- cross-posted to:
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- cross-posted to:
- [email protected]
As we continue developing our software, we accumulate a growing amount of technical debt just to keep the system running. But I believe we are on the brink of an even larger issue. Cognitive debt.
Hope you enjoy this reading, all feedback is welcome.
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I hate to say this but can’t LLMs solve the cognitive debt problem better then people? Wouldn’t having a stochastic machine that can have its state frozen in time, retrived at convience, and fed the same inputs be a potentially more transparent machine, thinking or otherwise?
I agree with you on stating thr problem though, and the term seems concise enough to me. The gap seems to be not in ability to do this but that creating graspable and reasonable audits for LLM usage is like many risk mitigation systems, an after thought in the industry.
and fed the same inputs be a potentially more transparent machine, thinking or otherwise?
This is where you go off the rails. LLMs are probalistic, not deterministic. It will probably give the same output, but thats still not actually true. This is where hallucinations come from.
Tbf the exact input and node activation is all you’d need for forensics, the only reason to refeed would old input plus new input mix, which should be new output.
Its not neural nets, its staticics. There aren’t nodes to trace.
Most of the LLMs architectures that I know of are neural net based.
For training maybe. But execution as far as i know are just a bunch of probabilities chucked into matrices. Back in my physcos days I could u derstand the math, but not today.
Also what needs citing, that nodes translate to debugable, reproducible outputs.
Because again, it’s all probablilties under the hood.
I mean probabilities in matrices are nodes in a neural net, right?
The only thing that makes it non-deterministic is the tempature value which is known after the fact from my understanding, so that should be able to deterministic.
No… No they’re not. Either that or nerual nets are even dumber than I thought. My understanding was emulating nodes of information like brains do. Thats not probabilities. But willing to be wrong if you can bring sources. The connection between points in probability doesn’t make sense. Thats a nonsense statement.
Thats also no how simulated annealing works. The temperature value is roughly the probability it will pick a different, less optimal step, in order to try and find better alternative paths. The temperature value is roughly the probability of trying something ‘random’. Not deterministic at all. The temperature value is lowered with time and progression. Its known the entire time, but its still a weighted coin flip that determines which path to take.