Back in 2011, two writers at Slate tried to build a robot version of @kottke. The resulting article is a throwback to the state of NLP and data mining at the time.
We should offer our help to LinkedIn, they clearly need help with their models.
"I'm committed to fostering an environment that values collaboration, diversity of thought, and a relentless pursuit of excellence that aligns with our corporate ethos."
Over the past few days I've been working on extending & re-packaging the procedural text generation engine from one of the old examples into a new package and also just wrote/updated documentation for its various features:
- variable definitions, optionally with multiple value choices
- cyclic & recursive variable references/expansion
- variable assignments
- dynamic, indirect variable lookups (for context specific situations)
- optional preset & custom modifiers (i.e. pointfree/concatenative application of modifier sequences)
- controlled randomness during var expansion
The new package is called: https://thi.ng/proctext (6.5KB incl. all deps) The text format used relies on a simple parser grammar defined and processed via https://thi.ng/parse. The resulting document AST is then interpreted via https://thi.ng/defmulti
Please see readme for notes/examples, as well as the refactored example project below. The tool is very useful for complex source code generation, but also could be useful for bots, interactive fiction etc. The generator is stateful and variable state can be optionally retained/re-used over multiple invocations. Making all modifiers async is also providing a lot of flexibility (e.g. loading external data sources, generating secondary/expanded descriptions etc.)
Demo (incl. 5 examples and can be used as playground):
https://demo.thi.ng/umbrella/procedural-text/
Meta Launches Generative AI Tools for Advertisers: https://www.reviewspace.info/meta-launches-generative-ai-tools-for-advertisers
#INLG2024 submission deadline is in 4 weeks! How are your papers coming together?
If you work on #NaturalLanguageGeneration, #TextGeneration (with or w/o #LLMs)
All deadlines are Anywhere on Earth (UTC-12)
• START system regular paper submission deadline: May 31, 2024
• ARR commitment to INLG deadline via START system: June 24, 2024
• START system demo paper submission deadline: June 24, 2024
• Notification: July 15, 2024
More info: https://inlg2024.github.io/calls.html
The first #CallForPapers for #INLG2024 is now out!
If you work on #NaturalLanguageGeneration, #TextGeneration (with or w/o #LLMs)
All deadlines are Anywhere on Earth (UTC-12)
• START system regular paper submission deadline: May 31, 2024
• ARR commitment to INLG deadline via START system: June 24, 2024
• START system demo paper submission deadline: June 24, 2024
• Notification: July 15, 2024
• Camera ready: August 16, 2024
• Conference: 23-27 September 2024
More info: https://www.jiscmail.ac.uk/cgi-bin/wa-jisc.exe?A2=SIGGEN;7b9b36b6.2404
@golovlev https://perplexity.ai и https://phind.com — как замену поисковикам, когда нужно невыдуманное описание или разъяснение явления или события с пруфлинками (но всё равно иногда умудряются спизднуть). Сюда же, в принципе, можно и #Copilot с #Geminy дбавить, обычно «спрашиваю» сразу у всех: кто-нибудь, да справится с вопросом.
Очень частый (уж извинити) юзкейс — написание каментов в Mastodon Считаю, что за пару секунд сгенерировать ответ на вопрос (с пруфлинками) — это гораздо «человечнее», чем отвечать «иди погугли».
#Mistral и #Клавдия — для художественного перевода и стилистической обработки текста. Их галлюцинациям доверия 0,0%.
https://theb.ai пишет код простеньких скриптов для бытовых задач чуть более избыточно, чем другие, но зато более понятно для «чайника».
А, ну и вот эти: https://kagi.com/summarizer/ выдает краткое содержание текста (или по ссылке). https://300.ya.ru тезисы из #YouTube-видео с таймстампами. Реально помогает решить, стоит ли полуторачасовой подкаст просмотра (как правило — не стоит).