| ▲ | za_creature 2 hours ago | |
> neural networks are algorithms ... are they? Algorithms are predictable: 1. it's really difficult to produce true randomness in an algorithm, which is why there's a whole area of study surrounding the qualities of pseudo-randomness, specifically with regards to the generation of cryptographic material with most conclusions being that we should draw entropy from the environment (e.g. electrical noise as cloudflare does - the lava lamp is a distraction) 2. when algorithms are not predictable despite being mathematically sound, this is indicative of a problem nowadays called "numerical stability" which again spawned its own area of study. CGoL shows how really simple rules (couple of bytes of data) can lead to extremely complex outcomes and you have the BB turing-golf aspect as proof of the worst case scenario. And with current models being measured in hundreds of gigabytes, with frontier labs deprecating then removing the "temperature" parameter (which never worked to begin with, temp=0 did not result in reproducible results), where exactly is the confidence of this 10^10 prediction coming from? | ||
| ▲ | antonvs 17 minutes ago | parent [-] | |
Yes, (digital) neural networks are algorithms. You probably know that non-determinism in real-world inference comes from deliberately stochastic features like temperature, from implementation choices like distributed and parallel computation, and numerical effects like floating point precision. The fact that a neural network's execution can be nondeterministic doesn't mean that the network stops being an algorithm. The point you're making boils down to speculation that the accidental non-determinism involved in real-world inference is significant enough to undermine or negate interpretability findings based on the algorithms. That would need to be demonstrated. The CGoL and BB examples demonstrate what might be possible in a worst-case scenario, but they're only analogies in this context. It's far from clear that real models suffer from such effects to a significant degree. You might actually be better off talking about the butterfly effect! | ||