measurablefunc

36 ms·

901.
by measurablefunc 1y ago
You don't have to imagine, there is a logically rigorous argument¹ that establishes the equivalence. There is also nothing unusual about neural networks or Markov chains. You've just been mystified by the marketing around them so
902.
by measurablefunc 1y ago
If there are no logical errors then you're just waving your hands which, again, you're welcome to do but it doesn't address any of the points I've made in this thread.
903.
by measurablefunc 1y ago
I prefer logic to hype. If you have a reason to think the hype nullifies basic logical analysis then you're welcome to your opinion but I'm going to stick w/ logic b/c so far no one has presented an actual counter-argume
904.
by measurablefunc 1y ago
Where is the logical mistake in the linked argument? If there is a mistake then I'd like to know what it is & the counter-example that invalidates the logical argument.
905.
by measurablefunc 1y ago
It's definitely something but it might not be apparent to those who do not understand the distinctions between intensionallity & extensionallity.
906.
by measurablefunc 1y ago
> Empirical evaluations demonstrate that our proposal significantly enhances the reasoning capabilities of LLMs, achieving a performance gain of over 40% compared to the optimal-path supervised fine-tuning method.
907.
by measurablefunc 1y ago
> As noted, you can keep all the same variables as a regular Sudoku solver What are those variables exactly?
908.
by measurablefunc 1y ago
Where is this spelled out formally and proven logically?
909.
by measurablefunc 1y ago
Choice-free feedforward graphs are LLMs. The inputs/outputs are extensionally equivalent to context and transition probabilities of a Markov chain. What exactly is your argument b/c what it looks like to me is you're simply m
910.
by measurablefunc 1y ago
Loop around an LLM is not an LLM.
911.
by measurablefunc 1y ago
My point is that your initial argument was missing several key pieces & if you specify the entire state space you will see that it's not as simple as you thought initially. I'm not saying it can't be done but that it&#x27
912.
by measurablefunc 1y ago
That still won't work b/c there is no backtracking. The point is that there is no way to encode backtracking/choice points like in Prolog w/ a Markov chain. The argument you have presented is not extensionally equivalent
913.
by measurablefunc 1y ago
There are multiple solutions for each incomplete grid so how are you calculating the transitions for a grid w/ a non-unique solution? Edit: I see you added questions for the ambiguities but modulo those choices your solution will almos
914.
by measurablefunc 1y ago
How are you encoding the state spaces for the sudoku solver specifically?
915.
The Fever Dream of Imminent Superintelligence Is Finally Breaking(nytimes.com)
14 points by measurablefunc 1y ago|0 comments
916.
by measurablefunc 1y ago
Same thing it does about their ability to drive cars.
917.
by measurablefunc 1y ago
If you think it is possible then I'd like to see an implementation of a sudoku puzzle solver as Markov chain. This is a simple enough problem that can be implemented in a few dozen lines of Prolog but I've never seen a solver impl
918.
by measurablefunc 1y ago
I don't expect a Markov chain to be capable of backtracking. That's the point I am making. Logical reasoning as it is implemented in Prolog interpreters is not something that can be done w/ LLMs regardless of the size of thei
919.
by measurablefunc 1y ago
If you think there is a mistake in this argument then I'd like to know where it is: https://markov.dk.workers.dev/ .
920.
by measurablefunc 1y ago
What part about backtracking is baseless? Typical Prolog interpreters can be implemented in a few MBs of binary code (the high level specification is even simpler & can be in a few hundred KB)¹ but none of the LLMs (open source or not)
921.
by measurablefunc 1y ago
There is a formal extensional equivalence between Markov chains & LLMs but the only person who seems to be saying anything about this is Gary Marcus. He is constantly making the point that symbolic understanding can not be reduced to a
922.
by measurablefunc 1y ago
It's b/c when Chomsky invented the theory of formal grammars he was studying natural languages & the universality of abstract grammar¹. Computer scientists realized later that they could use the same theory as a foundation for
923.
by measurablefunc 1y ago
It's unfortunate so many publicly elected representative do not understand basic facts about vaccines & immunity.
924.
by measurablefunc 1y ago
They have contracts w/ the military but I am certain these safety considerations do not apply to military applications.
925.
by measurablefunc 1y ago
If the goal is to recreate the training data set then all functional approximations are extensionally equivalent modulo biases introduced by the architecture. What I mean by architectural bias is how missing pieces of the data manifold are
926.
Every Implementable Algorithm Is Extensionally a Lookup Table(table.dk.workers.dev)
1 points by measurablefunc 1y ago|0 comments