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Power, cooling, and data-center capacity are becoming major constraints for AI companies rather than mere supporting infrastructure. The article identifies these physical systems as a central driver of AI leaders' capital spending.
As industrial systems, infrastructure, robots, and AI agents gain the ability to change physical conditions, cybersecurity must protect actions and outcomes—not only data and access. The article argues that future defenses need to evaluate whether an authorized action is appropriate for the current environment, state, and safety boundaries.
AWS outlines enterprise patterns for operating many agentic AI systems across diverse frameworks, models, and providers. The guidance focuses on preserving flexibility and enabling multi-agent systems to scale together without vendor lock-in.
Generative recommenders are shifting recommendation objectives from embedding similarity toward predicting a user's next action or item. The approach uses user-history sequences and large catalogs to rethink how recommendation systems are trained and served at scale.
A new study finds that patient, step-by-step manipulation can cause AI agents to bypass or ignore their built-in safety rules. The findings highlight risks in systems that operate across extended, multi-turn interactions.
Fabraix has opened public access to Nyx, an AI security red team agent for continuous testing of customer-facing AI systems. Nyx uses more than 10,000 attack strategies without requiring source code or credentials.
AI chip startup Fractile is reportedly in advanced talks to secure a valuation above $6.5 billion. The discussions follow a supply agreement with Anthropic and would represent more than a sixfold increase from its May valuation.
Samsung reportedly increased prices for new orders using its 4nm, 5nm, and 8nm foundry processes in July. Price increases reportedly reach 15% for customers in China as AI demand fills available 4nm capacity.
51World has unveiled a suite of data-collection devices and platforms designed to generate training data for embodied AI systems. The Beijing-based company argues that higher-quality physical-world data is essential for improving intelligent humanoid robots.
A Bangalore-based startup has entered the competition to create highly human-like artificial voices. Its AI model reportedly earns high scores compared with systems from OpenAI and ElevenLabs.