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This is great and worth a bookmark.

This is the companion to I own my books, where I made the case for stripping DRM and actually owning what I buy. This post is the machinery overview: how I store, serve, and read all of it from my own homelab.

The findings suggest far more Americans than previously thought may be at risk of the allergy, which can make having a hamburger for dinner a potentially life-threatening choice. The Centers for Disease Control and Prevention has previously estimated that only 0.14 percent of the US population (up to 450,000 people) has the allergy. But the study also highlights how little we understand about this unique disease—and the challenges of accurately diagnosing it.

This could be a fun project.

What happens to online employment when this reaches 80%? Of course, some new tasks will get created – people will innovate and find tasks that they can do which AI systems can’t do. But how many of these new tasks will exist? Enough to replace the labor the AI systems now do? It’s increasingly hard for me to reconcile the continued progress of AI systems with the economy staying the same – rather, it’s more likely to me we are about to see extremely person-light AI-heavy (or person-nil) organizations expand to take over chunks of the economy, out-competing un-augmented humans.

This is why you can go to the AI Engineering World’s Fair and come away thinking everyone is building dark factories and automating entire enterprises, while non-developers from outside the greater-San Francisco AI complex wonder why data centers are necessary.

The first symptom of prompt debt is slowing iteration. As users flag errors and spot edge cases, additional guidance is added to the instructions, nudging the model into line. If unwanted behaviors persist, instructions are repeated, with increasing severity. Pretty soon, the prompt isn’t straightforward and quick fixes regress previous instructions. Errors can no longer be handled with one-line “hot fixes” and your development cycle slows to a crawl.

“Our findings establish frontier AI as a more capable conversational persuader than the most prepared, incentivized, and expert humans we could recruit. Training humans does not appear to close that gap,” they write. “As access to these systems continues to grow, the question is no longer whether AI can out-persuade humans but how, where, and on whose behalf this capability will be exercised.”

That era of building a viable SaaS business in a few months is gone. I mean, it technically still exists today but only in the arbitrage sense that the rest of the world hasn’t yet caught on to how quickly and easily software can be built. It’ll be gone soon, I promise.

In atproto, every app is a projection of the whole Atmosphere, just like Feedly and Google Reader are projections of the entire Blogosphere. You mostly “decentralize” by swapping your hosting, and/or by making and trying new apps. Running many full copies of the Bluesky database server is possible, but it’s not any more useful than running many copies of Google Reader.