Mia Sato, writing for The Verge:

[Jennifer] Dziura still updates her personal blog — these are words for people.

The shop blog, meanwhile, is the opposite. Packed with SEO keywords and phrases and generated using artificial intelligence tools, the Get Bullish store blog posts act as a funnel for consumers coming from Google Search, looking for things like Mother’s Day gifts, items with swear words, or gnome decor. On one hand, shoppers can peruse a list of products for sale — traffic picks up especially around holidays — but the words on the page, Dziura says, are not being read by people. These blogs are for Google Search.

Nick Heer comments:

The sharp divergence between writing for real people and creating material for Google’s use has become so obvious over the past few years that it has managed to worsen both Google’s own results and the web at large. The small business owners profiled by Sato are in an exhausting fight with automated chum machines generating supposedly “authoritative” articles. When a measure becomes a target — well, you know.

Amen. Pieced together with this article talking about just how badly Reddit (and Twitter) fucked up really puts a point on just how much worse the internet has become:

We are living through the end of the useful internet. The future is informed discussion behind locked doors, in Discords and private fora, with the public-facing web increasingly filled with detritus generated by LLMs, bearing only a stylistic resemblance to useful information. Finding unbiased and independent product reviews, expert tech support, and all manner of helpful advice will now resemble the process by which one now searches for illegal sports streams or pirated journal articles. The decades of real human conversation hosted at places like Reddit will prove useful training material for the mindless bots and deceptive marketers that replace it.

I guess there’s a reason I’m nostalgic for, and still run, a blog that’s about stuff I want to write about. But I’d be lying if I don’t feel like a dying breed. A dinosaur watching the astroid from my bedroom window.

Claire Woodcock, writing at VICE:

Over a dozen public libraries in the U.S. and Canada have begun offering their own music streaming services to patrons, with the goal of boosting artists and local music scenes. The services are region-specific, and offer local artists non-exclusive licenses to make their albums available to the community.

The concept originated in 2014 when Preston Austin and Kelly Hiser helped the Madison Public Library build the Yahara Music Library, an online library hosting music from local artists. By the time they completed their work on Yahara, they were confident they had a software prototype that other interested libraries could customize and deploy.

“That became kind of the inspiration for building MUSICat,” Austin told Motherboard, referring to the software platform he and Hiser created under a startup called Rabble.

TechCrunch looks at Dance Diffusion, an AI music generator:

The emergence of Dance Diffusion comes several years after OpenAI, the San Francisco-based lab behind DALL-E 2, detailed its grand experiment with music generation, dubbed Jukebox. Given a genre, artist and a snippet of lyrics, Jukebox could generate relatively coherent music complete with vocals. But the songs Jukebox produced lacked larger musical structures like choruses that repeat and often contained nonsense lyrics.

Google’s AudioLM, detailed for the first time earlier this week, shows more promise, with an uncanny ability to generate piano music given a short snippet of playing. But it hasn’t been open sourced.

Dance Diffusion aims to overcome the limitations of previous open source tools by borrowing technology from image generators such as Stable Diffusion. The system is what’s known as a diffusion model, which generates new data (e.g., songs) by learning how to destroy and recover many existing samples of data. As it’s fed the existing samples — say, the entire Smashing Pumpkins discography — the model gets better at recovering all the data it had previously destroyed to create new works.