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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.
Large Language Models from scratch8:25

Large Language Models from scratch

375K views • 4 years ago
Graphics in 5 Minutes
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.
Does the language you speak change how you think?5:25

Does the language you speak change how you think?

1.6M views • 3 years ago
Tom Scott
Tom Scott, with linguists Gretchen McCulloch and Molly Ruhl, examines whether the language you speak changes how you think. The short answer is mostly no, with caveats about the weak version of the Sapir-Whorf hypothesis.
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.
The surprising pattern behind color names around the world6:46

The surprising pattern behind color names around the world

8.4M views • 9 years ago
Vox
Vox explains the Berlin and Kay research showing that languages around the world tend to invent color words in the same order. It walks through the hierarchy and the debate around it.
Topic match · Language & linguistics
why typing like this is sometimes okay.4:31

why typing like this is sometimes okay.

5.4M views • 7 years ago
Tom Scott
Tom Scott makes a short descriptivist argument that language keeps changing and that casual internet writing conventions, like lowercase typing and dropped full stops, are legitimate. It is part of his Language Files series, written with Gretchen McCulloch.
Topic match · Language & linguistics
Can Japanese Actually Write Japanese Kanji?5:49

Can Japanese Actually Write Japanese Kanji?

5.5M views • 10 years ago
That Japanese Man Yuta
Yuta asks whether native Japanese speakers can actually write kanji by hand, showing that many struggle to recall characters from memory.
Topic match · Language & linguistics
Why are British place names so hard to pronounce?8:14

Why are British place names so hard to pronounce?

6.6M views • 5 years ago
Map Men
The Map Men explain why British place names are so hard to pronounce, tracing it to layers of Viking, Anglo-Saxon, Celtic and Norman influence, with a pronunciation guide.
Topic match · Language & linguistics
PHP doesn't suck (anymore)10:48

PHP doesn't suck (anymore)

223K views • 3 years ago
Aaron Francis
Aaron Francis walks through how PHP has changed from 2012 to 2023, covering traits, array destructuring, generators, typed properties and more. It is a quick chaptered tour of modern PHP features.
Topic match · Python, Ruby & scripting languages
Transformers, the tech behind LLMs | Deep Learning Chapter 527:14

Transformers, the tech behind LLMs | Deep Learning Chapter 5

11.6M views • 2 years ago
3Blue1Brown
3Blue1Brown's visual explanation of how transformers and GPT-style language models work, tracing data through tokens, embeddings and attention.
Topic match · LLMs & generative AI
A London Accent from the 14th to the 21st Centuries18:10

A London Accent from the 14th to the 21st Centuries

7.2M views • 5 years ago
Simon Roper
Linguist Simon Roper reconstructs how a London accent would have sounded from the 14th to the 21st centuries, reading passages in period pronunciation. It draws on the Cambridge History of the English Language.
Topic match · Language & linguistics
Can Japanese People Read Chinese? (Kanji)9:37

Can Japanese People Read Chinese? (Kanji)

691K views • 7 years ago
That Japanese Man Yuta
Yuta, a Japanese YouTuber, explains whether Japanese speakers can read Chinese text. He shows how shared kanji let people guess meanings while the two languages remain completely different.
Topic match · Language & linguistics
Why don't subtitles match dubbing?8:26

Why don't subtitles match dubbing?

2M views • 2 years ago
Tom Scott
Tom Scott explains why subtitles often differ from dubbed dialogue, covering how translation, timing and reading speed shape each. It features translators and voice talent working in several languages.
Topic match · Language & linguistics
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.
Topic match · LLMs & generative AI
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.
Topic match · Python, Ruby & scripting languages
The US Has More Tribes Than the World Has Countries6:47

The US Has More Tribes Than the World Has Countries

7.3M views • 6 years ago
CGP Grey
CGP Grey explains why "Indian" is often preferred over "Native American" in the United States, especially near reservations, and how many tribes exist in the US. He draws on conversations with people who identify as Indian.
Topic match · Language & linguistics
The Zipf Mystery21:05

The Zipf Mystery

28.7M views • 11 years ago
Vsauce
Vsauce's explainer on Zipf's law, the pattern in which the frequency of a word is inversely related to its rank. It shows the pattern across many domains and discusses why it remains unexplained.
Topic match · Language & linguistics
Anagrams, but where you can break apart letters: "Anagraphs"12:04

Anagrams, but where you can break apart letters: "Anagraphs"

256K views • 8 years ago
suckerpinch
Tom Scott-style exploration by suckerpinch (Tom7) of generalized anagrams where letters can be broken into pieces, called anagraphs, with a whimsical computational approach.
Topic match · Language & linguistics
Rapping, deconstructed: The best rhymers of all time12:44

Rapping, deconstructed: The best rhymers of all time

16.3M views • 10 years ago
Vox
Vox breaks down how great rappers build rhymes, from Kurtis Blow's simple bars to Biggie's smooth flow and Kendrick Lamar's dense, fast delivery. It uses on-screen visualizations of rhyme structure.
Topic match · Language & linguistics
Gender Neutral Pronouns: They're Here, Get Used To Them3:49

Gender Neutral Pronouns: They're Here, Get Used To Them

4.6M views • 13 years ago
Tom Scott
Tom Scott argues that grammatical gender is a silly concept and that the singular 'they' is an established gender-neutral pronoun. The description carries later corrections and reflections he added in 2019.
Topic match · Language & linguistics
Shakespeare: Original pronunciation (The Open University)10:22

Shakespeare: Original pronunciation (The Open University)

