Sponsored Content
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AI at the Edge – Fulfilling the Promise
The ability to deliver inference anywhere is essential for successfully using AI across the organization. A recent Evans Data study found 1.4X more inference demand is projected outside data centers vs. in. As a result, AI strategies based on a hybrid (cloud and edge) infrastructure strategy will be the preferred approach.
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ThoughtSpot evolving as BI becomes driven by AI
Recent releases, including the Agentic Analytics Platform and Agentic Semantic Layer, demonstrate that the vendor continues to be...
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Latest Databricks tools use AI to simplify AI development
Fueled by user feedback, the vendor's newest features include a framework that automates building agents and a no-code interface ...
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U.S. senators offer perspectives on U.S. energy policy
Nuclear energy dominates the discussion among lawmakers and the tech industry as a top potential power source for AI data centers...
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Big tech, UAE make U.S. energy investments to support AI
The Trump administration has pointed to key partnerships, including with the United Arab Emirates and U.S. tech companies, to ...
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As Ocient matures, vendor names new CEO to drive growth
As the vendor moves from its startup to growth phase, John Morris, who has significant experience leading companies as they ...
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EnterpriseDB targets AI development with latest update
A low-code/no-code interface and data observability across hybrid environments address the challenges enterprises face moving AI ...
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7 challenges, best practices for ERP data migration
Resource constraints, poor data quality and system compatibility issues can complicate ERP data migration, but following best ...
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8 use cases for generative AI in manufacturing
Generative AI can potentially help manufacturers improve daily operations and increase efficiency, among other use cases. Learn ...