The manifold hypothesis posits that many high-dimensional data sets that occur in the real world actually lie along low-dimensional latent manifolds inside that high-dimensional space. As a consequence of the manifold hypothesis, many data sets that appear to initially require many variables to describe, can actually be described by a comparatively small number of variables, likened to the local coordinate system of the underlying manifold. It is suggested that this principle underpins the effectiveness of machine learning algorithms in describing high-dimensional data sets by considering a few common features.
For new cultivators I don't recommend forming your mana core using air mana (breath meditation). It's a classic and has some nice skill unlocks but you can always put spare skill points into those later. Instead, I recommend cultivating factors of cultivation for the exp gains.
Knowledge is the architecture independent representation of models, it’s one of the most important paths out of the current paradigm of Too Large Language Models
@utotranslucence i have some lived experience, and may be of some help ~* please feel free to reach out and let me know if and how i may contribute to your efforts.
@utotranslucence thank you for sharing a part of your story Jess. this is important and serious work. i imagine your experience has been heart-wrenching at times, marked with desolation and pain. your strength, and perseverance, is inspiring.
Mythologies as a technology:
truth - a perspective
Truth - a mythology: self consistent truths together forming One
Verity / Veritas - collection of all veritable Truths
the universe seems be doing at least two things:
1) maximizing qualia
2) minimizing description length
the balance / equilibrium between these two is existence: autopoesis.