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No strong matches for “nlp”. Here are the closest videos.
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
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
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.
Topic match · Computer vision, speech & NLP
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 · Computer vision, speech & NLP
Reveal Invisible Motion With This Clever Video Trick14:20

Reveal Invisible Motion With This Clever Video Trick

2.8M views • 6 years ago
Steve Mould
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.
Topic match · Computer vision, speech & NLP
Tesla Autopilot Crashes into Motorcycle Riders - Why?8:35

Tesla Autopilot Crashes into Motorcycle Riders - Why?

1.1M views • 4 years ago
FortNine
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.
Topic match · Computer vision, speech & NLP
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.