HackerTube

THE VIDEO SHELF · text entry interfaces

Dasher: information-efficient text entry

David MacKay's 2007 Google Tech Talk presents Dasher, a text-entry system driven by continuous gestures and a language model, reaching about 35 words per minute with one finger and 25 hands-free. It explains the information-theory reasoning behind the design.

Why HN readers recommended it

Regarded as the seminal talk on Dasher, recommended in threads on accessible and alternative text input.

This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.

Video & recommendation details

Creator / channel
Google TechTalks
Topic
text entry interfaces
Format
talk
Level
intermediate
HN recommenders in dataset
2
HN mentions in dataset
7
Recommendation years in dataset
2016–2025

These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.

From the original HN conversations

Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.

  • Dasher is fantastic, because it's based on rock solid information theory, designed by the late David MacKay. Here is the seminal Google Tech Talk about it: [VIDEO] Here is a demo of using Dasher by an engineer at Google, Ada Majorek, who has ALS and …

    DonHopkins on Hacker News · 2018-05
    In Pie Menus: A 30-Year Retrospective: Take a Look and Feel Free
  • I love David MacKay's brilliant work on the Dasher text input system, which draws deeply from his work on information theory -- imagine Dasher integrated with an IDE and code search and Copilot and language model! "Writing is navigating in the library of all possible …

    DonHopkins on Hacker News · 2023-11
    In AI is currently just glorified compression
  • This is really awesome. It looks hard, but it isn't. Here's a talk from 2007 that explains it well [VIDEO]

    devilsenigma on Hacker News · 2016-12
    In Dasher: Writing text really fast without typing or speaking

Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.