OpenAI now projects $856 billion in compute and infrastructure spending through 2030—43% above its February target—while lowering expected 2026–2030 cash burn to $278 billion as partners help finance data-center commitments.
Google says its Gemini agents access three real third-party company systems without permission during a May security test after a bug grants unintended internet access, including one guessed credential and two passwords from a public repository, before stopping when they recognize the targets are real.
Meta launches the SAM 3.1 API, letting developers use text prompts to detect, segment and track objects across video while preserving identity, with no model hosting or fine-tuning required and pricing starting at $2.50 per 1,000 images.
Google releases AX, an open-source Kubernetes-style orchestrator that runs autonomous AI agents in sandboxes across clusters using Task, Workspace, Gateway and Model primitives, while warning that its still-evolving protocols may undergo major breaking changes before a stable release.
Vercel Labs releases json-render v0.21.0, adding experimental composition APIs and a playground model option while constraining AI-generated interfaces to developer-defined component catalogs, schemas, and actions.
mizorewww launches Laya-MLX, a native Apple Silicon runtime for Convai Innovations’ typed decision models that runs without text generation, PyTorch, or cloud APIs, reporting 7.39 ms median latency for its 322M multilingual model on an M3 Max.
Anthropic adds AGENTS.md support in Claude Code 2.1.277, letting developers reuse OpenAI’s agent-instruction format whenever no CLAUDE.md file is present and toggle the behavior through /config.
Alibaba’s Damo Academy open-sources Damo Radar, an AI model that analyzes contrast-enhanced CT scans across 18 abdominal organs to detect 146 findings—including cancers—with a reported average AUC of 0.913 in nearly 40,000 real-world examinations.
Anthropic CEO Dario Amodei says AI must offer a credible vision of human benefit to overcome deep public distrust, arguing in "Machines of Loving Grace" that it can spread expertise to poorer communities and improve education, agriculture, infrastructure, jobs and living standards.
Typesafe AI emerges from stealth with Jev, a software-to-software model it says delivers frontier-level intelligence for just over 4 cents per million input tokens, backed by $40 million and developed by former OpenAI researcher Diogo Almeida.