Plus: Former national security advisor John Bolton pleads guilty in classified-materials case, Microsoft helps take down major infostealer infrastructure, and more. A WIRED investigation this week offers insight into a predictive policing program in Bristol, England that has involved 23 separate models over more than a decade, intended to score the likelihood of specific individuals will perpetrate or be victims of different crimes. The investigation draws on data from public records requests and other reporting to reveal a messy law enforcement apparatus that has real implications for the community--but that most people in the area know nothing about. After the identities of members of Peter Thiel's private "Dialog" group were exposed last week, the organization claimed that a "criminal" hacker was behind the breach. But evidence shows that members' personal information--including that of a White House intelligence official and an active-duty special operations officer --was publicly accessible and likely exposed as the result of a Dialog website misconfiguration .

British Police Built a Sprawling Crime-Prediction Machine. Some Results Couldn't Be Trusted As UK police embrace the AI revolution, a WIRED investigation reveals the messy inside story of one region's experiment with predictive analytics. The Think Family Database holds records on close to half a million people who live in the city of Bristol, England. For many years, few of them knew anything about it. Launched in 2016 by the Bristol City Council and the regional Avon and Somerset Police, the database has stored all manner of sensitive information--police intelligence reports, housing status, mental health records, teenage pregnancies, enrollment in parenting courses, free school meals. On top of this sensitive data, officials built machine-learning models to assign scores to thousands of adults and children. They hoped to build what they called a "picture of threat, harm, and risk" in the region. At an event in early 2022 to help officials tackle child exploitation crimes, one police data scientist described part of the approach this way: "I essentially dump all that data in a big bucket and stir it with a data-science spatula, and we come out with a lovely risk score for everybody." This risk scoring inside the Think Family Database was just one part of Avon and Somerset Police's sprawling predictive analytics program.

Mathematicians stunned by AI's biggest breakthrough in mathematics yet An 80-year-old maths conjecture that has eluded the world's greatest mathematicians has been cracked by an artificial intelligence model built by OpenAI. The result has stunned experts and is being hailed as a seismic moment for AI's mathematical ability. "This is a problem that I didn't expect to see solved in my lifetime," says Misha Rudnev at the University of Bristol, UK. "It's absolutely a bomb." Tim Gowers at the University of Cambridge wrote that the solution is "a milestone in AI mathematics" in a blog post accompanying the work . "If a human had written the paper and submitted it to the and I had been asked for a quick opinion, I would have recommended acceptance without any hesitation. No previous AI-generated proof has come close to that."

A clump of human brain cells can play the classic computer game . While its performance is not up to par with humans, experts say it brings biological computers a step closer to useful real-world applications, like controlling robot arms. In 2021, the Australian company Cortical Labs used its neuron-powered computer chips to play . The chips consisted of clumps of more than 800,000 living brain cells grown on top of microelectrode arrays that can both send and receive electrical signals. Researchers had to carefully train the chips to control the paddles on either side of the screen.

Implicit Neural Representations (INRs) have previously been used to represent and compress image and video content, demonstrating relatively high decoding speed compared to other methods.

This makes it easily extensible and much more expressive than existing toolkits. It supports all 9 and all 10 of the decision-based group metrics of two popular review articles.