marshfarm

12 ms·

1.
by marshfarm 11mo ago
Without being a dualist, we can say from neurobiology, ecological psych, coord dynamics, neural reuse that meaning isn't simply upstream. Technically it can't be because of the language problem is post-hoc. You're an engineer
2.
by marshfarm 11mo ago
Words are merely wax fruit metaphors for meaning, they aren't meaningful in and of themselves. That's how dictionaries exist. Any reality understood from words is mere simulation.
3.
by marshfarm 11mo ago
The idea of meaning is contradictory, it's not strictly an illusion. There's a huge difference. State changes mean differences, they don't ensure meaning. This is an obvious criteria. We have tasks and the demands are variabl
4.
by marshfarm 11mo ago
Thought is wordless. It's made in action-spatial syntax. As these are the defined states of intelligence, this would have been a far better approach to emulate. Words and images are the equivalent of junk code. Semantics can;t be speci
5.
by marshfarm 11mo ago
There's much more meaning than can be loaded into statements, thoughts, etc. And conscious will is a post-hoc after effect. Any computer has far less access to the meaning load we experience since we don't compute thoughts, though
6.
by marshfarm 11mo ago
This was wonderful, thank you for posting, I learned so much.
7.
by marshfarm 11mo ago
Action patterns in syntax? They already exist, the binary chose to forgo that level emulation for arbitrary words, in arbitrary symbols, predicted, geometrically arranged in space as "meaning" as tokens. I'd suggest comp sci
8.
by marshfarm 11mo ago
We're probably post-narrative and post-lexical (words) but haven't become aware of what to possibly update these tools with. Post-truth is an abstraction rooted in the arbitrary. Reality is specific. Actions, materials. Words and
9.
by marshfarm 11mo ago
I think the best way would have been to assume thought is wordless (as the science tells us now), and images and probability (as symbols) are still arbitrary. That was the threshold to cross. Neither neurosymbolic, nor neuromorphic get ther
10.
by marshfarm 11mo ago
> They respond in much smarter ways than traditional multi-layer perceptrons or traditional RNNs like LSTM networks because their attention mechanisms helps them to make much better sense of the input they were provided by selectively pa
11.
by marshfarm 11mo ago
Was a mistake from the beginning to use language as the basis for tokens and embedded spaces between them to generate semantics. It wasn't thought out, it was a snowball trial and error that went out of control.
12.
by marshfarm 11mo ago
The effect is easy to grasp, we're moving away from Pleistocene communication technology, which is benchmarked in dated tools like reading, math, SAT/ACT scores. Human intelligence isn't going away, another form of expression
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by marshfarm 11mo ago
You can start here, sports and cinema combined create the syntax of language as a code. https://www.routledge.com/The-Constraints-Led-Approach-Princ...