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Microsoft and Hugging Face have open-sourced the ThinkingBox framework: using the database’s final state as a deterministic reward signal to advance post-training reinforcement learning for agents.
Microsoft and Hugging Face have jointly launched the open-source framework ThinkingBox, which generates binary 0/1 rewards by comparing the LLM agent’s final database state after execution with the expected state, for reinforcement learning-based fine-tuning. The accompanying benchmark, ThinkingBox-Bench, includes 507 real-world backend tasks, none of which were used during training. After 50 steps of GRPO fine-tuning, Qwen3.8-27B achieved a 9.08-percentage-point improvement in pass@1 on the held-out test set, with Observed 20/20 nearly tripling; however, pass@20 declined in some domains, reflecting a trade-off between breadth and stability.
ClickHouse Workload for Microsoft Fabric: sub-second analytics on OneLake, now in public preview
ClickHouse Workload for Microsoft Fabric brings sub-second analytics to OneLake data through a native Fabric workload, with dedicated ClickHouse Cloud compute for agents, dashboards, and applications.