AI News Daily
AI developments selected from public sources
- 10
- major stories
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- sources
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- first-party stories
Lead story
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Oracle has issued a force majeure notice to the developer of Project Jupiter, the Stargate data center campus located in New Mexico, Bloomberg first reported on Thursday. The notice is not an intent to withdraw as the anchor tenant, but rather allows payments to be deferred if the campus misses its 2028 launch target. The campus is designed to carry 2.45 gigawatts and relies on Bloom Energy's gas fuel cells; the Energy Transfer pipeline supplying it has been delayed by nearly six months to February 1, 2027, due to repeated permit denials, and the air quality permit for the fuel cell system is still under review, with the state environmental department required to decide by November 23. Oracle said the project remains on schedule, and Blue Owl Capital said the notice does not change its financial commitment to the multi-year project.
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AWS explains how to build multi-account AI agents using Amazon Bedrock AgentCore Gateway and MCP: the platform account runs agents through AgentCore Runtime and performs LLM inference via Amazon Bedrock, while each line-of-business account packages its data and tools as MCP servers, with the Gateway serving as a single MCP endpoint for unified tool discovery and invocation. The solution also combines AgentCore Identity with Okta for OAuth 2.0 M2M authentication, and uses Policy in AgentCore (Cedar) to achieve fine-grained authorization.
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Google Research has released a unified multi-agent framework for automatically generating temporally coherent long-video narratives, addressing identity drift and cascading failures in existing linear pipelines. Built on top of Gemini and Veo as an orchestration layer, the framework consists of four parts: AI video co-director uses multi-armed bandits for global creative search, CANVAS plans multi-shot visual continuity through persistent visual memory, A²RD generates segment by segment autoregressively while maintaining multimodal video memory, and VQQA uses visual question answering to generate semantic gradients for closed-loop prompt optimization. Evaluations show that AI video co-director reaches a peak quality score of 81.4 on GenAD-Bench, CANVAS improves scene-reappearance continuity on ST-Bench and HardContinuityBench, A²RD reduces layout drift on VBench-Long and LVBench-C, and VQQA achieves quality gains on T2V-CompBench, VBench2, and VBench-I2V.