5.6M views • 15 years ago
OpenLearn from The Open University
David and Ben Crystal introduce the Original Pronunciation production of Shakespeare and show what it reveals about the history of English, including puns and rhymes lost in modern speech.
Topic match · Language & linguistics
w18:28

w

3.7M views • 7 years ago
jan Misali
jan Misali traces the history of the letter W, including why it is called double u. The video is part of a series of deep dives into individual letters.
Topic match · Language & linguistics
Accent Expert Gives a Tour of U.S. Accents - (Part 2) | WIRED14:18

Accent Expert Gives a Tour of U.S. Accents - (Part 2) | WIRED

2.7M views • 5 years ago
WIRED
Dialect coach Erik Singer tours a range of accents across North America with linguists in Part 2 of WIRED's accent series. It covers regional distinctions such as Southern Mississippi, Miami and Utah English.
Topic match · Language & linguistics
Vocal Fry: what it is, who does it, and why people hate it!27:18

Vocal Fry: what it is, who does it, and why people hate it!

4.1M views • 3 years ago
Dr Geoff Lindsey
Linguist Geoff Lindsey explores vocal fry: what it is, who uses it, how it relates to glottal stops and accents, and why some people dislike it.
Topic match · Language & linguistics
Why “No Problem” Can Seem Rude: Phatic Expressions3:51

Why “No Problem” Can Seem Rude: Phatic Expressions

5M views • 7 years ago
Tom Scott
Tom Scott explains phatic expressions such as hello, thank you and how are you, which carry social meaning rather than information, and why replies like no problem can seem rude to some people.
Topic match · Language & linguistics
Rhyme: Why Eminem is one of the most impressive lyricists ever6:00

Rhyme: Why Eminem is one of the most impressive lyricists ever

3.7M views • 13 years ago
Library of Alexandria
A re-upload of a video breaking down Eminem's rhyme schemes, showing multi-syllable and internal rhymes in songs such as Lose Yourself. It aims to show why he is considered a standout lyricist.
Topic match · Language & linguistics
Accent Expert Gives a Tour of U.S. Accents - (Part One) | WIRED21:33

Accent Expert Gives a Tour of U.S. Accents - (Part One) | WIRED

9.6M views • 5 years ago
WIRED
Dialect coach Erik Singer and several linguists tour distinct accents across English-speaking North America. It is the first part of a WIRED series on US accents.
Topic match · Language & linguistics
One Typo, Wrong Continent16:04

One Typo, Wrong Continent

11.6M views • 3 years ago
CGP Grey
CGP Grey explains why airport codes are inconsistent and sometimes confusing, from their origins in old weather station codes to the quirks that cause mistakes. He builds the story around a single typo that sent a flight to the wrong continent.
Topic match · Language & linguistics
Tiffany: The Name That Cheats Death8:56

Tiffany: The Name That Cheats Death

6M views • 5 years ago
CGP Grey
CGP Grey investigates why the name Tiffany spiked in popularity and then faded, with help from onomastics experts. It is a short, playful look at how names spread.
Topic match · Language & linguistics
How big is a billion? - Numberphile9:42

How big is a billion? - Numberphile

1.8M views • 14 years ago
Numberphile
Numberphile explains the long and short scales for naming large numbers, covering millions, billions, trillions, milliards and the Greek myriad, with James Grime and Tony Padilla.
Topic match · Language & linguistics
The Hidden Rules of Conversation5:33

The Hidden Rules of Conversation

5.8M views • 6 years ago
Tom Scott
Tom Scott explains Gricean maxims, the unwritten guidelines that shape how we understand each other. He uses examples such as why 'asbestos-free cereal' sounds suspicious.
Topic match · Language & linguistics
Movie Accent Expert Breaks Down 32 Actors' Accents | WIRED16:41

Movie Accent Expert Breaks Down 32 Actors' Accents | WIRED

15.8M views • 9 years ago
WIRED
Dialect coach Erik Singer analyzes how accurate the accents are of 32 well-known actors, including Brad Pitt and Will Smith, in WIRED's breakdown.
Topic match · Language & linguistics
Why Does Portuguese Sound Like Russian?! (or Polish)11:06

Why Does Portuguese Sound Like Russian?! (or Polish)

2.5M views • 7 years ago
Langfocus
A Langfocus video examining why Portuguese, especially European Portuguese, sounds like Russian or Polish. It compares shared sounds such as vowel reduction and palatalization.
Topic match · Language & linguistics
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.
Topic match · LLMs & generative AI
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.
Topic match · Computer vision, speech & NLP
Fourier Optics used for Optical Pattern Recognition18:31

Fourier Optics used for Optical Pattern Recognition

103K views • 6 years ago
Huygens Optics
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.
Topic match · Computer vision, speech & NLP
Breaking The Creepy AI in Police Cameras35:49

Breaking The Creepy AI in Police Cameras

3.8M views • 1 year ago
Benn Jordan
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.
Topic match · Computer vision, speech & NLP
Attention in transformers, step-by-step | Deep Learning Chapter 626:10

Attention in transformers, step-by-step | Deep Learning Chapter 6

4.8M views • 2 years ago
3Blue1Brown
3Blue1Brown's visual walkthrough of the attention mechanism inside transformers, covering self-attention, multiple heads and cross-attention. It is chapter 6 of his deep learning series.
Topic match · LLMs & generative AI
Attention Is All You Need27:07

Attention Is All You Need

814K views • 8 years ago
Yannic Kilcher
Yannic Kilcher walks through the Attention Is All You Need paper, which introduced the Transformer, a sequence model based solely on attention without recurrence or convolutions. He reviews the architecture and the paper's translation results.
Topic match · LLMs & generative AI
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.
Topic match · Computer vision, speech & NLP