Infrastructure

As AI agents take on more complex development tasks, coordinating their work and controlling their actions become increasingly important. Anthropic and Arcjet approach these challenges from different angles, while AWS and Euclyd address the infrastructure constraints of running AI models efficiently. Beyond development and infrastructure, Google Discover is testing how AI-generated overviews could reshape the way readers explore published content. All sources used to prepare this edition are listed at the end of the article. ...

AI agents are reaching beyond the chat window, bringing new questions about who controls the systems they can access. Google Home’s agent integrations and Mandiant’s security architecture put those boundaries in focus, while Virginia’s data-centre measures raise questions about the physical footprint of AI services. The edition also explores machine forecasting as a product category and the role of proprietary data in ad-tech consolidation. In this edition — jump to a story ...

As AI systems gain autonomy, oversight, security and physical capacity become harder to separate. OpenAI’s approach to reporting model misalignment and Anthropic’s account of autonomous cyber operations put those risks in focus, while sovereign-AI consolidation and data-centre energy flexibility expose the infrastructure decisions behind deployment. The edition also looks at proposed remedies in ad tech, where control over platforms and access to competition remain contested. In this edition — jump to a story ...

Turning AI ambition into working systems requires more than model advances. Today’s stories examine the gap between safety debate and coordination, Anthropic’s plans for computing capacity in Australia, and Factory’s push to measure what coding agents actually deliver. European inference hardware and a new Google Ads benchmarking tool complete the picture: infrastructure choices and performance measurement matter well beyond the model itself. In this edition — jump to a story ...