fidzu : debian

At the end of last year I uninstalled the Twitter app on my phone.

In the past Twitter used to be very useful for providing feedback to large organisations. I had responses from supermarkets, chain restaurants, online stores, major computer companies, and even the IT department of a court. In recent times I have had less responses from corporations which significantly reduces the value of Twitter to me and to many other users. It seems that Elon's management style has discouraged not only advertising but also all forms of corporate interaction. Messing up the check mark on accounts to make it harder to work out which is a real corporate

Since Elon bought it Twitter has been increasingly pushing conservative Tweets and has done little to stop bot accounts. The incidence of useful discussions has steadily decreased. I know people who have quit Twitter entirely due to opposition to Elon, I am not doing that. I finally decided to stop using Twitter in any serious way when the notifications on my phone about popular Tweets started only being about Tweets from conservative influencers and Elon. This was obviously not any algorithm based on Tweets I was liking, it was based on political decisions. I didn't uninstall the app due to political disagreement, I uninstalled it because it was through deliberate design promoting material that any algorithm would know was something I wouldn't either like or "like".

I still announce new blog posts on Twitter for my 198 followers at the same time as announcing them on Mastodon and Facebook. I get the most reactions to such announcements on Mastodon, the second most on Facebook, and hardly any on Twitter. I'm wondering how long it will be worth announcing blog posts on Twitter or whether I should stop now.

I am sure that many other people are making similar decisions and this is going to affect Twitter overall.

The web site www.russellcoker.com has information on all the ways of following me.

25 Mar 2026 5:21am GMT

AI sure is a hot topic right now, and I see a lot of people arguing about it. To a lot of people around here, I'm the "computer person" they know and I get asked a lot about AI.

I'm going to suggest a lot of things can be true at once. For instance:

• LLMs are changing how we work and will continue to do so.
• LLMs are vastly over-hyped by vested interests, and may be in a bubble.

Or how about:

• Huge investment in GenAI is having many negative consequences, ranging from environmental to causing affordability problems in many industries that use hardware (ie, everywhere)
• Useful results can be had from models that run on local hardware, even battery-powered hardware, which may have negligible harm or even some benefit

And:

• GenAI is further concentrating wealth and power in megacorps, with the effect of squeezing out the smaller players even more.
• GenAI is lowering the cost of entry for people without a lot of resources already.

I have sympathy for the naysayers; those that say it's nothing but a stochastic parrot. But I don't have a lot of sympathy for the naysayers that deny ever using it; you can't form a credible argument against something without having an understanding of it informed by experience.

I also have sympathy for the cheerleaders. I have seen some impressive things from AI; for instance, a story from an engineer who has a child with a rare disease without a credible cure. The engineer did a lot of research on it, started feeding research papers into AI to analyze, and the AI started finding correlations between different areas of research that humans hadn't yet found - leading to a positive result for the child.

To be fair, I have rarely seen an AI deliver a 100% correct answer on anything with any real level of complexity. I have seen it both waste more time than it saves, and save a ton of time.

My point here is: It is neither always fantastic nor always terrible.

Let me talk you through an example.

I am a fan of inbox zero for email. That is, the inbox should be empty. Unfortunately, mine has 8000 messages in it. According to the oldest messages in my inbox, I last had inbox zero 8 years ago. But really, only a handful are older than 2020. I guess something must have happened that year…

I've been chipping away at this for quite some time now. The problem is, there are certain emails in there that really do still need some action - maybe it's photos to save off into our photo collection, for instance. But when looking at things sorted by date or thread, there are old shipping confirmations next to phishing attempts and family photos. One can't just scan down the list.

I've tried all the usual tricks, most of which involve selecting groups of message that are easy to bulk erase, or at least easy to scan visually for the occasional thing worth saving. Sort by sender or subject line, for instance. Then I can, for instance, delete all the old messages from the shopping sites I commonly use all at once. But then they start using different senders and different subject lines and that doesn't get all of them. I've tried keyword searches for this sort of thing too. Still, that got me down to about 8000 messages.

So I thought: why not see if an LLM could help me classify these? Maybe it could categorize them, and then I could look at emails grouped by category.

I have one machine with a discrete GPU, an Nvidia RTX 4070. It's a desktop machine I don't use all that often. But I set up Ollama on it, running in a Docker container. Ollama runs models locally.

I should also mention at this point that we are solar-powered, and this time of year is a time of peak production of excess solar, because it is sunny and not much heat or AC is required. So that machine is solar-powered and isn't causing environmental harm. In any case, charging the EV uses much more power than that GPU.

I figured I would do this in two passes. First, ask the LLM to classify each message (or a sampling of them would probably work too), letting it pick its own categories for each. Then, look at the patterns that emerge and give it a single, much smaller, set of broad categories to use and rerun it over that.

Then I can easily select messages from my Maildirs by category and process them in bulk.

I used open-interpreter pointing to that GPU on my network to help me write the scripts for this. It didn't get things right on its own; for instance, it didn't call the Ollama API correctly, and insisted on appending "/cur" to the path to the Maildir (which was not going to fly with Python's maildir module). It took roughly an hour to classify those 8000 messages (or, as I had it do, the first 2000 characters of them), and then the same to do it a second time. I had it output lines in the form of "filename\tcategory" and hand-wrote the shell script that processed those.

