For those of you who went to NSNorth at Chateau Montebello, enjoyed your time there, and are in the market for a resort, this might be an interesting opportunity: https://youtu.be/ZeoNkWbA9nI
Chris Liscio
@liscio
- 232 Followers
- 64 Following
- 120 Posts
I write SuperMegaUltraGroovy software, such as http://capoapp.com. More recently, I'm also a grad student at the University of Waterloo.
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Full disclosure: If you signed up recently, (a) you probably need to re-sign-up and/or let me know if you still don't have a confirmation email, and (b) you *may* receive the 015 edition newsletter to your inbox in the next day or so.
I'm still working on the email export in my Middleman project, but I wanted to publish ASAP so that my in-app newsletter links don't still point at a page with a 3-year-old "latest post". 😛
It's official—The SuperMegaUltraGroovy Newsletter is Back!
https://supermegaultragroovy.com/2025/10/15/smug-newsletter-is-back/
Check out Newsletter #015 (https://supermegaultragroovy.com/newsletter/015/) and consider signing up for future mailings!
Thanks to the glowing endorsement of @danielpunkass and others, I have just now finished configuring my Sendy install, and look forward to re-building my email subscriber list up again from zero.
Sign up here, if you're into that sort of thing: https://supermegaultragroovy.com/newsletter
I *obviously* don't send email very often, given yesterday's saga (https://supermegaultragroovy.com/2025/10/09/i-guess-i-let-it-go-too-long/). But that needs to change, and not just because I don't want stuff deleted quietly on me!
Capo is the best tool on your Mac for learning songs by ear, and today we released Capo 4.6 which looks and works better than ever—especially on macOS Tahoe!
And it still plays all the hits! Capo can: slow songs with top sound quality, visualize and "tab out" complex solos, sync looping regions to the beat. Oh, and did we mention it has the best on-device chord detection on the planet?
Get it today: https://supermegaultragroovy.com/products/capo/mac/
TIL that Campaign Monitor—a company that is in the email-sending business—deletes inactive accounts without ever sending you an email notice.
https://supermegaultragroovy.com/2025/10/09/i-guess-i-let-it-go-too-long/
In related news, Capo 4.6 is set to go live tomorrow AM (EST) on the Mac App Store, and I'll be back to talk more about that then.
Jordan B. L. SmithWhen Suno generates a song that resembles one from the training data, has it plagiarised that song?
I think it's hard to deny that it has, but if you disagree, you might find support for your view in a short story by Jorge Luis Borges, about a man who wanted to rewrite "Don Quixote" without plagiarising it. He only succeeds in writing a few chapters — but they're even better than the original!
I wrote an essay about it for my blog:
https://jbls.fun/On-Suno-and-rewriting-the-Quixote/
On Suno and rewriting the <em>Quixote</em>
Last year, Suno and Udio released products that generate songs based on user prompts. Both services are based on large language models (LLMs), neural networks that are good at synthesising all kinds of data when trained on large enough datasets. To build these models, Suno and Udio likely would have needed millions of high-quality examples: audio, lyrics and metadata for real music composed by real artists. The launch of these products thus raised red flags for those in the music industry: what data did they use? If it was copyrighted, was this use of the data permissible? And if the models were somehow using bits of copyrighted music to build new pieces of music, was this plagiarism?
Earworms can be annoying, especially when you don't like the song that's playing in your head. But what if I told you that a well-crafted earworm could help you learn the melody of a new song, or a tricky solo?
Learn more about this in my latest article, The Earworm Strategy: https://supermegaultragroovy.com/products/capo/ear-learning/earworm-strategy/
Want to have a laugh? Talk through the design of a CoreAudio playback engine with your favourite LLM!
You'll get to see *all the greatest hits* in the IOProc that it spits out:
* Calling ObjC code (both property accesses, and straight-up method calls)
* Using fetch_add(…, std::memory_order_relaxed) to update a shared frame counter
* Allocating/freeing buffer lists
😂🤣🤪
Tonal working memory is a short-term buffer in your mind that lets you answer the fundamental, repeated question of ear learning: “did I play the note I just heard?”
Unfortunately, it kind of sucks at its job, so you need to work a little bit smarter so you don't overload your tonal working memory.
Here's the latest article in my series on ear learning, Why Learning By Ear is Actually Learning By Memory: https://supermegaultragroovy.com/products/capo/ear-learning/learning-by-memory/