computer vision

Mike Pound explains the discrete cosine transform and how it underpins JPEG compression. It is part two of Computerphile's JPEG series.

A Computerphile video in which Dr Mike Pound and PhD student Lewis Stuart explain 3D Gaussian splatting, a quick technique that turns photos of a scene into a 3D model without much compute. It includes a demo and compares the approach to NeRFs.

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.

Veritasium visits the US Navy's Crane facility to test top night vision goggles. It explains how image intensifier tubes and thermal or digital systems work and compares the generations of the technology.

FortNine looks at why Tesla Autopilot has rear-ended motorcyclists, speculating that the vision system misreads motorcycle taillights as a distant car. It argues that radar and other sensors would help.

Rob Miles explains "glitch" tokens, odd strings in large language model vocabularies that make the model produce gibberish. He covers how they likely arise from tokenizer training data, such as Reddit usernames, that never appeared in the model's own training.

Steve Mould explains motion amplification and video magnification, techniques that find tiny changes in video invisible to the eye and exaggerate them. He covers the MIT research and industrial uses such as diagnosing vibrating machinery.

Tom Scott explains for Computerphile why handling time and timezones in code is so hard, walking through a simple web app that computes how long ago something happened. It covers the quirks of timezones and calendars and ends in an exasperated rant.

Tom Scott explains for Computerphile why electronic voting is a bad idea, arguing that paper ballots are transparent, auditable and hard to tamper with at scale. He covers why moving voting to phones, tablets or computers undermines trust and verifiability.

Tom Scott explains for Computerphile how Unicode and UTF-8 grew out of messy older character encodings to become the web's standard. It covers why the design works and how it handles worldwide text.

Dr Mike Pound of Computerphile shows how a modern laptop can crack Enigma, using a ciphertext-only attack based on an older paper. He compares it with the tooling in CrypTool.

Rob Miles explains on Computerphile why implementing an off switch for a general AI is hard. A capable agent would resist being stopped because shutdown prevents it from achieving its goal.

Computerphile interview with Prof. Ross Anderson on how Chip and PIN payment systems are being compromised, and the attacks researchers have seen.

Tom Scott explains for Computerphile how floating point numbers work, why moving the binary point is fast, and why it handles money badly.

A Computerphile video in which Mark Jago of the University of Nottingham explains Turing's halting problem and how it led to the blueprint for the modern computer.

Computerphile video in which Mike Pound explains a University of Maryland paper on watermarking LLM output. The method biases token choices so generated text can later be detected statistically.

Rob Miles discusses GPT-3 on Computerphile, covering how scaling parameters kept improving results over GPT-2 and how the model nearly learned arithmetic without anyone knowing exactly how.

Ben Eater explains why he builds computers on breadboards, including testing their signal behavior on an oscilloscope. It is a companion to his 6502 breadboard computer series.

Technology Connections explains how analog television produced moving images without computers, covering scanning, CRTs and standards like NTSC and PAL. It is part of a series on analog TV.

Professor Brailsford of the University of Nottingham describes how the university set out to print its own mathematics exam papers in the 1980s. The story centers on getting a Mergenthaler Linotron 202 typesetter to work with their own software.

The first of four short videos from Bill Hammack (engineerguy) introducing and giving the history of a 100-year-old mechanical computer, Michelson's harmonic analyzer. The series goes on to explain Fourier synthesis, analysis and operation of the machine.

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.

Veritasium traces analog computers from the Antikythera mechanism and Kelvin's tide-predicting machines to fire control and modern analog approaches. It explains how these machines computed continuously rather than digitally.

A PBS Infinite Series episode explaining the mathematics of quantum computers, including how qubits store complex numbers and how quantum computation differs from classical computation. Hosted by Kelsey Houston-Edwards.

An Asianometry explainer on why the Soviet Union, once a leading computing power, fell far behind the US in computers by the 1980s. It traces the gap from the 1960s onward despite strong state support for science.

Scott Manley tells the story of a computerized telemetry system built to sit at the heart of a nuclear test device in place of the plutonium pit, designed to transmit data in the microseconds before it was destroyed.

A Computerphile video in which Rob Miles warns against assuming a general AI will think like a human. He uses the thought experiment of a stamp-collecting AI to show how a goal-driven system could pursue its aim with dangerous results.

Rob Miles explains for Computerphile why simple rule sets like Asimov's Three Laws cannot make robots and AI safe. Terms like harm and human are too ambiguous to specify precisely.

A 36-minute animated deep dive from Branch Education into how DRAM works. It shows how memory connects to the CPU and how billions of bits are stored in nanoscale capacitor cells. It also covers why DRAM sits between SSDs and the processor.

MinutePhysics explains Shor's algorithm, showing how a quantum computer factors large integers by finding the period of a number modulo N. It walks through the modular arithmetic and number theory that give the exponential speedup over classical factoring, and why this threatens encryption.

Technology Connections takes apart a 1970 Wurlitzer 3400 jukebox to show how electromechanical relays and switches automated its behavior without a computer.

Veritasium explains how cosmic rays and other particles flip bits in computer memory, with examples including a Belgian election count error, plane incidents and game glitches. It is inspired by a RadioLab episode on bit flips.

Dr Mike Pound explains the suspected backdoor in the Dual_EC_DRBG random number generator and how elliptic curve constants could let someone predict its output.

Huygens Optics explains the Fourier transform and shows how a lens performs one optically. A DLP projector is used as a Fourier filter to do simple pattern recognition on lithographic character patterns.

MinutePhysics explains that computers store brightness nonlinearly, so blurring and blending colors in raw RGB gives wrong, dark results. It shows why mixed colors, such as in gradients, look off.

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.

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.

Tom Scott visits the Swiss Military Museum to see the last surviving 1970s tank-driving simulator. It uses a real camera moving over a miniature model landscape rather than any computer graphics.

Matt Parker of Stand-up Maths explains single-pile Nim and the trick that wins it, using Dr NIM, a 1960s mechanical plastic computer that plays perfectly. He teaches the strategy so viewers can beat friends.

Isaac Arthur explains the Matrioshka Brain, a hypothetical computer or artificial mind powered by an entire star using nested shells. It covers how such megastructures relate to Dyson spheres and superintelligence.