In the context of general relativity and the canonical formulation of the theory, the Hamiltonian constraint is a fundamental equation that arises in the process of quantizing gravity. It plays a key role in the framework known as Hamiltonian formalism or the ADM (Arnowitt-Deser-Misner) formulation of general relativity.

A **Cauchy surface** is a concept used in the context of general relativity and differential geometry, particularly in the study of spacetime. It is a type of hypersurface that has important implications for the determination of the evolution of physical fields and signals in spacetime.

Self-play is a training technique used primarily in artificial intelligence and machine learning, particularly in the development of algorithms for games and strategic decision-making. In self-play, an AI system plays against itself instead of competing against human opponents or other external agents. This approach allows the AI to explore a wide range of strategies and scenarios without the need for external data.

A corrosion inhibitor is a chemical substance that, when added in small amounts to a corrosive environment, significantly reduces the rate of corrosion of metals or alloys. Corrosion is the natural process where metals deteriorate due to reactions with their environment, often involving moisture, oxygen, salts, or acids. Corrosion inhibitors work by various mechanisms, such as: 1. **Surface Film Formation:** Some inhibitors form a protective film on the metal surface, preventing corrosive agents from contacting the metal.

The NLGI (National Lubricating Grease Institute) consistency number is a standardized classification system used to describe the thickness or viscosity of lubricating grease. This classification helps users select the appropriate grease for specific applications by providing a measure of its consistency.

Accumulated Local Effects (ALE) is a statistical technique used primarily in the context of interpreting machine learning models, particularly those that are complex and difficult to understand, such as ensemble methods or neural networks. ALE provides insights into how the predicted outcomes of a model change as individual features (or variables) are varied.

Ludwig Wittgenstein's philosophy of mathematics is primarily presented in his later work, particularly in "Philosophical Investigations" and "Remarks on the Foundations of Mathematics." His approach represents a significant departure from traditional philosophical views of mathematics, emphasizing the role of language, use, and social practices.

The Dominance-Based Rough Set Approach (DRSA) is a methodology used in decision-making processes, particularly within the fields of data mining, machine learning, and multi-criteria decision analysis. It integrates the concepts of rough set theory and dominance relations to handle uncertainty and vagueness in decision-making.

Error-driven learning is a type of learning that emphasizes the importance of errors in the educational process. It involves using mistakes or deviations from desired outcomes as a catalyst for improvement and adaptation. This approach is often applied in various fields, including machine learning, cognitive psychology, and education. Here are some key aspects of error-driven learning: 1. **Feedback Mechanism**: Errors serve as feedback that indicates where a learner or a system has deviated from the expected path.

An Alias in macOS is a type of shortcut that provides a quick way to access a file, folder, or application without needing to navigate to its original location on your hard drive. When you create an alias, it creates a small file that points to the original item but does not duplicate the content itself. You can create an alias in macOS by right-clicking (or Control-clicking) on an item and selecting "Create Alias" from the context menu.

www.youtube.com/playlist?list=PLVV0r6CmEsFzCodipONmNiROhYCUWyz_U interview with Walter Murch by Web of Stories. He worked on sound design for all The Godfather films, and tells some interesting details about it. He's just super nice in general otherwise. E.g.: