AI Agents Are Learning to Predict What Users Want—Before They Ask for It
Researchers in China built a model that uses an AI’s downtime to prepare for users’ next question before they ask it.
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As AI agents move from experiments to production, AWS, Cloudflare, and others are redesigning cloud infrastructure for a future dominated by machine-generated internet traffic instead of human users.
Read full articleResearchers in China built a model that uses an AI’s downtime to prepare for users’ next question before they ask it.
AWS rebuilt Amazon OpenSearch Serverless from the ground up for agentic AI and dynamic workloads. Get instant autoscaling and up to 60% cost savings.
The update positions OpenSearch as foundational infrastructure for enterprises, enabling faster, scalable search.
Google DeepMind CEO Demis Hassabis believes progress toward artificial general intelligence (AGI) is moving faster than expected and that society now has only a few years to prepare. He believes AGI could arrive around 2030, though acknowledges it could be here in 2029 — or even sooner. In an interview with Axios, Hassabis said that today’s AI agents — systems capable of performing tasks independently — should be viewed as a sort of “practice run” for significantly more powerful AI in the future. He also warned that governments, economists, and society at large are not taking this development seriously enough. One particular risk he highlighted is that AI systems in the future might begin to improve their own development. “All the leading labs are pretty focused on that,” Hassabis told Axios. “It will yield clear benefits in the form of faster research. But there are also risks associated with that type of system.”
Google Pay is overhauling its payment infrastructure for an impending wave of transactions from AI agents. The latest updates introduce the Universal Commerce Protocol and a new server architecture, positioning Google Pay as a central clearinghouse for purchases executed by autonomous agents rather than human users. AI agents – designed to perform tasks like booking […] The post Google Pay preps for AI agents with Universal Commerce Protocol appeared first on AI News.
Modern AI agents built on top of large language models (LLMs) are designed to run continuously.
Snowflake said it plans to acquire US-based startup Natoma to boost governance, security, and connectivity for AI agents operating across heterogeneous enterprise environments, amid growing efforts by organizations to move agentic AI workflows from pilots into production. The cloud data platform provider is betting that enterprises will increasingly require centralized governance, identity controls, and auditability as AI agents begin interacting more deeply with internal applications, APIs, and business workflows through the emerging Model Context Protocol (MCP) standard, an area in which Natoma claims to specialize. Natoma’s platform, which provides MCP-based tool access along with governance and observability capabilities, will be integrated into Snowflake to help enterprises securely connect Cortex Agents, Snowflake Intelligence, Cortex Code, and other AI platforms with enterprise systems spanning SaaS applications, cloud environments, VPCs, and on-premises infrastructure through M
The tech giant says a breakthrough in data-center networking has dramatically accelerated the flow of information through its massive cloud infrastructure.