Microsoft Research has released Orchard, an open-source framework designed to enable scalable and cost-effective research into autonomous agents. The system centers on Orchard Env, a Kubernetes-based environment service that allows researchers to train and evaluate agents across diverse domains like software engineering, web navigation, and personal assistance without rebuilding infrastructure.
Microsoft Research has released Echoverse, a collection of twelve deep synthetic environments designed to train computer-use agents. The initiative includes ten domain-specific worlds and two capability-focused worlds, all built to maintain coherent state and behavioral fidelity.
Microsoft Research has introduced EvoLib, a framework that enables large language models to learn from their own experience during inference without requiring ground-truth labels or external feedback. Rather than storing raw experiences as static memories, EvoLib transforms them into reusable skills and reflective insights that are continually refined, consolidated, and reweighted.
Microsoft has open-sourced a branch of its SymCrypt cryptographic library containing formal specifications and proofs for the Rust implementations of ML-KEM and SHA-3. This release demonstrates a methodology where production algorithms are written in safe Rust and verified against standards-derived Lean models using the Aeneas toolchain.