The point OP is trying to make is that calculators originally were essentially non-deterministic. Technology will go from unreliable to reliable.
Calculators never were non-deterministic by design.
Non-deterministic calculators are called dice.
Calculators and computers are deterministic, they give the same output to the same output every time. Language models specifically are not. So it might give you are function that is correct, or a function that is not, or worse yet a function that behaves correctly, but introduces some god-awful bug down the line that can cause serious havoc. It is obvious that they need supervision, not only for output, but also sandboxing and various harnesses for them to not do any “oops, I deleted your codebase sry” kind of nonsense people post to Reddit.
So I think the problem is to determine which problems under what instructions we can safely give to a model application to solve and how we test the output for safety and functionality. This would create more usable and safe, albeit a bit more boring, AI-based applications alin to a calculator or general computer. Whether this is posswith current model architecture is another thing.
If you set the temperature 0, an LLM is also deterministic (same prompt -> same output every single time). We just don't do this because the LLM is not so smart in that mode. But "LLM is not so smart" is changing at Moore's law speeds.
Non-determinism is not an essential property of LLMs. It's an optimization that we've added intentionally.
Ehm, no! The same prompt does not always lead to the same output.
Have you ever tried to achieve consistently deterministic output from an LLM? I have, and it's not easy.
That means output differs between machines and architectures. Running inference on CPU vs GPU also affects output. Even running the same prompt twice in a row on the same machine can lead to different outputs because a prompt that was partially stored in the kv cache will result in different output than an uncached prompt.
LLM output is very much not deterministic!
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Humans (IQ of X, non deterministic) can write deterministic code.
AI (IQ of Y, non deterministic) can write deterministic code.
Y is going to keep increasing, while X will not.
Why will X not keep increasing? It’s been increasing, albeit very slowly, since the start of the 20th century as the disease burden declines and nutrition improves. I see no reason to think that future health interventions couldn’t further juice those numbers.
Will it keep up with Y? Probably not, unless people are willing to accept pretty radical interventions to their biology. But it almost certainly is not static
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> Calculators and computers are deterministic
How do you know?
Memory bits flip randomly. It's not a super rare thing either. You and me have experienced that many times without knowing. The only reason that computers feel deterministic is that we have error-correcting code to fix that. But in the most extreme cases, when multiple bits flip together, once "deterministic" program can generate unexpected output.
So why do you trust computers? Because statistically the case is just very unlikely. Therefore if AI is statistically unlikely to make mistakes there is no reason to not trust them.
You are confusing hardware noise and whether the algorithm itself is verifiable as if parity bits were not a thing. We don’t trust computers because the medium itself is infallible, but because the logic is sound.
With statistical models - such as LLM’s - there is no logic as such, but statistical assumptions based on given data. The output can ge very good or very bad, but you are fool to trust it blindly. Therefore you need a deterministic way to verify, whether meat- or software-based.
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Calculators aren't deterministic if you go all the way down, the electron "harness" introduces that consistency via error correction.
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Calculators hallucinate! Mine did not come with error correcting RAM. (Though you might not know from the price.)
It will be even more amazing if they solve the theory of everything or the hard problem of consciousness.
Imagine AI crushing quantum mechanics like Einstein pwned classical physics.
Given the disappointing levels of intellectual decay that our current technology has thrust upon civilization, I only see humans reverting back to neanderthal levels of intelligence in short time with the advent of AI
> One wonders whether a generation that demands instant satisfaction of all its needs and instant solution of the world's problems will produce anything of lasting value. Such a generation, even when equipped with the most modern technology, will be essentially primitive — it will stand in awe of nature, and submit to the tutelage of medicine men.
- Eric Hoffer
> Sounds awesome
- Tech Bro
There's no reliable evidence that Neanderthals were less intelligent than modern humans. They're extinct now (except for a tiny genetic legacy in some human populations) but that could have happened for a variety of reasons unrelated to intelligence or lack thereof.
> neanderthal levels of intelligence
were gonna need a citation on this one.
No you don't. If people don't learn to solve problems and exercise their mind with small problems, how are they going to deal with big problems? The "neanderthal" part is a colorful expression.
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