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.
Nothing is stopping LLMs to be more deterministic/correct over time.
Also you yourself is nondeterministic :)
All people are. That is how automation appeared to begin with - to provide deterministic behavior.
you clearly don't know how transistors work, which is ironic because it's a thread in hackernews about LLMs and mathematics
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.
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.
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.
> meat-
There is no meat-based deterministic way to do anything yet yet. You're talking sci-fi.
AI (IQ of Y, non deterministic) can write deterministic code.
Y is going to keep increasing, while X will not.
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
The increases still happen globally but mostly driven by developing countries.
Non-determinism is not an essential property of LLMs. It's an optimization that we've added intentionally.
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!
At the end of the day, an LLM is just a very big mathematical function. That is, by definition, deterministic. A particular implementation might give up on determinism for the sake of higher efficiency, but it you want a deterministic LLM, it can absolutely be done.
If you ran an LLM with infinite precision and guaranteed order of execution, it would be deterministic.
(I think determinism is overrated. Being deterministic does not make LLMs more reliable or correct.)
Non-determinism is injected, on purpose.
Put another way: if you could have a virtualization layer that guarantees deterministic floating point operations then a LLM set to 0.0 temp would produce deterministic output.
Imagine AI crushing quantum mechanics like Einstein pwned classical physics.
- Eric Hoffer
- Tech Bro
were gonna need a citation on this one.
There are so many parallels between what TV could have become and the progression of AI, a nearly free conveyance for culture, education, art and discourse. Yet, we allowed it spiral in a positive feedback loop, creating a cognitive gyre that now razes society.
At least the youngest now use "that's AI" as a pejorative, as in that is bullshit.