mathlib3

fassistants.stackexchange.com/ Perhaps to understand LLMs and application, e.g. the Cuttlefish algorithm fills in an erased part of an image; like autocomplete; so, can autocomplete and guess and check (and mutate and crossover; EA methods and selection, too) test [math] symbolic expression trees against existing labeled observations that satisfy inclusion criteria, all day and night in search of a unified model with greater fitness?

Lean-related. [1]: https://wwwf.imperial.ac.uk/~buzzard/xena/natural_number_gam... [2]: https://leanprover-community.github.io/ [3]: https://github.com/leanprover-community/mathlib [4]: https://leanprover-community.github.io/undergrad.html [5]: https://leanprover-community.github.io/mathlib-overview.html [6a]: https://github.com/leanprover-community/lean-liquid [6b]: https://www.nature.com/articles/d41586-021-01627-2 [7]: https://leanprover.zulipchat.com/

than Bayesian networks (or other conventional approaches) for the purpose of interfacing basic probabilistic inference with these other sorts of inference. In addition, the inference rules are formulated in such a way as to avoid the paradoxes of Dempster–Shafer theory. Has anybody already taught / reinforced an OpenCog [PLN, MOSES] AtomSpace hypergraph agent to do Linked Data prep and also convex optimization with AutoML and better than grid search so gradients? Perhaps teaching users to bias analyses with e.g. Yellowbrick and the sklearn APIs would be a good curriculum traversal? opening/baselines "Logging and vizualizing learning curves and other training metrics" https://github.com/openai/baselines#logging-and-vizualizing-... https://en.wikipedia.org/wiki/AlphaZero There's probably an awesome-automl by now? Again, the sklearn interfaces. TIL that SymPy supports NumPy, PyTorch, and TensorFlow [Quantum; TFQ?]; and with a Computer Algebra System something for mutating the AST may not be necessary for symbolic expression trees without human-readable comments or symbol names? Lean mathlib: https://github.com/leanprover-community/mathlib , and then reasoning about concurrent / distributed systems (with side channels in actual physical component space) with e.g. TLA+. There are new UUID formats that are timestamp-sortable; for when blockchain cryptographic hashes aren't enough entropy. "New UUID Formats – IETF Draft" https://news.ycombinator.com/item?id=28088213 ... You can host online ML algos through SingularityNet, which also does PayPal now for the RL.