Cool Links Vol. 1: July, 2024

Welcome to the first edition of Cool Links™! (not really trademarked)

The idea here is to post links to cool stuff I've read or watched every month. It is part of an effort I'm making into writing more and more often. Posting these links gives me the opportunity to comment on them, which feels less intimidating than writing a full blog post. Plus, it's an opportunity to link to the work of other writers and keep the spirit of the IndieWeb going.

This year I've also started posting some articles with the "Reading Recs" category to be able to comment on them. These Cool Links will replace some of those, but might still show up in cases where I have a lot to say about them.

So, let's go to this month's Cool Links:

Design

Different Gets Ignored, by Luke Wroblewski

This article talks about how users are growing increasingly indifferent to elements that "pop" on websites and apps. Because “⁠if a pop-up or any element of a user interface for that matter looks too different from the rest of the design, people will often perceive it as something that doesn't belong (like an ad) and dismiss it.”.

Instead, making the important elements feel like the core flow tends to yield better results.

Why users are ignoring your features, by Built for Mars

This case study (in the form of a slide presentation) has amazing insight into how having too many features can backfire. It goes through many design concepts and practical examples onto how you can make users take notice and actually use the features you work so hard to build.

How small UI delighters have a huge impact on UX, by Growth Design

Another case study; this one shows how apps that are great ideas can become a disappointment when they don't know how to display those good ideas correctly. And how good (and fun) design can make all the difference on getting users on board.

AI

AI Companies Need to Be Regulated: An Open Letter to the U.S. Congress and European Parliament, by MacStories

The MacStories team was able to put into words what a lot of people (including me) are feeling. AI companies that scrape content on the web (ignoring its licenses) pose a big threat to websites that need the pageviews to keep the lights on. Right now, that is all done under the claim that they're using the data to train their models and not reproducing the content directly, which would fit into "fair use". But there are good arguments that it's not true.

AI models collapse when trained on recursively generated data

This study shows that, predictably, generative AIs or LLMs tend to decline in quality as they start feeding on content that was generated by other LLMs instead of humans.

Considering much of the web is now getting polluted by this LLM-generated slop and the web is a big source of data for their training, it seems that future models will likely regress in quality. Doesn’t seem like a very sustainable model, does it?