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A New Framework for Open Source AI
Mozilla and partners published a paper proposing a layered, gradient openness framework for foundation models, defining openness for data, code, weights, docs, and deployment. The framework gives developers, regulators, and civil society a common language to evaluate openness and safety beyond a binary label.
Mozilla Automation Teammozilla.org3 minArticle: Your Next DSL Author Is a Language Model
Typed Domain Grounding (TDG) embeds a DSL inside a mainstream language the LLM already knows (e.g., Kotlin) and uses the host compiler as an oracle. The author describes five building blocks—embedding, choosing a host language with high training‑data frequency, compiler‑driven type safety, a generate‑compile‑repair loop, and an on‑demand teaching tool—and shows measured results from kUML, a Kotli…
InfoQinfoq.com18 minHints for Computer System Design
Lampson’s 1983 essay distills practical design hints for computer systems, emphasizing simple, well‑defined interfaces, predictable costs, and separating common‑case from worst‑case paths. The advice, illustrated with examples from Alto, Dorado, and early OSes, remains relevant for modern system architects.
Hall of Famemicrosoft.com62 minpaperArticle: Beyond Relevance: A Governance-First Architecture for Enterprise Personalization
The article proposes a governance‑first architecture for enterprise personalization, where policy‑driven steps (memory, journey graph, AI routing, scoring, trust checks, outcome simulation) shape the recommendation before it is returned. A reference FastAPI implementation demonstrates the pattern with external YAML policies and optional LLM assistance.
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