January 2026

The Markup’s investigation into racial disparities in Los Angeles’s intake system for unhoused people has won a 2024 Sigma Award, which celebrates the best data journalism from around the world. Judges said the investigation “uses data to expose racial disparities and systematic issues that were previously largely supported by anecdotal evidence. The extensive methodology acts as a guide that other journalists can follow to do similar investigations in their own communities. The Markup did outstanding work in the […]

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The Markup, now a part of CalMatters, uses investigative reporting, data analysis, and software engineering to challenge technology to serve the public good. Sign up for Klaxon, a newsletter that delivers our stories and tools directly to your inbox. U.S. Customs and Border Protection is trying to build AI-powered border surveillance systems that automate the process of scanning people trying to cross into the U.S., an effort that experts say could push migrants to take more perilous routes […]

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Numbers such as π, e, log 2 or √2 have binary digits (bits) that look randomly distributed. They are very good candidates to generate randomness especially in cryptography. One way to assess their randomness is by proving that they are normal numbers. Such a proof has remained elusive for centuries. Here I focus on a different type of numbers that seem a lot easier to handle, such as (2π)-1 arccos(3/5). To test normality, the most well-known tool is […]

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EIP-7702, introduced with the Ethereum Pectra upgrade, represents a major turning point for the EVM ecosystem. It lets Externally Owned Accounts (EOAs) operate as smart contract accounts for a limited time. This brings Account Abstraction (AA) features, such as advanced transaction logic and flexible gas payments, to existing EOA addresses. Why EIP-7702 Infrastructure Matters EIP-7702 introduces a new “setCode” transaction type (0x04) that temporarily equips EOAs with powerful smart account functionality. However, without an open and reliable infrastructure to handle UserOperation […]

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Global sensitivity analysis of complex numerical simulators is often limited by the small number of model evaluations that can be afforded. In such settings, surrogate models built from a limited set of simulations can substantially reduce the computational burden, provided that the design of computer experiments is enriched efficiently. In this context, we propose an active learning approach that, for a fixed evaluation budget, targets the most informative regions of the input space to improve sensitivity analysis accuracy. […]

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