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OpenAI Blog 10 months ago
OpenAI released GDPval, an evaluation framework that assesses how well its models perform on economically valuable tasks across different job categories. The framework covers 44 occupations and measures model performance on work that generates measurable economic value. This enables more targeted identification of which sectors and roles could see productivity gains from AI deployment.
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2 August 2026
NVIDIA's release of Molt, a reinforcement learning framework built on PyTorch, marks a significant simplification in how frontier labs train agentic AI systems. At 8.6K lines of code—seven times leaner than competing frameworks like VERL—Molt composes existing tools (Ray, vLLM, AutoModel) without forking them, letting researchers iterate rapidly on RL algorithms while maintaining correctness guarantees around token identity and policy versioning. The framework requires modest hardware by frontier standards: two nodes with eight H100 GPUs each, split evenly between training and rollout. This accessibility matters because RL remains the bottleneck for scaling AI agents beyond supervised learning, and simpler codebases reduce the engineering burden on well-funded startups and enterprise research groups.
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