GAO: DOE Failing to Apply Key Lessons in Nuclear Waste Cleanup Efforts

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The U.S. Government Accountability Office (GAO) has released a report criticizing the Department of Energy (DOE) for missing opportunities to improve its nuclear waste cleanup programs. The report finds that the DOE is not consistently applying lessons learned from past cleanup experiences across its various sites. This gap in knowledge-sharing and practice is seen as a significant oversight in managing one of the country's most complex environmental challenges. The findings suggest that better integration of past lessons could improve both the efficiency and effectiveness of ongoing cleanup operations.

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OpenAI harness fix, EU AI gigafactories, and Cognition's SWE-1.7: AI roundup Aug 1, 2026

OpenAI revealed on July 29 that GPT-5.6 Sol's poor ARC-AGI-3 benchmark score of 7.8% was caused by a flawed evaluation harness that discarded reasoning between moves, not by the model itself. Enabling retained reasoning and context compaction in the Responses API lifted Sol's score from 13.3% to 38.3% and allowed it to clear all six benchmark levels, a feat no frontier model achieves on the official leaderboard. The finding highlights that benchmark results reflect the combined effect of model, harness, and settings rather than model capability alone. Meanwhile, the European Commission launched a formal tender on July 30 to build up to seven AI gigafactories across the EU, backed by up to €10 billion in public funding and a €30 billion total target including private investment, with awards expected in early 2027. Separately, AI coding lab Cognition released SWE-1.7 in July, a new frontier coding model built on a Kimi K2.7 base and trained via reinforcement learning, featuring innovations in sampling stability, multi-continent training, and extended task horizons.

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ProgrammingDEV Community ·

AI Agent Safety Belongs in the Environment, Not the Agent's Own Judgment

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ProgrammingDEV Community ·

CS Student Launches Technical Writing Series on AI, Python, and NLP

A computer science student and aspiring technical writer has introduced herself to the Dev.to community while sharing her ongoing work in technical content creation. She has published a deep-dive guide on Natural Language Processing on her Hashnode blog, covering text preprocessing pipelines and practical Python examples using the spaCy library. The article aims to explain how computers interpret and understand human language. She is seeking constructive feedback from developers and writers to improve the clarity of her technical explanations. The author plans to continue publishing in-depth articles covering AI, Python, and broader software concepts.

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ProgrammingDEV Community ·

Kubernetes Hiring Is Flawed When Trivia Tests Replace Real Engineering Judgment

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