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BirbSingularity 6 hours ago [-]
I can't help but think of orthogonal frequency-division multiplexing and it's use in encoding data on multiple carrier frequencies, and it makes me wonder what other parallels we will discover between digital transmission technology for cross-domain stuff like this.
dapperdrake 5 hours ago [-]
Not even cross-domain. (Nor cross-co-domain.)
Trigonometric polynomials are also polynomials. And linear spaces are all "the same". That is what the definition is for. Even the transpose-mapping is linear.
chimpanzee2 40 minutes ago [-]
I have this strange sensation that I can't put into words that somehow we are on the brink of unveiling an entirely new paradigm of AIs or perhaps even of combining AI with classical algorithms in a way to rapidly iterate between each other (and sensor data) that will instantly 10x or 100x current capabilities.
Anyone else feel this?
cyanydeez 37 minutes ago [-]
no. we're approach a sigmoid. AI is bloated carcass and we're tweaking out the size of the models and speed they'll run on smaller hardware.
I think to feel what you're feeling, you've bought into "all we need is more context". I think evolution demonstrates that's not really true.
chimpanzee2 28 minutes ago [-]
would you really bet that this is it? there is nothing beyond this?
reminds me of the famous anecdote of a 19th century physics professor who said "there is nothing left to be discovered in physics, only minor corrections"
Trigonometric polynomials are also polynomials. And linear spaces are all "the same". That is what the definition is for. Even the transpose-mapping is linear.
Anyone else feel this?
I think to feel what you're feeling, you've bought into "all we need is more context". I think evolution demonstrates that's not really true.
reminds me of the famous anecdote of a 19th century physics professor who said "there is nothing left to be discovered in physics, only minor corrections"
then came Einstein...