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Awesome, you did understand the reference I made, I was afraid I was too sneaky about it but seems it was just clear enough :)
Of course! That point in the guidelines has links to some prior art in this vein. Highly recommend it for you. And please, do better next time!
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> LLMs do reason No, they don't. They are token predictors that use statistical techniques to emit the randomly weighted next most likely token given the previous token list. The result is a strange mimic of human reasoning, because the tokens it predicts are trained on strings that were produced by humans that were reasoning, but that's not the same thing. Human cognition is complex and poorly understood, and the na…
> They are token predictors that use statistical techniques to emit the randomly weighted next most likely token given the previous token list. Sounds like an implementation detail. Now describe how human reasoning works and explain why that process of chemical and electrical signals results in "reasoning" whereas what LLMs do isn't. The problem with being this reductive is you can do it to anything, including humans…
For an example, look at some of Julia Mossbridge's work.
If even a small part of her work is true and valid, it points to something far outside our current framework.
You don't need to go as far afield as Mossbridge, though - that's an extreme example. Pretty much any modern neuroscience will make you question a lot of assumptions, at least it did for me.
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You have moved goalposts from reasoning to "human cognition". I won't tolerate that sort of slippery wordplay. Reasoning is making analogies between logical patterns found in conceptual space, with a direction of time (statements precede conclusions). For example. A => B and B => C. You may now deduce A => C. For something fuzzier, A~D and B~E, you may now deduce that D~=>E. This is the sort of thing that higher laye…
Reasoning requires cognition, otherwise there's nothing to reason about, no context or value system to use as a basis for reason. Decision making can be done by trained machines following rules, but that's different that reasoning. A thermostat isn't reasoning when it decides to turn on the air conditioner, to argue otherwise expands the definition of "reason" to be so broad that it becomes useless. LLMs are trained…
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Wow, there are still people trying to claim they don't reason. What will they have to do before you'll admit that they can?
You are asking the wrong question. It's not about if you can do X which can be faked especially if you are given practically infinite tries and all failures are hidden. The people who want to believe they actually reason just ignore all obvious evidence of contrary and cherry pick the times reasoning was faked well enough. The people who don't want to believe will just take a second to understand how they work and th…
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Unless you're writing kernels, or high integrity systems with memory allocation constrains there is very little reason to use a language like Rust. Everything that people find great on Rust with exception of the borrow checker, can be found in any compiled language from ML linage. And even that is fading away as they introduce a mix of linear types, dependent types, effects and formal logic.
Rust has uses you haven't mentioned. For example, each compiled language from the ML lineage (and almost every language period) has its own runtime, particularly, its own assumptions and contracts about heap-allocated storage. In contrast, Rust famously does not need a runtime library -- and it is low-level enough that it can usually (with enough cognitive effort by programmers) interface with an arbitrary foreign ru…
Likewise those Python program should have use a dynamic managed compiled language, like Common Lisp or Julia, which was originally designed exactly to avoid that.
Maybe one day replaced by Mojo, if they get lucky with it.
Too many devs see a specific language as their solution for everything, and when it doesn't fit we end up in such sandwiches.
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Reasoning requires cognition, otherwise there's nothing to reason about, no context or value system to use as a basis for reason. Decision making can be done by trained machines following rules, but that's different that reasoning. A thermostat isn't reasoning when it decides to turn on the air conditioner, to argue otherwise expands the definition of "reason" to be so broad that it becomes useless. LLMs are trained…
Why does reasoning require cognition? Isn’t a if else block or switch statement reasoning? Or a formal logic proof? If an LLM produces an output using formal logic or a python script why is that not reasoning? A human would offload the reasoning using similar methods. I know when I took the LSAT, I learned ways to diagram arguments and didn’t have to think/reason about it because the formal logic diagram did the “rea…
Agreed but I would frame it in the negative, "don't worry about overfitting, the lucky ticket hypothesis just works "
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Reasoning requires cognition, otherwise there's nothing to reason about, no context or value system to use as a basis for reason. Decision making can be done by trained machines following rules, but that's different that reasoning. A thermostat isn't reasoning when it decides to turn on the air conditioner, to argue otherwise expands the definition of "reason" to be so broad that it becomes useless. LLMs are trained…
Can you give a concrete example of something that is impossible for an LLM to ever do due to its lack of reasoning ability.
In the meantime, these [1] are pretty funny.
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Of course! That point in the guidelines has links to some prior art in this vein. Highly recommend it for you. And please, do better next time!
Whenever I make joke reference to the guidelines, I do promise I'll attach a link to them, just to make it extra clear, thanks! :)
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> They are token predictors that use statistical techniques to emit the randomly weighted next most likely token given the previous token list. Sounds like an implementation detail. Now describe how human reasoning works and explain why that process of chemical and electrical signals results in "reasoning" whereas what LLMs do isn't. The problem with being this reductive is you can do it to anything, including humans…
Human cognition is poorly understood and much more complex than it seems. For an example, look at some of Julia Mossbridge's work. If even a small part of her work is true and valid, it points to something far outside our current framework. You don't need to go as far afield as Mossbridge, though - that's an extreme example. Pretty much any modern neuroscience will make you question a lot of assumptions, at least it…
Never heard of her but I just spent about 5 minutes looking.
Her PhD is in communication sciences and disorders [1], but apparently she’s a quantum physicist now:
> AMELIA is built on the Causally Ambiguous Duration-Sorting (CADS) effect — a breakthrough discovery by Dr. Julia Mossbridge showing that light, under classical boundary conditions, behaves differently based on future temporal boundaries. [2]
Filed under crank, not going to bother investigating further.
[1] https://books.google.com/books/about/Have_a_Nice_Disclosure....