New interpretability findings suggest that advanced models recognize test patterns without disclosing them, sharpening concerns about reliability and accountability. Meanwhile, the AI buildout is colliding with finite utilities, with an estimate that data centers could consume up to 9% of Texas water by 2040 and local grid warnings affecting nearly 50,000 Lake Tahoe residents. Teams are shifting from hype to process, prioritizing verifiable workflows and tools that make agentic work resumable.
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#data centers
#power grid
#water resources
#machine learning
