"It is a sin to be silent when it is your duty to protest."
~ Abraham Lincoln
Millions turn out for "No Kings" rallies held worldwide to protest against Trump
"When a clown moves into a palace, he doesn’t become a king. The palace becomes a circus."
Daily Dose of Dust
Jozef Imrich, name worthy of Kafka, has his finger on the pulse of any irony of interest and shares his findings to keep you in-the-know with the savviest trend setters and infomaniacs.
''I want to stay as close to the edge as I can without going over. Out on the edge you see all kinds of things you can't see from the center.''
-Kurt Vonnegut
Powered by His Story: Cold River
"It is a sin to be silent when it is your duty to protest."
~ Abraham Lincoln
Millions turn out for "No Kings" rallies held worldwide to protest against Trump
"When a clown moves into a palace, he doesn’t become a king. The palace becomes a circus."
“A reader lives a thousand lives before he dies, said Jojen. The man who never reads lives only one.”
This website has an endless collection of less-famous Robert Doisneau shots to click through.
The Guardian – If you can’t hold it, you don’t own it’: why media fans want to escape algorithms with CDs, DVDs and vinyl. People describe their return to physical media – whether to protect data, support artists, or retain control of one’s choices. ‘If you can’t hold it, you don’t own it’: why media fans want to escape algorithms with CDs, DVDs and vinyl…”
In a system predicated on voluntary compliance, taxpayer privacy is an evergreen concern. But in recent weeks, three disparate events have raised questions about the security of taxpayer data—and what information the government should collect through the tax system.
What are these events? First, the Treasury Inspector General for Tax Administration’s report on IRS employees’ access to celebrity taxpayers’ return information. Second, allegations that IRS officials leaked an employee’s tax information to the Department of Justice in retaliation for whistleblowing. Third, the controversial inclusion of a citizenship or work authorization question on Form 1040, that hallowed pillar of individual filing and frequent political football.
Details and connections, below the fold.
QuarterMile: “I used to struggle with life. I still do sometimes. But things have gotten a lot better since I started writing things down. Things that, if I do them, make life a little nicer to live. And now it’s really easy. I just have to remember all of these things, all of the time.
And I have to do them. Always. Easy! You can live the life of your dreams too. If, like me, you only remember and follow this list. Bonus fact: if you read the below list then you are also exempt from ever having to read a self-help book again. Just a few from an excellent, long list:’
Wenzel Hablik (1881) was a painter, graphic artist, architect, designer, and craftsman from Bohemia of the early twentieth century, associated with German Expressionism. At the age of six, he found a specimen of crystal, and saw in it “magical castles and mountains” that would later appear in his art. Hablik died at Itzehoe in 1934. The Wenzel Hablik Museum was established in the city of Itzehoe in 1995. The museum contains much of his art, as well as his collections of crystals and minerals, seashells and snails.
More of his work, found on Tumblr.
Duchess of Swabia, Agnes of Waiblingen (1072–1143), was the daughter of Holy Roman Emperor Henry IV, and lived to be about 70 years old. She married twice, had 17 children and became the mother of German kings and Holy Roman emperors. While medieval women rarely ruled in their own right, Agnes’s personal achievement was the deliberate cultivation of an extraordinary network of children and she positioned them meticulously across the geopolitical chessboard of Europe. Agnes was far from a passive political figure. Upon the sudden death of her second husband, Margrave Leopold III of Austria, in 1136, she actively secured the political succession of Austria. She was a prolific patron of the church, co-founding major institutions that remain culturally significant today.
That’s about all the juice you can dig up on her, so this absolutely feels like a research project crying out for a historian.
Now and again, Geiser finds himself wondering what he really wants to know, what he hopes to gain from all this knowledge. (Man in the Holocene, Max Frisch, tr. Geoffrey Skelton, p. 90)
What I Read in August 2026 – what he hopes to gain from all this knowledge
The secret to a good night’s rest? Let sleeping dogs lie — next to you NBC News
A New ‘Super Ice’ Is 10 Times Stronger, Bringing It Close to The Strength of Concrete Science Alertp
Background knowledge: a neural network, conceptually, has billions of little things called neurons. One goal of so-called "interpretability" would be to be able to look at each neuron and say what it does for the network.
However, there is an observed phenomenon called "polysemanticity" wherein it seems that sometimes a single neuron seems to be for multiple different things. An early example of this was a finding that a single neuron in this image model seems to be for both animals and cars: Dragons and Cars …
An incendiary post from a prominent researcher suggests that AI is actually more predictable than we thought.