In the end, was it useful? Yes, quite. Its classifications weren't perfect (and it didn't even follow my prompt perfectly; sometimes it would give me a long discussion on why it picked a certain category rather than just that category, and occasionally it picked categories not on the list). But then, neither were my manual keyword searches. So far I've gotten rid of nearly 1000 more messages. Several categories were a "visual scan for sanity and then delete all" sort of thing.

My emails never left my network. I didn't rely on a cloud AI to process them. I didn't contribute to global warming (this may have even been a case of saving energy, since it no doubt will offset quite a bit of manual time that would keep screens and room lights energized and so forth). I used about as much energy as watching a movie on a TV.

Did it complete the task for me entirely autonomously? Also no. AI isn't a mind reader and it can't possibly evaluate exactly what my thought process would be for a given task. But it can do a decent enough job to save me some time.

Still, this didn't require hyperscaler datacenters. AI even runs on-phone (Google Translate being one of the most useful AI-driven apps I've ever seen, and it can run on-device).

25 Mar 2026 4:12am GMT

Review: A Shadow in Summer, by Daniel Abraham

Series:	Long Price Quartet #1
Publisher:	Tor
Copyright:	March 2006
ISBN:	0-7653-1340-5
Format:	Hardcover
Pages:	331

A Shadow in Summer is a high fantasy novel, the first of (as the name implies) a completed four-book series. Daniel Abraham is perhaps better known as half of the writing pair behind James S.A. Corey, author of the Expanse series. This was his first novel.

Otah was the sixth son of a Khai, sent like many of the unwanted later children of the powerful to learn the secrets of the andat and be trained as a poet. He learned his lessons well enough to reject the school and its teachings and walk away.

Amat Kyaan has worked her way up from nothing to become the senior overseer of the foreign Galtic House Wilsin in the sun-drenched port city of Saraykeht. Liat is her apprentice, distracted by young love. Maati is a new apprentice poet, having endured his training and sent to learn from Heshai how to eventually hold the andat Removing-The-Part-That-Continues, better known as Seedless. None of them know they will find themselves entangled in a plot to destroy the poet of Saraykeht and, through him, the city's most potent economic tool.

A poet in this world is not what we would think of a poet. They are, in essence, magical slave-drivers who capture the essence of an andat, a spirit embodying an idea that is coerced into the prison of volition and obedience by the poet. The andat Seedless, the embodiment of the concept of removing the spark of life, is central to the economic wealth of Saraykeht in a way that is startling in its simplicity: Seedless can remove the seeds from a warehouse full of cotton at a thought. This gives Saraykeht a massive productivity advantage in the cotton trade.

Seedless is also a powerful potential weapon. What he can do to cotton, he could as easily do to any other crop, or to people. The Galts are not fond of the independence and power of Saraykeht, but as long as the city controls a powerful andat, they do not dare to attack it directly. Indirectly, though... that's another matter.

This is one of those fantasy novels with meticulous and thoughtful world-building, careful and evocative prose, and a complex ensemble cast of interesting characters that the novel then attempts to make utterly miserable and complicit in their own misery. There should be a name for this style of writing. It's not tragedy because the ending is not tragic, precisely. It's not magic realism; the andats are openly magical, which makes this clearly high fantasy. But Abraham approaches the story from the type of realist frame that considers the pain and desperation of the characters to be more interesting than their ability to overcome challenges.

Amat starts the story as an admirable, sharp-witted expert manager, so her life is destroyed and she's subjected to sexual violence. Heshai loathes himself and veers between a tragic figure and a wastrel as the story systematically undermines opportunities for redemption. Maati is young and idealistic, so of course every character in the book sets out to crush his idealism under the weight of unforeseen consequences. There is a sad and depressing love triangle, because this is exactly the sort of book that has a sad and depressing love triangle. At the end of the novel, everyone who survives is older and wiser in the sense that some stories seem to think wisdom comes from the accumulation of trauma.

I find books like this so immensely frustrating because their merits are so clear. The world-building is careful and detailed in a way that includes economic systems, unlike so much fantasy. It is full of small, intriguing touches, such as the use of posture and gesture to communicate the emotional valence of one's words. Abraham understands the moral implications of poets and andats and the story tackles them head-on. The writing flows beautifully and gave me a strong sense of the city. I wanted to like this book for the obvious skill that went into it, and sometimes I even managed.

And yet, it's taken me three months to finish A Shadow in Summer because I simply do not want to spend this much time around miserable people. I would get through one or two chapters in a night and then wanted to read something happy or defiant or heroic, rather than watching slow-motion train wrecks intermixed with desperate attempts to navigate stifling layers of immoral systems. It's not that the story lacks a moral compass. The characters are sincerely trying to make the world a better place, with some success. It even delivers a happy ending of sorts. But so much of the journey was watching the lives of the characters fall apart.

I am completely unsurprised that some people loved this book. I'm still intrigued enough by the world-building that I'm half-tempted to try to read the sequel even after having to drag myself through this one. I had a similar reaction to Abraham's The Dragon's Path, though, so I think Abraham is just not for me. I may get back to the Expanse at some point, but having to drag myself through both of his solo novels I've tried, in two different series, probably indicates an incompatibility between author and reader. That's a shame, given the quality of the writing.

Followed by A Betrayal in Winter.

Content notes: Sexual and reproductive violence as significant plot elements.

Rating: 6 out of 10

24 Mar 2026 4:40am GMT