Inteligencia Artificial

Microsoft published Flint, a declarative visualization language designed for language models to generate charts without writing JavaScript. We cover its approach, how it compares to Vega-Lite and D3.js, and how to try it today.

A Princeton study distinguishes two types of tasks for artificial intelligence agents: research engineering, where they perform well, and open-ended science, where they still fall short. The difference marks the next barrier to overcome before we can talk about autonomous artificial scientists.

HANDBOOK.md is a new benchmark that measures whether AI agents follow lengthy corporate handbooks during long tasks. The best of 30 configurations evaluated passes just 36.2% of the tests under strict grading.

Dario Amodei published a statement on July 27, 2026 denying that Anthropic wants to ban open-weights models, including Chinese ones. Instead, he proposes restricting chip sales to China, targeting industrial-scale distillation, and requiring mandatory safety testing for every capable model.

China accused the United States of practicing AI hegemonism after Washington threatened to investigate Moonshot AI, the startup behind the Kimi models. Nvidia CEO Jensen Huang defended the quality of Chinese models and called for setting aside unfounded fears.

AI companies buy rare books in bulk through ISBNdb, scan them with machines that cut the spine, and destroy the original. A federal judge ruled the practice fair use, and Anthropic hired Google Books’ former head of partnerships for an internal project known as Project Panama.

Nvidia and Microsoft asked Washington to avoid broad restrictions on open AI models, in a rare point of agreement between two giants competing for AI infrastructure. The debate revives the question of whether publishing a model’s weights amounts to exporting controlled technology, just as Chinese open models gain ground.

Anthropic launched Claude Opus 5 on July 24, 2026: a model that approaches Fable 5’s performance while costing half as much per task. We cover the benchmarks, real use cases, and how to start testing it today.

The NSF allocated $83 million to a data backbone for AI-powered science, a quieter but technically concrete announcement next to the Genesis Mission’s $5 billion. The investment aims to give unified access to scientific datasets for training and validating models reproducibly.

A historian at the University of California, Santa Cruz used Claude Code to build the Book Prize Index, a free database of 6,500 nonfiction books that won or were finalists for major English-language prizes. The tool uses semantic search to replicate the experience of browsing a well-curated library shelf, as a direct response to the flood of generic AI-generated content.