Boiled down, Cammarata’s main contention is that generative-AI models are not actually black boxes, contrary to the common perception that these systems are so big and labyrinthine as to be nearly impenetrable. In fact, Cammarata argues, there is a relatively clear path toward understanding them. If that’s the case, the material significance could be tremendous: It would provide a way to map AI models’ inner workings and, in turn, perhaps prevent them from wreaking all sorts of harm—autonomously hacking companies and sovereign nations, encouraging users’ delusions, appearing to deceive AI researchers themselves. There is an entire field of research, called “mechanistic interpretability,” devoted to the study of just this.
The argument is just as important as the person making it. Cammarata, a former OpenAI employee, is a respected figure in his field. Years ago, he played a key role in establishing the opposite claim, which is now common wisdom: that neural networks, the software architecture that generative AI is built on, are impossible, or at least very difficult, to understand. In this new essay, Cammarata, who now works at the AI-research company Goodfire, essentially says that he and his entire field have been wrong ever since. “The claims here are viscerally shocking,” one observer wrote. Or, as another wrote on X, they are “big big big big.”
Read: Imagine every AI agent on Earth buying the same cheap paper towels
Neural networks, inspired by the human brain, consist of layered connections among individual nodes, or “neurons,” that activate and send information to one another when responding to a query. Earlier research, including Cammarata’s, established that individual machine neurons can activate in response to many different, unrelated topics—for instance, one neuron can correspond to images of cat faces, cat legs, and the front of cars. Nobody was sure why this happened, but one explanation was that, because AI models contain far more information than they have neurons, they have to repurpose these nodes. Regardless, the basic units of an AI model having seemingly arbitrary, multitudinous functions would make it very difficult to understand what is going on under the hood.
Cammarata now thinks that individual neurons can be understood and that each has a self-consistent function. Neural networks are not “tangled knots,” he wrote, but “clean.” He found that the cat-face and car-face neuron, for instance, was actually responding to things with a V-shape—including V-shaped flames and jets of water. This would make AI’s internal mechanisms relatively straightforward and predictable rather than mysterious and nebulous. And if we can harness that understanding, some people in the industry believe, AI will be much less likely to go haywire and, say, kill us all. “This is truly one of the greatest cases for optimism in years!” the OpenAI researcher Adam Majmudar wrote on X.
Not everyone agrees with Cammarata. For one, his 26,000 words were merely a “working hypothesis” for a “forthcoming technical paper” and were thus hard, on a technical level, to evaluate. And the neural networks he studied most closely were vision models, which are generally simpler and better understood than the language models underlying ChatGPT and Claude. Cammarata could be mistaken, or he could be overstating his case. The blog post isn’t peer-reviewed, and the forthcoming paper probably won’t be, either, as is typical in the field. The research itself is something of a black box. (Cammarata, who did not immediately respond to a request for comment, wrote on X earlier today that he appreciates all of the discussion and that his approach “seems promising so far” for “bigger modern language models.”)
Discussions of Cammarata’s essay have revealed philosophical rifts. “This is interesting work, but I don’t think it’s a significant update to the big picture,” Neel Nanda, who leads mechanistic interpretability at Google DeepMind, wrotein his appraisal of Cammarata’s findings. Even if researchers could approximate the function of every neuron in Claude Mythos 5.1 or GPT-6 Astra, that’s not the same as understanding how they connect and how the network works as a whole. Physicists have good models of atoms and interatomic interactions, but they cannot from first principles explain or predict every physical event (hence unpredictable extreme weather or, for that matter, the notion of free will). You know all of your friends from school, various workplaces, and the local softball league, but you can’t always know whether they’ll get along at your birthday party. More to the point, insights into the inner workings of an AI model will not necessarily produce insights into how to make the technology more reliable. Interpretability may be necessary to build safer AI models, but it is by no means sufficient.
If generative-AI models are actually legible under the hood, that would undoubtedly help make the technology safer. But many people in Silicon Valley, and especially employees at OpenAI, are discussing Cammarata’s blog post with a breathless enthusiasm that echoes Silicon Valley’s long track record of easy technical solutions and grand promises—an attitude that belies its mixed record on following through.
