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Showing posts with the label infrastructure planning

Google's Acquisition of Intersect Signals Shift in Datacenter Automation and Capacity Planning

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Google’s parent Alphabet agreed to buy Intersect to speed the buildout of co-located power generation and data-center campuses for AI workloads. The deal signals a shift from buying electricity to engineering energy supply, enabling tighter capacity planning, faster deployment, and more automated power-and-load management across future Google data centers globally. Note: This post is informational only and not legal, procurement, or investment advice. Deal timelines, product plans, and policies can change as regulatory and operational steps progress. TL;DR Alphabet announced a definitive agreement to acquire Intersect for $4.75B in cash (plus assumption of debt) to accelerate data center and power-generation capacity coming online. Intersect is positioned as a “data center and energy infrastructure” specialist, including co-located power and campus-style builds that pair load with dedicated generation. The deal highlights a broader shift: capacity ...

How AI Streamlines Clean Energy Transitions Through Smarter Automation and Workflows

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Artificial intelligence (AI) is playing an important role in managing the complex workflows involved in transitioning to clean energy. By automating and optimizing various processes, AI supports more informed decision-making in power grids, infrastructure planning, and material development. TL;DR The article reports that AI helps balance renewable energy supply and demand by processing data and automating grid management. AI-driven workflow automation aids infrastructure investment planning by simulating scenarios to identify effective projects. Researchers use AI to accelerate the discovery of new energy materials through automated data analysis and virtual testing. AI in Power Grid Management Operating power grids involves coordinating energy supply and demand, especially with renewable sources like wind and solar. AI systems analyze large datasets from sensors and weather forecasts to predict energy patterns. This enables dynamic adjustments to...