you will probably need to read a book or two to understand all that but it can get so many application that maybe you should actualy read them or wont lost time doing so :
Data structure, deep learning using topologie, lossless embeding, introduction to P vs NP and etc. A lot of ideas may emerge from this kind of work
humuhumu33•3mo ago
This framework gives you a playground to explore, manipulate, and apply the patterns that shape the universe’s most intricate structures, unlocking new possibilities in AI, quantum computing, and scientific discovery.
Link: https://www.uor.foundation/blog/universe
Greetings from Colorado, and we welcome any feedback.
humuhumu33•3mo ago
This just happens to match w/ original GPT-3 parameters below.
With the key difference that Atlas enables unique deterministic data addressing, which does not require expensive transformer training.
https://dugas.ch/artificial_curiosity/GPT_architecture.html
"Decoding. We're almost there! Having passed through all 96 layers of GPT-3's attention/neural net machinery, the input has been processed into a 2048 x 12288 matrix. This matrix is supposed to contain, for each of the 2048 output positions in the sequence, a 12288-vector of information about which word should appear."
graphtheory•3mo ago