Jump to Navigation

Main menu

  • Login
Home

Secondary menu

  • [Room Booking]
  • [Wiki]
  • [Webmail]

lloyd's blog

256A Reading Response #8

Submitted by lloyd on Sun, 11/08/2020 - 1:09pm
This is a response to a definition in Ge Wang’s book Artful Design:
“Definition 8.14: The ‘pi’ shaped individual” (pg. 428)
  • Read more

256A Reading Response #1

Submitted by lloyd on Wed, 11/04/2020 - 6:44pm
*Caution, contains severe nitpicking and strong yet under-argued thoughts*

“Artful design is conscious effort to elevate that natural process to a higher discipline” (pg. 52)

Does design need to be elevated in order to reach the sublime? Or should it’s “sublimeness” rather be revealed? Was it not always there? And should the majority of our work to experience it not be in adjusting, and readjusting, and readjusting our framing and perspective?
  • Read more

256A Reading Response #7

Submitted by lloyd on Sun, 11/01/2020 - 9:36pm
This is a response to a principle in Ge Wang’s book Artful Design:
“Principle 7.7: A little anonymity can go a long way” (pg. 363)
  • Read more

256A Reading Response #6

Submitted by lloyd on Sun, 10/25/2020 - 10:07pm
This is a response to a principle in Ge Wang’s book Artful Design:
“Principle 6.20 The Tofu Burger Principle” (pg. 341)
  • Read more

256A Reading Response #5

Submitted by lloyd on Sun, 10/18/2020 - 3:51pm
This is a response to a principle in Ge Wang’s book Artful Design: “Principle 5.5 Have your machine learning – And the human in the loop!” (pg. 218)

Hey Robot! Share! Please?

Machine learning is generally structured around “tasks”, but never “tools”. There are countless papers and competitions about which algo or model can classify the emotion of a facial expression, but far fewer on what to do with that. While this feels like a classic case of “we were so preoccupied with if we could, we never stopped to ask if we should”, it gets at something a little deeper I think:
Machine learning is hard!
  • Read more

256A Reading Response #4

Submitted by lloyd on Sun, 10/11/2020 - 6:46am
“Now” and time in the computer music programming language Chuck: a response to chapter 4 of Ge Wang’s Artful Design. Chuck navigates time in a very interesting way. Unlike other languages which might be event-based, like the bang system of Max/MSP, or durational, like Csound and many others, Chuck asks you to contemplate the trickiness of “now” and encourages a different way to think about time. The big “woah” moment for me came when I realized that sound and time are one and the same in Chuck. Since it is strongly-timed, digital audio samples are the basis of time, which is kind of trippy to think about. Let’s say there is a glitch and the audio stops, you’ll lose time outside of Chuck and maybe get some silence, but Chuck never lost time because it’s audio wasn’t being calculated.
  • Read more
  • 1
  • 2
  • next ›
  • last »
Syndicate content
  • Home
  • News and Events
    • All Events
      • CCRMA Concerts
      • Colloquium Series
      • DSP Seminars
      • Hearing Seminars
      • Guest Lectures
    • Event Calendar
    • Events Mailing List
    • Recent News
  • Academics
    • Courses
    • Current Year Course Schedule
    • Undergraduate
    • Masters
    • PhD Program
    • Visiting Scholar
    • Visiting Student Researcher
    • Workshops 2022
  • Research
    • Publications
      • Authors
      • Keywords
      • STAN-M
      • Max Mathews Portrait
    • Research Groups
    • Software
  • People
    • Faculty and Staff
    • Students
    • Alumni
    • All Users
  • User Guides
    • New Documentation
    • Booking Events
    • Common Areas
    • Rooms
    • System
  • Resources
    • Planet CCRMA
    • MARL
  • Blogs
  • Opportunities
    • CFPs
  • About
    • The Knoll
      • Renovation
    • Directions
    • Contact

Search this site:

Spring Quarter 2023

Music 101 Introduction to Creating Electronic Sounds
Music 128 Stanford Laptop Orchestra (SLOrk)
Music 220C Research Seminar in Computer-Generated Music
Music 250A Physical Interaction Design for Music 
Music 254 Computational Music Analysis
Music 257 Neuroplasticity and Musical Gaming
Music 264 Musical Engagement
Music 319 Research Seminar on Computational Models of Sound Perception
Music 320C Audio DSP Projects in Faust and C++

 

 

 

   

CCRMA
Department of Music
Stanford University
Stanford, CA 94305-8180 USA
tel: (650) 723-4971
fax: (650) 723-8468
info@ccrma.stanford.edu

 
Web Issues: webteam@ccrma

site copyright © 2009 
Stanford University

site design: 
Linnea A. Williams