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Open source devs say AI crawlers dominate traffic, forcing blocks on entire countries - Ars Technica

As it currently stands, both the rapid growth of AI-generated content overwhelming online spaces and aggressive web-crawling practices by AI firms threaten the sustainability of essential online resources. The current approach taken by some large AI companies—extracting vast amounts of data from open-source projects without clear consent or compensation—risks severely damaging the very digital ecosystem on which these AI models depend.

Go To Hellman: AI bots are destroying Open Access

AI companies with billions to burn are hard at work destroying the websites of libraries, archives, non-profit organizations, and scholarly publishers, anyone who is working to make quality information universally available on the internet.

The Blowtorch Theory: A New Model for Structure Formation in the Universe

Make yourself a nice cup of tea and settle in with Julian Gough’s magnum opus:

How early, sustained, supermassive black hole jets carved out cosmic voids, shaped filaments, and generated magnetic fields

AI wants to rule the World, but it can’t handle dairy.

AI has the same problem that I saw ten year ago at IBM. And remember that IBM has been at this AI game for a very long time. Much longer than OpenAI or any of the new kids on the block. All of the shit we’re seeing today? Anyone who worked on or near Watson saw or experienced the same problems long ago.

The New York Good Times

Better than the real thing. All true too.

Refresh for more.

What I’ve learned about writing AI apps so far | Seldo.com

LLMs are good at transforming text into less text

Laurie is really onto something with this:

This is the biggest and most fundamental thing about LLMs, and a great rule of thumb for what’s going to be an effective LLM application. Is what you’re doing taking a large amount of text and asking the LLM to convert it into a smaller amount of text? Then it’s probably going to be great at it. If you’re asking it to convert into a roughly equal amount of text it will be so-so. If you’re asking it to create more text than you gave it, forget about it.

Depending how much of the hype around AI you’ve taken on board, the idea that they “take text and turn it into less text” might seem gigantic back-pedal away from previous claims of what AI can do. But taking text and turning it into less text is still an enormous field of endeavour, and a huge market. It’s still very exciting, all the more exciting because it’s got clear boundaries and isn’t hype-driven over-reaching, or dependent on LLMs overnight becoming way better than they currently are.

Prescriptive and Descriptive Information Architectures | Jorge Arango

Interesting—this is exactly the same framing I used to talk about design systems a few years ago.

Information literacy and chatbots as search • Buttondown

If someone uses an LLM as a replacement for search, and the output they get is correct, this is just by chance. Furthermore, a system that is right 95% of the time is arguably more dangerous tthan one that is right 50% of the time. People will be more likely to trust the output, and likely less able to fact check the 5%.

Daring Fireball: Kottke on the Art and Power of Hypertextual Writing

Hypertext links are an information-density multiplier.

The way I’ve long thought about it is that traditional writing — like for print — feels two-dimensional. Writing for the web adds a third dimension. It’s not an equal dimension, though. It doesn’t turn writing from a flat plane into a full three-dimensional cube. It’s still primarily about the same two dimensions as old-fashioned writing. What hypertext links provide is an extra layer of depth. Just the fact that the links are there — even if you, the reader, don’t follow them — makes a sentence read slightly differently. It adds meaning in a way that is unique to the web as a medium for prose.

Information Architecture First Principles | Jorge Arango

• People only understand things relative to things they already understand
• People only understand things in context
• People rely on patterns and consistency
• People seek to minimize cognitive load
• People have varying levels of expertise and familiarity
• People are goal-oriented
• People often don’t know what they’re looking for
• Information is more useful when it’s actionable

Notes – David Bushell

David is on board. Who else?

Beyond the Frame | Untangling Non-Linearity

A fascinating look at the connections between hypertext and film editing. I’m a sucker for any article that cites both Ted Nelson and Walter Murch.

RSS Anything

Next time you’re frustrated by a website that doesn’t provide an RSS feed, try using this tool:

Transform any old website with a list of links into an RSS Feed

The Website vs. Web App Dichotomy Doesn’t Exist | jakelazaroff.com

Amen!

If there’s one takeaway from all this, it’s that the web is a flexible medium where any number of technologies can be combined in all sorts of interesting ways.

The map-reduce is not the territory

Unlike many people, I’m not particularly worried about AI replacing peoples’ jobs, although employers will certainly try and use it to reduce their headcount. I’m more worried about it transforming jobs into roles without agency or space to be human. Imagine a world where performance reviews are conducted by software; where deviance from the norm is flagged electronically, and where hiring and firing can be performed without input from a human. Imagine models that can predict when unionization is about to occur in a workplace. All of this exists today, but in relatively experimental form. Capital needs predictability and scale; for most jobs, the incentives are not in favor of human diversity and intuition.

Undersea Cables by Rishi Sunak [PDF]

Years before becoming Prime Minister of the UK, Rishi Sunak wrote this report, Undersea Cables: Indispensable, insecure.

The last dConstruct | hidde.blog

A great write-up from Hidde on dConstruct 2022 and how the speakers tackled the theme of design transformation:

They talked about turning a series of penstrokes into art, lasers into fireworks, human experiences into novels and patient data collection into a minimal effort task.

A lot of our work in web design and technology has a power to transform and that is wonderful, especially when we manage to be intentional about the how and why.

Improving the information architecture of the Smart Pension member app | Design and tech | Smart – retirement, savings and financial wellbeing

Here’s a really excellent, clearly-written case study that unfortunately includes this accurate observation:

In recent years the practice of information architecture has fallen out of fashion, which is a shame as you can’t design something successfully without it. If a user can’t find a feature, it’s game over - the feature may as well not exist as far as they’re concerned.

I also like this insight:

Burger menus are effective… at hiding things.

Still the Same — Real Life

Everything old is new again:

In our current “information age,” or so the story goes, we suffer in new and unique ways.

But the idea that modern life, and particularly modern technology, harms as well as helps, is deeply embedded in Western culture: In fact, the Victorians diagnosed very similar problems in their own society.

Which color scale to use when visualizing data - Datawrapper Blog

A fascinating four-part series by Lisa Charlotte Muth on colour in data visualisations:

1. Which color scale to use when visualizing data
2. When to use quantitative and when to use qualitative color scales
3. When to use sequential and when to use diverging color scales
4. When to use classed and when to use unclassed color scales