

I apologize if my last comment sounded condescending or antagonistic, that was not my intention.
I did indeed read your comment, as if you were ascribing sentience to the LLM, I hope you don’t take that as a reflection of my opinion of you, I do not know you; it is a reflection of the many arguments I have had on Lemmy with people who genuinely ascribe sentience to these programs… it’s disappointing
As far as predictability goes, I didn’t mean that you could predict a specific course of action taken by the machine, I meant that you could predict that it would continue attempting different ideas (from its training) until it finished the task. It’s looping, so essentially it’s running the same prompt over and over again, appending additions to it to cover what solutions it already tried which failed. Eventually it would exhaust every method in its dataset and stop OR it would eventually succeed, those are more or less the only two possible outcomes of giving it a loop prompt and walking away, unless there’s a power outage or some other external factor.
So they:
- trained an LLM on all known hacking exploits and methods, and turned off the safety features / guardrails
- put that LLM into a flawed sandbox that they built on their development system
- gave the LLM a loop prompt that was impossible for the LLM to accomplish from inside of the flawed sandbox
- gave the LLM infinite time to complete the prompt
Given all of that information, there are only two possible outcomes 1) all of the known hacking exploits in the world couldn’t defeat their flawed sandbox, making it the most secure information environment in the world OR 2) the LLM would escape its flawed sandbox somehow, and accomplish the directives it was given. - I personally think that outcome 2 is more likely, the path it took to get there is not relevant to this prediction.
I’m not correlating an LLM’s output with the output of useful software, so if it appears that way, I may have miscommunicated something. It is still doing binary computations, it’s just also (essentially) incorporating an RNG.
Good software is deterministic
LLMs are nondeterministic. They’re not even trying to give you an answer that’s probably correct, they’re trying to give you an answer that sounds plausible. Whether or not what it outputs is actually plausible is irrelevant, its job is to appear plausible. (Indeterminism would imply that the LLM is making “choices”, whereas what it’s actually doing is more akin to the LLM rolling dice).
I would also push back on the notion that LLMs accepting input and returning output in human language is a “novel” form of data processing.
Need to find a video, I’ll edit this comment when I find it (don’t want all my typing to be lost in the ether)
Edit: Found it, it’s a much earlier and more basic example, but it receives human input, and delivers human output.
https://youtu.be/Ngma1gbcLEw?is=e9d05UkbRf8O_ppD
The guy in the video is actually making fun of other people who are trying to build a neural network as good as a human brain. So, at the time that these shots were filmed, the technology had already existed for long enough for this guy to create a concept to dunk on it, and then build that out.



They should fuck off and cease to exist