Any research finding that pertains to AI safety will require an industry chasing multitrillion-dollar public offerings to slow down and take a long, hard look at itself. Perhaps even more concerning than an unintelligible superintelligence is the fact that a group of companies openly state that they don’t really know what they are building—and then continue to push that technology to extremes anyway. If Cammarata is correct, AI companies will have to work with one another, outside auditors, and governments to figure out how to translate such a breakthrough into safe and reliable products. And right now, absent any serious regulation, nobody can decide to take such action other than the companies themselves. All of which suggests that the real black boxes are OpenAI and Anthropic themselves.
Why Plain Text Is Still One of the Best Technologies We Have
Dead Parrot BBS: “There are not many computer file formats I would trust to still be readable fifty years from now, but plain text is one of them. That may sound like faint praise. A text file cannot embed a spreadsheet, preserve elaborate page layouts, run a presentation, or provide many of the conveniences we expect from modern applications. What it does instead is store text in one of the simplest and most widely understood forms in computing, and that simplicity is a large part of why it has lasted.
Almost Nothing to Go Wrong – The Unicode Standard defines plain text essentially as a sequence of character codes, without the additional formatting information associated with rich text. Fonts, colors, layout, and similar presentation details belong somewhere else. From a user’s point of view, the important part is simpler: the file contains the text itself without requiring a particular application to make sense of it.
I can create a text file on Linux, copy it to a Windows machine, put it on a web server, open it in a terminal, search it with command-line tools, edit it with any number of programs, or send it to somebody using an entirely different system. Very little about the file depends on how it was created. That is different from many document formats, where the information is closely tied to the application or family of applications that understands the format.
Sometimes that is harmless. Sometimes the format is well documented and broadly supported. In other cases, opening an old file means hoping that suitable software still exists. Plain text has very little of that baggage…”
Popular erectile dysfunction pill may deliver additional boost to aging men
The vast resorts and luxury hotels of France’s Tarentaise Valley are renowned in the ski world — but just to the south, the less-visited Haute Maurienne offers quieter delights


Sydney is a city that’s always in a rush. Standing defiantly amid all of this is Slow Lane Brewing.
Hidden away from the hustle and bustle on a quiet backstreet in Botany, this small South Sydney brewery opened in 2020 and instantly made a big impression with their modern take on traditional, European-inspired beers.
While most budding breweries launch with a lager or a pale ale, husband-and-wife team Alex and Yvonne Jarman announced their intent early, debuting with a Belgian blonde ale and a saison aged for three months in a wine barrel with Brettanomyces yeast for added complexity.
The accolades soon followed. In their debut year, they won Champion Mixed Culture Beer at the Indies for their Botany Weisse. In 2021, their Threefold Belgian tripel took home trophies at the Sydney Royal Beer & Cider Awards and a gold medal at the Australian International Beer Awards.
Despite their Euro focus, Slow Lane’s origin story actually started in the US, where Alex And Yvonne worked for five years. While living in New York and then California, the couple visited countless breweries and fell in love with those focused on reinterpreting classic continental styles, so much so that Alex, already an avid homebrewer, quit his corporate job to work at breweries before returning to Sydney in 2017 with a vision to start one of their own.
Once home, Alex dove wholeheartedly into his new career, blending new ideas with old world techniques and revelling in funky yeasts, open ferments and can-conditioning. Along the way, Slow Lane’s beer range has evolved and expanded as they experiment with new gear and more modern styles. The purchase of three horizontal lagering tanks means he can now craft the European lagers he’s always wanted to – while he’s also been producing more contemporary styles – hazy IPAs and West Coast pilsners – with dazzling results.
Like the beers, the brewery and taproom channel a similar mixture of traditional and contemporary. It may reside in an industrial warehouse but the stark white walls and oak barrels stacked to the ceiling hint at a beer cellar in Belgium. There’s a feeling of striking simplicity, which is mirrored in the modernist branding and minimalist can art.
More recently, Alex and Yvonne have been busy expanding that space to offer even more options for thirsty and hungry visitors. The wooden-panelled bar now boasts 14 taps (including two Czech side-pour Lukr taps) alongside a large selection of wines, spirits, cocktails, ciders and spritzes, if beer ain’t your beat.
There’s also an in-house kitchen dishing out Neapolitan-style pizzas, share plates, cheeses and charcuterie plus a bigger beer garden out front with wine barrel tables. On the events side, punters can catch live music on Saturday nights and Sunday arvos as well as themed months celebrating different beer styles from around the world.
Wash it all down with some award-winning brews and you can’t lose with this small yet mighty brewery.
Jason Treuen & Mick Wüst