high-dimensional sampling

Richard Hamming's 1995 lecture on n-dimensional space, showing how geometric intuition about spheres and cubes breaks down in high dimensions. It is part of his course on learning to learn.

Michael Betancourt's lecture at MLSS Iceland 2014 on efficient Bayesian inference with Hamiltonian Monte Carlo. It covers MCMC concepts and motivation and the problems of sampling in high-dimensional distributions.

Zach Hartwig of MIT introduces the key concepts of magnetic fusion energy and the state of fusion research. He then presents MIT's proposed pathway of using high-field superconducting magnets to build smaller, cheaper tokamaks on a climate-relevant timescale.

Rick Hartley gives a roughly two-hour live training on proper grounding in PCB design. He explains how energy actually flows in the space between conductors, and how that governs noise, EMI, return paths and signal reflections.

Casey Muratori's University of Twente guest lecture is a case study in how straightforward code can cut thousands of lines and tens of seconds of runtime down to a few dozen lines running in under a second. It uses concrete examples to show why software is often an order of magnitude slower than it should be.

Doug McGuff presents the biochemistry behind high-intensity strength training and the paleo diet, including how the body stores and burns fat. It is a roughly hour-and-a-half full-length lecture.

A segment from Carl Sagan's original Cosmos explaining the fourth spatial dimension through analogy with a two-dimensional world and shadow projection.

Lecture 1 of Harvard's Statistics 110 with Joe Blitzstein, introducing sample spaces, the naive definition of probability, counting, binomial coefficients and the sampling table.

Andrej Karpathy's first Neural Networks: Zero to Hero lecture, which builds micrograd, a tiny autograd engine, from scratch in Python. It explains backpropagation and neural network training step by step, assuming only basic Python and some high-school calculus.

A Royal Institution event with Sean Carroll and Jennifer Ouellette on what happens if you fall into a black hole, covering the firewall paradox, the information problem and the holographic principle.

The first lecture of Stanford's CS107 Programming Paradigms, taught by Jerry Cain, giving an overview of the course. The course goes from C and assembly through C++, concurrency, Scheme and Python.

An ESOTERICA episode tracing Yahweh from a warrior-storm god near Mt Seir to the god of the Israelites in the Judean highlands. It examines how Yahwism absorbed and contended with Canaanite religion.

The first lecture of Stanford's Natural Language Processing with Deep Learning course, taught by Chris Manning and Richard Socher. It introduces NLP and word vectors, including SVD, skip-gram, CBOW, negative sampling and word2vec.

Erik Demaine's MIT 6.851 Advanced Data Structures lecture introducing succinct data structures, covering rank, select and tries. It is part of the Spring 2012 course.

A Royal Institution lecture in which Nicholas Humphrey presents his theory of phenomenal consciousness and its evolution. He draws on the book Sentience and discusses evidence for animal sentience.

Neuroscientist Karl Friston gives a 15-minute talk on the free energy principle, covering Markov blankets, Bayesian model evidence and global brain theories.

A 1990 lecture by James Gosling on NeWS, Sun's networked window system in which clients send PostScript programs to the server for execution. It covers the high-level imaging model and compares NeWS with similar systems.

Nathan Kutz presents the spatio-temporal dynamics of rotating detonation rocket engines, including combustion fronts that behave like solitons. He shows a bifurcation analysis of a multiscale model that captures the main features.

A lecture for high school seniors and college freshmen making the case for nuclear power and answering common objections. It is an overview of the channel's more detailed videos on each topic.

A guest lecture Jon Gjengset gave at Two Sigma on using Rust for large, high-performance systems. It covers why Rust suits such projects, the Noria research database, a concurrent data structure used in it, and practical experience.

The second talk in the Mill CPU series by Mill Computing, covering the Belt, the Mill's operand-passing model that replaces general registers. It explains the cost of register renaming in conventional wide CPUs and how the Belt reaches high instruction-level parallelism.

Royal Institution lecture by Dr Kate Lancaster on the most powerful lasers in the world and the extreme conditions they create. It includes live demonstrations and covers applications from industry to fusion.