network 1976

An 8-minute explainer on the Lightning Network and how it relates to Segwit, Bitcoin and Litecoin. It covers how off-chain payment channels route payments to scale blockchain transactions.

3Blue1Brown's first chapter on deep learning explains what neurons and layers are and the math underlying a basic neural network, using handwritten digit recognition with visual animations.

Two Minute Papers covers a paper on speeding up fluid and smoke simulation with convolutional networks. It contrasts the approach with earlier regression forest methods.

3Blue1Brown's second neural network chapter explains cost functions and gradient descent, showing how a network learns by minimizing error during training.

Mark Handley of UCL explains, with simulation visualizations, how early Starlink satellites without inter-satellite links could still give low-latency wide-area communication by hopping via ground relays. He shows it can beat fibre on many long paths.

Tom 7 (suckerpinch) delivers a long, comedic digression on gradient descent and floating-point imprecision. He shows how rounding behavior can supply the nonlinearity needed to build a neural network.

Veritasium explains why analog computing may suit AI workloads, covering old analog computers, The Analog Thing and Mythic's analog chips that use flash memory for neural network inference. It argues digital hardware is hitting limits.

3Blue1Brown's third deep learning chapter gives a visual, intuitive account of backpropagation and what happens to a neural network as it learns. A follow-up video covers the underlying calculus.

Mark Handley of UCL looks at how SpaceX's November 2018 revisions to the Starlink constellation affect network behavior. The video visualizes the orbits and routing and estimates latencies, building on his earlier video and research paper.

A short cartoon explaining how language models like ChatGPT work, from autocomplete and conditional probabilities to neural networks, gradient descent and backpropagation. It shows how networks act as universal function approximators.

3Blue1Brown's chapter 4 on deep learning gives a more formal, symbol-based account of backpropagation calculus, connecting the intuition from the previous chapter to the math found in textbooks and code.

Harvard professor Arthur Brooks explains why boredom is useful rather than something to avoid. He describes how a wandering mind engages the brain's default mode network, which supports creativity and curiosity, and suggests it may protect against depression.

A Welch Labs explainer on neural scaling laws and the compute-efficient frontier, asking why model loss seems to hit a line it cannot cross. It draws an analogy to an ideal gas law for AI.

Branch Education explains how Starlink works, from the ground dish and satellites to phased-array beam steering and data routing. Animations cover how a beam stays connected to a satellite moving at 27,000 km/h.

A two-minute clip in which Milton Friedman uses a humble pencil to show how thousands of strangers across many countries cooperate, without central direction, to make a simple product. It is a short visual version of the 'I, Pencil' essay's argument about free markets and dispersed knowledge.

Autoline's John McElroy and Caresoft president Terry Woychowski look at the BYD Seagull, an electric hatchback that sells in China for about $11,500. Woychowski points out the cost-saving design and manufacturing choices, and McElroy takes it for a short test drive.

Real Engineering explains how Zipline built a drone delivery network for medical supplies in Rwanda. It covers the fixed-wing drones, catapult launch, parachute drop and the logistics behind the service.

Benn Jordan explains how Flock Safety's license plate cameras log and share vehicle locations, and explores how adversarial AI can defeat them. It covers weak security and the surveillance risks of private police-camera networks.

A Wendover Productions explainer on how China built the world's largest high-speed rail network so quickly and why its rail strategy differs from America's. It covers politics, social benefits and the economics of unprofitable lines.

A Kurzgesagt animation giving a big-picture tour of the human immune system, its organs, transport network, and the cells it produces every day. It accompanies their IMMUNE book.

Rob Miles explains on Computerphile how language models generate plausible text and how transformers improved on recurrent networks, with a look at what comes next.

A Two Minute Papers episode on NVIDIA's recurrent denoising autoencoder, which cleans up noisy Monte Carlo path-traced image sequences. It shows how a neural network can produce usable renders from very few samples.

Tom Scott explains Electrical Network Frequency analysis, where hum from the power grid in a recording is matched against grid logs to date and place it. He talks to a researcher and sets them a challenge.

A Vox explainer from the 2020 election series on why American public transit is so poor. It traces the effect of the interstate highway system on cities and the resulting car dependence.

A four-minute minutephysics video arguing that causal models and causal networks let statistics infer causation from correlation. It touches on Reichenbach's principle, common causes, feedback and quantum causal discovery.

Tom Scott visits Peachtree City, Georgia, which has about a hundred miles of dedicated golf cart paths that serve as an alternative to driving. He explains how the network works as a quasi-transit system that keeps cars off the roads.

CityNerd explains why traffic congestion grows nonlinearly as more cars use a road network, and why adding road capacity tends not to fix it. It covers the consequences for drivers, bus riders, cyclists and pedestrians, and discusses alternatives such as true bus rapid transit.