Dasher: information-efficient text entry

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 books." -David MacKay We just allocate more shelf space to the more probably letters. link link link DonHopkins on May 18, 2018 | parent | context | favorite | on: Pie Menus: A 30-Year Retrospective: Take a Look an... 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: ▶ this video Here is a demo of using Dasher by an engineer at Google, Ada Majorek, who has ALS and uses Dasher and a Headmouse to program: link Another one of her demonstrating Dasher: Ada Majorek Introduction - CSUN Dasher link Here’s a more recent presentation about it, that tells all about the latest open source release of Dasher 5: Dasher - CSUN 2016 - Ada Majorek and Raquel Romano link Here's the github repo: Dasher Version 4.11 link >Dasher is a zooming predictive text entry system, designed for situations where keyboard input is impractical (for instance, accessibility or PDAs). It is usable with highly limited amounts of physical input while still allowing high rates of text entry. Ada referred me to this mind bending prototype: D@sher Prototype - An adaptive, hierarchical radial menu. link >( link ) - a really neat way to "d

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: ▶ this video Here is a demo of using Dasher by an engineer at Google, Ada Majorek, who has ALS and uses Dasher and a Headmouse to program: link Another one of her demonstrating Dasher: Ada Majorek Introduction - CSUN Dasher link Here’s a more recent presentation about it, that tells all about the latest open source release of Dasher 5: Dasher - CSUN 2016 - Ada Majorek and Raquel Romano link Here's the github repo: Dasher Version 4.11 link >Dasher is a zooming predictive text entry system, designed for situations where keyboard input is impractical (for instance, accessibility or PDAs). It is usable with highly limited amounts of physical input while still allowing high rates of text entry. Ada referred me to this mind bending prototype: D@sher Prototype - An adaptive, hierarchical radial menu. link >( link ) - a really neat way to "dive" through a menu hierarchy/, or through recursively nested options (to build words, letter by letter, swiftly). D@sher takes Dasher, and gives it a twist, making slightly better use of screen revenue. >It also "learns" your typical useage, making more frequently selected options larger than sibling options. This makes it faster to use, each time you use it. >More information here: link and here: link Dasher is even a viable way to input text in VR, just by pointing your head, with

link DonHopkins on Nov 24, 2023 | parent | context | favorite | on: AI is currently just glorified compression 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 books." -David MacKay We just allocate more shelf space to the more probable letters. Why isn't Dasher built into every operating system and mobile phone? link link link DonHopkins on May 18, 2018 | parent | context | favorite | on: Pie Menus: A 30-Year Retrospective: Take a Look an... 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: ▶ this video Here is a demo of using Dasher by an engineer at Google, Ada Majorek, who has ALS and uses Dasher and a Headmouse to program: link Another one of her demonstrating Dasher: Ada Majorek Introduction - CSUN Dasher link Here’s a more recent presentation about it, that tells all about the latest open source release of Dasher 5: Dasher - CSUN 2016 - Ada Majorek and Raquel Romano link Here's the github repo: Dasher Version 4.11 link >Dasher is a zooming predictive text entry system, designed for situations where keyboard input is impractical (for instance, accessibility or PDAs). It is usable with highly limited amounts of physical input while still all

This is really awesome. It looks hard, but it isn't. Here's a talk from 2007 that explains it well ▶ this video

minute 32: breathing as one-dimensional input method (!): ▶ this video current version of Dasher in the browser: link

I'd love a neural interface to Dasher, which adaptively learns as you use it which letter combinations are the most popular, and adjusts over time to make it easier and faster to input common text. It would be wonderful integrated with a context and language sensitive IDE. link link link >To make the interface efficient, we use the predictions of a language model to determine how much of the world is devoted to each piece of text. Probable pieces of text are given more space, so they are quick and easy to select. Improbable pieces of text (for example, text with spelling mistakes) are given less space, so they are harder to write. The language model learns all the time: if you use a novel word once, it is easier to write next time. [...] >Imagine a library containing all possible books, ordered alphabetically on a single shelf. Books in which the first letter is "a" are at the left hand side. Books in which the first letter is "z" are at the right. In picture (i) below, the shelf is shown vertically with "left" (a) at the top and "right" (z) at the bottom. The first book in the "a" section reads "aaaaaaaaaaaa..."; somewhere to its right are books that start "all good things must come to an end..."; a tiny bit further to the right are books that start "all good things must come to an enema...". [...] >.... This is exactly how Dasher works, except for one crucial point: we alter the SIZE of the shelf space devoted to each book in proportion to the probability of the corre

People seem to pick up Dasher pick up pretty quickly link and the demo makes it seem much easier than it is ▶ this video