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AWS CEO responds to data center controversy: no longer using NDAs
Amazon Web Services CEO Matt Garman said in a blog post that the company no longer uses non-disclosure agreements (NDAs) when partnering with government agencies to build data centers. He also rebutted four claims about data centers—that they consume too much water, drive up electricity prices, cause serious pollution, and bring no benefit to communities—saying that direct water use by data centers accounts for only 0.5% of U.S. industrial water use, that backup generators sit idle 99.9% of the time, and that over the past three years Amazon has invested more than $1 billion in U.S. communities where it has data centers.
Amazon Web Services CEO Matt Garman said in a blog post that the company no longer uses non-disclosure agreements (NDAs) when partnering with government agencies to build data centers. He also rebutted four claims about data centers—that they consume too much water, drive up electricity prices, cause serious pollution, and bring no benefit to communities—saying that direct water use by data centers accounts for only 0.5% of U.S. industrial water use, that backup generators sit idle 99.9% of the
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AWS open-sources the decision model Strands Decider 2B, which can run locally
AWS has released the open-source decision model Strands Decider 2B, built on Qwen3.5-2B. Instead of generating text, it selects from preset options with a confidence score; it is fast, low-cost, and small enough to run locally. The model was developed by AWS Distinguished Engineer Marc Brooker on his own after seeing TypeSafe's Jev, briefly topped the Jevbench ranking for models of the same scale, and was subsequently packaged and released by Strands Labs. Brooker said that AWS customers' agent workflows do not always need the full capability and cost of an LLM, and that this type of model can serve as a decision step within workflows, delivering more reliable performance and lower latency thanks to its confidence scores and closed answer domain.
AWS has released the open-source decision model Strands Decider 2B, built on Qwen3.5-2B. Instead of generating text, it selects from preset options with a confidence score; it is fast, low-cost, and small enough to run locally. The model was developed by AWS Distinguished Engineer Marc Brooker on his own after seeing TypeSafe's Jev, briefly topped the Jevbench ranking for models of the same scale, and was subsequently packaged and released by Strands Labs. Brooker said that AWS customers' agent
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An agentic conversational video intelligence solution built on AWS
AWS has released an agentic video intelligence solution based on the Strands Agents SDK, in which a single AI agent orchestrates Amazon Bedrock, Amazon Rekognition, and Amazon Transcribe at runtime, allowing users to query video content by asking questions in natural language. Responses for already-analyzed content are returned within 1 second, while the first analysis of a new video takes 5–10 minutes; one media and entertainment company used it to reduce the manual review time for more than 200 multi-hour recordings by about 80%.
AWS has released an agentic video intelligence solution based on the Strands Agents SDK, in which a single AI agent orchestrates Amazon Bedrock, Amazon Rekognition, and Amazon Transcribe at runtime, allowing users to query video content by asking questions in natural language. Responses for already-analyzed content are returned within 1 second, while the first analysis of a new video takes 5–10 minutes; one media and entertainment company used it to reduce the manual review time for more than 20
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