2026-04-29 15:11:50
Apparently, the words we use and how we structure our sentences in writing is nearly as unique as our fingerprints. Kelsey Piper has been using this to benchmark new LLMs by entering text and asking who wrote it. Anthropic’s Opus 4.7 model was the first to return all the correct answers.
For WaPo opinion, Megan McArdle tested the search with her own unpublished text.
Would Claude do better or worse with something more modern? I fed Claude a different opening chapter from an unpublished science fiction novel I started right before the pandemic — I contain multitudes — and this time Claude needed only 1,132 words. The eulogy I gave for my mother, lightly edited to remove some too-specific biographical details, was even faster: Depending on the passage, Claude was able to peg me as the author in as few as 124 words.
I’m too scared to try this on myself, but I’ll assume it works. Lucky for me, I’ve always written and made things with the assumption that my mother would see it.
However, if you publish words or share thoughts on social media, I hope you don’t value online anonymity too much.
Tags: chatbot, Megan McArdle, privacy, Washington Post
2026-04-28 17:18:10
For Rest of World, Rina Chandran reports on the big difference in excitement:
As AI adoption increases globally, anxiety about AI is rising — but so is optimism about its benefits, according to a recent study from Stanford University’s Human-Centered Artificial Intelligence center. Not in the U.S. To the prompt, “products and services using AI make me excited,” only 38% of respondents in the U.S. said yes, in comparison to 84% in China. Southeast Asians are among the most optimistic about AI, with 80% of Indonesians, 77% of Malaysians, and 79% of Thais agreeing.
The difference in sentiment appears to be related to each country’s trust in government regulation. From the Stanford study, here are the percentages for those who said they trust their government:
Singapore is over 80 percent trusting. Meanwhile, the United States is the lowest at 31 percent.
This isn’t all that surprising, but I wonder why there is such a big difference. Is there an overall distrust in government and AI companies in the United States? With the largest companies in the United States, do we get a closer look and therefore more skepticism?
Tags: country, excitement, Rest of World
2026-04-28 15:03:15
For NYT Opinion, Paul Ford on the challenges for AI companies to build ethical systems:
All the while, money keeps gushing in. You start out transparent, sharing your journey, but then before an initial public offering of shares, you must honor the S.E.C.-mandated quiet period and restrict promotional communications. After that, the transparency never quite returns. The market demands a rising stock price. Your company still makes a lot of software, but a huge amount of time goes to tax strategy and compliance.
At that scale, people start to blur together, and human users can become aggregate pools of statistics and growth vectors that go up and down — a mulch into which you plant your products.
Cue the Harvey Dent scene about living long enough to become the villain.
Tags: ethics, New York Times, Paul Ford
2026-04-27 15:45:45
The Economist shows probabilities that a person votes for each party, given a set of demographics.
But the electorate is not monolithic. The Economist has built a statistical model of it based on a survey of voting intentions by More In Common, a pollster. Our model estimates the probability that any individual will vote for one of Britain’s main political parties based on the eight characteristics that most influence voters’ choices: sex, age, ethnicity, region, education, employment status, type of housing and whether it is in a rural or urban area. In different combinations these characteristics yield 275,000 different voter profiles. Each week we get new polling data and update our calculations.
Select the demographics, such as sex, age, race, and education, and see how each factor swings the probability for each party. The overall prediction shows at the bottom.
The 2008 decision tree by Cox comes to mind.
2026-04-24 15:03:39
The Kyoto Aquarium in Kyoto and the Sumida Aquarium in Tokyo each have detailed relationship diagrams for their penguins. The above is for Kyoto.
The networks are framed as reality shows with weddings, divorce, and cheating, along with likes and dislikes of each penguin. Watch out for the penguin named Pon:
Kuruma and Tako live next door to each other, and Pon has been visiting each of them in turn for snuggle sessions. Both boys are obsessed with Pon, but it seems neither of them can fully satisfy her. What’s the fate of this neighborhood love triangle!?
Oh my.
I don’t know why these exist, but it’s nice that they do. The aquariums have updated the networks each year since 2024.
[Thanks, Charlotte]
Tags: Kyoto Acquarium, penguin, relationships
2026-04-24 01:35:45
Even if only military areas are targeted, civilian and commercial structures are also damaged, because the real world isn’t separated into discrete, selectable items on a map. Bloomberg analyzed satellite imagery to estimate the type of areas damaged in the strikes.
Each detection was classified into one of six categories: military, industrial, civilian, commercial, government, or unclassified. We separated government facilities from the broader civilian category because these buildings may serve dual military-civilian purposes. Rather than forcing a single label, the analysis preserves the full mix of land use types around each detection — a site classified as “military” might also be 20% residential and 10% commercial, reflecting the mixed-use reality of urban areas.
Sets of Voronoi diagrams are used to show the percentage breakdowns for each detection.
Tags: Bloomberg, damage, Iran, satellite imagery, war
