Nobel Laureate John Jumper Departs DeepMind for Anthropic

TechCrunch reports that John Jumper, a Nobel laureate and prominent researcher at Google DeepMind, is leaving the organization to join Anthropic. Jumper is widely recognized for his contributions to protein structure prediction, work that was central to his Nobel recognition. According to TechCrunch, Jumper is not the only notable name to have recently departed Google DeepMind, suggesting a broader shift in talent movement across the AI research landscape. Anthropic, the AI safety and research company behind the Claude family of models, continues to attract high-profile figures from competing organizations.

The Atlantic Publishes Searchable Database of Music Used in AI Training

The Verge reports that The Atlantic has released a publicly searchable database of music tracks identified as being used to train AI models. The database was compiled by Atlantic reporter Alex Reisner, who uncovered four distinct datasets of music used as AI training data. Two of the datasets are particularly large, containing approximately 12 million and 9 million tracks respectively. The remaining two datasets are smaller but still represent a substantial volume of training material. The Verge notes that the full contents of all four datasets have been made searchable for public access, offering a rare level of transparency into the composition of AI music training corpora.

In the Weights Launches as an AI-Focused Vanity Search Tool

TechCrunch highlights the launch of In the Weights, a new search tool designed to let users discover how prominently they or their content appear within AI model training data. The tool is described as an AI-centric take on the concept of a vanity search — similar in spirit to searching for one's own name online, but oriented specifically around presence in AI training weights and datasets. Further technical details about the tool's methodology were not specified in the report.

These stories reflect ongoing developments across AI talent acquisition, training data transparency, and emerging tooling built around AI systems.