Location: San Diego, California
  Remote: Yes. With travel up to one week a quarter.
  Willing to relocate: No
  Technologies: Ruby on Rails, Git, Linux, Tailwind, Hotwire/Turbo, SQL/Postgres, Cloud infrastructure, people
  Résumé/CV: Seasoned Rails developer with extensive experience at Shopify, Apple, Intuit as well as many start ups. You can read more at https://bradlyfeeley.com
  Email: bradly@rails247.com

You've got an extra "R" in there. In 2020 their only revenue from was non-recurring lifetime software purchases. Like SaaS if you had a 100% churn rate.

  Location: San Diego, California
  Remote: Yes. With travel up to one week a quarter.
  Willing to relocate: No
  Technologies: Ruby on Rails, Git, Linux, Tailwind, Hotwire/Turbo, SQL/Postgres, Cloud infrastructure, people
  Résumé/CV: Seasoned Rails developer with extensive experience at Shopify, Apple, Intuit as well as many start ups. You can read more at https://bradlyfeeley.com
  Email: bradly@rails247.com

https://github.com/bradly/christmas-lights.js

You can see it in action at https://bradlyfeeley.com and https://birdymusic.com

Thank you! It is now fixed <3

[0]: This was actually Monday-Thursday with travel on Friday

I worked on systems for evaluating the quality of models over time and for evaluating the quality of new models before release to understand how the new models would perform compared to current models once in the wild. It was difficult to get Siri to use these tools that were outside of their org. While this wouldn't solve the breadth of Siri's functionality issues, it would have helped improve the overall user experience with the existing Siri features to avoid the seemingly reduction of quality over time.

Secondly, and admittedly farther from where I was... Apple could have started the move from ML models to LLMs much sooner. The underlying technology for LLMs started gaining popularity in papers and research quite a few years ago, and there was a real problem of each team developing their own ML models for search, similarity, recommendations, etc that were quite large and that became a problem for mobile device delivery and storage. If leadership had a way to bring the orgs together they may have landed on LLMs much sooner.

Yesterday I put up a little dictionary of synth sounds that I'm building out to help me on my journey (https://synthrecipes.org). The goal to be able to export any particular sound in a format for different live coding environments. Sounds are defined in a JSON format like https://synthrecipes.org/recipes/acid-bass.json. I'll open source it today so other can submit sounds.

--

Edit: I've open sourced the repo so others can improve existing sounds and add new ones. https://github.com/bradly/synth-recipes/tree/main

This Sonic Pi example really blew my mind when I first heard it. Such a rich sound out of three notes.

    use_synth :hollow
    with_fx :reverb, mix: 0.7 do
    
      live_loop :note1 do
        play choose([:D4,:E4]), attack: 6, release: 6
        sleep 8
      end
    
      live_loop :note2 do
        play choose([:Fs4,:G4]), attack: 4, release: 5
        sleep 10
      end
    
      live_loop :note3 do
        play choose([:A4, :Cs5]), attack: 5, release: 5
        sleep 11
      end
    end

Mort Garson: Mother Earth's Plantasia

Hiroshi Yoshimura: Surround

Satoshi Ashikawa: Still Way (Wave Notation 2)

Shameless plug... Search BirdyMusic.com in Spotify/Apple Music/YouTube Music to hear some ambient music algo generated based on realtime Birdnet detections and weather in my backyard.