circuit networks

Steve Mould shows Spintronics, a set of mechanical components such as resistors, capacitors and transistors linked by chains, that give an intuitive feel for how electrical circuits work.

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

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 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.

Veritasium argues that electric energy is carried by fields around the wires rather than by electrons moving through them, using a thought experiment with a large circuit.

Polylog explains how algorithms can be turned into circuits and encoded as satisfiability problems, which lets you effectively run them backwards. It uses this to motivate breaking RSA, general reductions to SAT, and what P vs NP is really asking.

Veritasium explores how electrical energy actually travels in a circuit, arguing that it flows through electromagnetic fields around the wires rather than through the electrons. It builds a long-cable experiment with Caltech to test when a distant bulb lights.

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.

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.

AlphaPhoenix uses a custom high-speed measurement setup to watch voltage waves travel down wires and split at a fork. It answers how electricity knows where to go and how quickly that process happens.

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.

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.

ElectroBOOM's Mehdi Sadaghdar responds to Veritasium's lamp-and-long-wire puzzle, analysing it as an electrical engineer. He covers where the original framing misleads and the role of stray capacitance.

Technology Connections explains why electric kettles are uncommon in the US, centering on 120V circuits limiting power. He tests ways of boiling water on gas, electric ranges and kettles.

Big Clive tears down the Dubai lamp, a Philips LED bulb developed with Dubai's ruler for maximum efficiency and long life. He examines its construction and circuitry, including underrun LEDs and many filament strips.

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.

Technology Connections explains weaknesses in the US electrical system, centering on how cord and circuit ratings can mismatch and cause fires. It covers extension cords, power strips and plug history in about 25 minutes.

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 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.

The Signal Path takes apart a Starlink dish layer by layer, analyzing the phased array RF design, system architecture and integrated circuits, with an X-ray of the RF stack.