AI & Machine Learning

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US, China discuss AI dialogue mechanism and trade ahead of Trump-XI summit

US and Chinese delegations held “succesful” and “constructive” talks in New York on Sunday on Artificial Intelligence and trade, ahead of Chinese President Xi Jinping’s visit to Washington later this week. The two countries discussed setting up a dialogue mechanism as fears over AI security keep rising, and prepared to ease trade tensions as a

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Bounded AI Control Loops for Hybrid Cloud Operations

TL;DR AI-assisted hybrid operations must keep observation, policy, authorization, execution, and verification connected without granting one agent unrestricted access. Design bounded control loops with scoped tools, explicit owners, cost limits, recovery paths, and evidence of the resulting service state. The dragon illustration represents distributed coordination; it is not a design for one all-powerful controller. The

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VCF 9.1 Workload Mobility: Network Dependencies and Failover Contracts

TL;DR Moving or failing over a workload requires an approved destination, usable capacity, network and data dependencies, application validation, and an accountable decision owner. Design those requirements as a workload contract before choosing the mobility workflow. The rail-network metaphor helps explain the routes and handoffs, but it does not establish that every destination or movement

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OpenAI launches Astra for Law in US: What Sam Altman’s new AI tool means for lawyers

OpenAI has launched Astra for Law, a legal-focused version of GPT-6 Astra designed to assist with research, document analysis and drafting. The system combines AI with US case law, statutes, regulations and legal workflows, with selected law firms getting early access.

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AI Agent Evaluation: A Passing Test Is Not Production Proof

TL;DR AI agent evaluation must test the complete application, its enforcement boundaries, and its observed effects, not just the final answer. Separate task completion from control failures, exercise changed approvals and uncertain execution outcomes, and verify that the test itself worked. Then introduce production exposure within a defined resource and authority boundary. This final installment

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