
AI Browser Automation: How Agents Work Without APIs
AI browser automation lets agents use website interfaces when an API is unavailable. Learn how page interpretation, authenticated sessions, action checks and human oversight affect reliability.
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AI browser automation lets agents use website interfaces when an API is unavailable. Learn how page interpretation, authenticated sessions, action checks and human oversight affect reliability.

Meta has released Muse Ember, its smallest and most cost-efficient Muse AI model, designed for repetitive agent tasks and complex reasoning. Priced at $0.10 per million input tokens, it…

Meta has introduced Spaces for its Muse AI assistant, letting users create personalized planners, trackers, and project boards through conversational prompts. The feature supports connected…

Axiom Math has released a formalized version of the Stacks Project, an extensive mathematical reference covering algebraic geometry. Its AI agents generated approximately 16 million lines…

Y Combinator-backed startup Discovered Materials has launched a $1 million prize program targeting five unresolved materials science problems. The initiative aims to test AI's scientific…

Box has introduced Context Retrieval, an enterprise search engine powered by Nvidia Nemotron models. The company says the technology can deliver answers four times faster, improve retrieval…

AI agent training environments let developers recreate real software tasks, evaluate agent actions and safely test learning before production deployment.

Continual learning for AI agents can turn reviewed production feedback into model improvements. The process requires trusted data, measurable outcomes, careful retraining, and strict…

Uber received just four AI-agent ride bookings and approximately 500 AI-generated Uber Eats orders during Halloween week, compared with 320 million total transactions. The figures reveal…

Parallel AI coding agents can work simultaneously when Git worktrees separate files and branches. Learn what this architecture solves and why merges, tests, and access controls still matter.

AI semantic layers can reduce conflicting business reports by connecting natural-language questions to consistent metrics, governed database queries and verifiable results.

AI process discovery helps businesses understand how work moves between applications, identify repetitive tasks and evaluate which activities are suitable for automation without overlooking…