AGI research remains empirical and lacks a foundational theoretical framework. A central tension exists between computationalism and undecidable problems, as AIXI illustrates. The author proposes that continuous causal embedding with the environment may be a missing axiom, and calls for discovering fundamental constraint principles that bound any physically realizable intelligence.

The theatrics of Anthropic, led by Dario Amodei, exhibit the quintessential characteristics of the Judaic Messianic narrative, whose structure typically proceeds as follows: the world confronts an immense crisis of which the majority remains unaware; only a select few prophets perceive the danger; these prophets must be entrusted with authority; and they shall deliver salvation to the world.

From a statistical learning perspective, modern neural networks can indeed be understood as a large-scale maximum likelihood estimation (MLE) process. Specifically, a neural network is a parameterized function, and the most common way to train a neural network is to perform maximum likelihood estimation on the data.

The core purpose of UAT (Universal Approximation Theorem) is that neural networks can approximate any continuous function, and continuous functions can be approximated by polynomials (Weierstrass theorem).

所有的战争与和平，爱恨与悲欢，都在这颗名为「地球」的微尘上，日复一日地上演。