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The Problem with Time & Timezones - Computerphile10:13

The Problem with Time & Timezones - Computerphile

4.4M views • 12 years ago
Computerphile
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.
Why Electronic Voting is a BAD Idea - Computerphile8:21

Why Electronic Voting is a BAD Idea - Computerphile

2.3M views • 11 years ago
Computerphile
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.
JPEG DCT, Discrete Cosine Transform (JPEG Pt2)- Computerphile15:12

JPEG DCT, Discrete Cosine Transform (JPEG Pt2)- Computerphile

697K views • 11 years ago
Computerphile
Mike Pound explains the discrete cosine transform and how it underpins JPEG compression. It is part two of Computerphile's JPEG series.
Characters, Symbols and the Unicode Miracle - Computerphile9:37

Characters, Symbols and the Unicode Miracle - Computerphile

2.1M views • 13 years ago
Computerphile
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.
Cracking Enigma in 2021 - Computerphile21:20

Cracking Enigma in 2021 - Computerphile

2.9M views • 5 years ago
Computerphile
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.
3D Gaussian Splatting! - Computerphile17:40

3D Gaussian Splatting! - Computerphile

273K views • 2 years ago
Computerphile
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.
AI Language Models & Transformers - Computerphile20:39

AI Language Models & Transformers - Computerphile

354K views • 7 years ago
Computerphile
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.
AI "Stop Button" Problem - Computerphile20:00

AI "Stop Button" Problem - Computerphile

1.4M views • 9 years ago
Computerphile
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.
Chip & PIN Fraud Explained - Computerphile8:45

Chip & PIN Fraud Explained - Computerphile

851K views • 11 years ago
Computerphile
Computerphile interview with Prof. Ross Anderson on how Chip and PIN payment systems are being compromised, and the attacks researchers have seen.
Floating Point Numbers - Computerphile9:16

Floating Point Numbers - Computerphile

2.5M views • 12 years ago
Computerphile
Tom Scott explains for Computerphile how floating point numbers work, why moving the binary point is fast, and why it handles money badly.
Ch(e)at GPT? - Computerphile13:52

Ch(e)at GPT? - Computerphile

617K views • 3 years ago
Computerphile
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.
GPT3: An Even Bigger Language Model - Computerphile25:57

GPT3: An Even Bigger Language Model - Computerphile

446K views • 6 years ago
Computerphile
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.
Typesetters in the '80s - Computerphile12:23

Typesetters in the '80s - Computerphile

105K views • 12 years ago
Computerphile
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.
Deadly Truth of General AI? - Computerphile8:30

Deadly Truth of General AI? - Computerphile

941K views • 11 years ago
Computerphile
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.
Why Asimov's Laws of Robotics Don't Work - Computerphile8:16

Why Asimov's Laws of Robotics Don't Work - Computerphile

873K views • 11 years ago
Computerphile
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.
The Great 202 Jailbreak - Computerphile19:55

The Great 202 Jailbreak - Computerphile

532K views • 12 years ago
Computerphile
Computerphile with Professor Brailsford on how a 1979 Bell Labs team reverse engineered a Linotron 202 phototypesetter over a summer to get high-quality print output. It covers typesetting history and the later 2013 rebuild of the famous vacation memo.
Turing & The Halting Problem - Computerphile6:14

Turing & The Halting Problem - Computerphile

919K views • 12 years ago
Computerphile
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.
ChatGPT with Rob Miles - Computerphile36:02

ChatGPT with Rob Miles - Computerphile

517K views • 3 years ago
Computerphile
Computerphile interviews AI safety researcher Rob Miles about ChatGPT: how it was trained with human feedback, why it tends to produce confident nonsense, and where it may or may not be dangerous.
Glitch Tokens - Computerphile19:29

Glitch Tokens - Computerphile

353K views • 3 years ago
Computerphile
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.
Where GREP Came From - Computerphile10:07

Where GREP Came From - Computerphile

1.3M views • 8 years ago
Computerphile
Brian Kernighan explains how grep came to be, written overnight by Ken Thompson, and how it got its name from the ed command g/re/p. He also covers the lineage from QED to ed that led to it.
Elliptic Curve Back Door - Computerphile12:24

Elliptic Curve Back Door - Computerphile

554K views • 8 years ago
Computerphile
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.