Month: February 2005

  • Clone Wars Watchlist

    I’m such a follower. Obviously, this doesn’t actually require iTunes, and could be applied to any music library.

    How many total songs? 2952, or just under 8 days

    Sort by song title; first and last? From “…To Die For” by Hans Zimmer from The Lion King soundtrack to “Zombie” by The Cranberries. Ignoring non-letter-initial songs, the first would be “A Boy Like That” by Stephen Sondheim from Side by Side by Sondheim.

    Sort by time; shortest and longest? From “The End of the Talking!” by the VeggieTales from A Very Veggie Christmas to “Vice Presidential Debate” by Dick Cheney and John Edwards from 2004 Presidential Debates. Ignoring the spoken word, the longest would be “Presto – Allegro Assai – Andante Maestoso – Allegro Energico, Sempre Ben Marcato” by Ludwig van Beethoven from The 9th Symphony in D Minor, Op. 125. I was kind of hoping that “Star Trek: Conversational Klingon” would come up as the longest. Maybe I should delete the debates…

    Sort by album title; first and last? From Moby’s 18 to Kenny Loggins’ Yesterday, Today, and Tomorrow.

    Top five most played songs?

    • “Radio Ga Ga” by Queen (25)
    • “Imaginary” by Evanescence (24)
    • “Clubbed to Death (Kurayamino Mix)” by Rob D (24)
    • “Special” by Garbage as arranged and sung by Stanford Mixed Company (24)
    • “Jerry Springer” by “Weird Al” Yankovic (23)

    Search for sex; how many songs show up? 1

    • “Sexy Sadie” by The Beatles

    Search for death; how many songs show up? 3

    • “Judas’ Death” from Jesus Christ Superstar
    • “Come to Me (Fantine’s Death)” from Les Misérables
    • “Clubbed to Death (Kurayamino Mix)” by Rob D

    Search for love; how many songs show up? 122
    From “A Heart Full of Love” from Les Misérables to “You’ve Got to Hide Your Love Away” by The Beatles, a total of just under 8 hours. I guess that means that love accounts for approximately one twenty-fourth of my music library…

    I Heard It Through The Grapevine” from Chronicle, Volume I by Creedence Clearwater Revival

  • Sunspot

    A small Yorkshire Terrier lies in a pet bed on a green upholstered chair in a sunny living room.

    I wish I could nap like Pike naps.

  • The Muppets Meet Murderbot

    For the last year and a half or so Andrle and I have been having a ton of fun as part of an online book club put together by my friend Tanya. Unlike most book clubs where you all read the same thing, we all just share things we love that we’ve been reading.

    One recommendation that kept coming up was The Murderbot Diaries by Martha Wells, and I’m glad we finally ran with it and started reading them. We’ve been bingeing the last few weeks and they’re really, really great. Highly recommend (even though I’m only on Book 4.)

    Unsurprisingly another thing I’ve been reading about and thinking about a lot is the advent of Large Language Models, particularly as manifested by ChatGPT. My past work life as an NLP practitioner has me a mix of curious, envious, and highly suspicious of what these are and how they’re being used. In the short term I don’t mind using them as a toy that I can play with for the purpose of a joke, which is what this post is about.

    A recurring topic in this book club is how we might have the Muppets interpret a particular book, or how we might recast a movie with Muppets (but keep one human actor). This provides a lot of fun discussions, especially since I grew up regularly watching the classic Muppet movies on VHS recorded off of TV, and I really like musicals.

    That all brings me to some prompt iterating that I did to get ChatGPT to write the painfully cliché finale to a Muppet musical featuring Murderbot. (Apologies to both Henson and Wells.)

    Verse 1 (Murderbot):
    I used to be a killing machine,
    A rogue cyborg, feared and mean,
    But then I met the Muppets and Kermit,
    And learned what friendship truly meant.

    Verse 2 (Kermit):
    I'm just a simple frog, it's true,
    But I believe in friendship too,
    And when I met Murderbot, I knew,
    Together we could do something new.

    Chorus (All):
    We don't need to kill no more,
    Our friends are all we're fighting for,
    With Murderbot and Kermit side by side,
    We'll show the world what we stand for.

    Verse 3 (Murderbot):
    I never wanted to be a tool,
    But that's all humans see in me, it's cruel,
    I used to dream of breaking free,
    From their endless schemes and greed.

    Verse 4 (Kermit):
    It's true, I'm always happy-go-lucky,
    But I've been through some tough times that were quite yucky,
    But now with Murderbot and the gang,
    I know our friendship will never hang.

    Chorus (All):
    We don't need to kill no more,
    Our friends are all we're fighting for,
    With Murderbot and Kermit side by side,
    We'll show the world what we stand for.

    The past is gone, the future bright,
    With friends like these, we'll win the fight,
    Our love and trust will guide us through,
    Together we'll see this journey through.

    Chorus (All):
    We don't need to kill no more,
    Our friends are all we're fighting for,
    With Murderbot and Kermit side by side,
    We'll show the world what we stand for.

    So let's raise our voices high,
    And let the world hear our battle cry,
    With Muppets and Murderbot side by side,
    We'll change the world and turn the tide.
    OpenAI. (2023, Mar. 16) [Iterative prompt conversation starting with “This Muppet movie is about a rogue cyborg traveling to different space stations and learning the power of friendship from the Muppets” and “I need some lyrics for the big finals. The music is big broadway style number about how the rogue cyborg doesn’t need to kill bad guys anymore because it has friends.” and then encouraging more dialogue between Kermit and Murderbot]

    Yes, I looked up recommendations on how to properly cite ChatGPT output.

    Overall the result was mildly amusing. I couldn’t get it to capture Murderbot’s signature style, presumably because while information about the novellas are in its model training, not enough text from the novellas are in there.

    I’m still not sure what useful things I could do with this kind of tool, but in the meantime, I can make it make silly songs.

  • Fox Ferocity

    Pike playing with a toy almost as big as he is.

  • Groomed Pike

    Tiny freshly groomed Yorkie sits on a teal couch wearing a monstera bow tie

    I love this little gentleman.

  • The Kale Wanter

    A small black and brown Yorkie stands on a cream rug in front of a brown cupboard begging for the bunch of lacinato kale in hand in the foreground.