DSPy: A Framework for Programming with LLMs

Read how the author showcases how DSPy revolutionizes LLM programming by offering a declarative Python framework with automated prompt optimization and adaptable pipeline compilation, contrasting manual prompting approaches and enhancing efficiency and precision in LLM interactions. DSPy’s modular design streamlines LLM application development, reducing manual effort and ensuring prompt coherence, setting it apart from traditional frameworks like LangChain and general-purpose ones like PyTorch.

Winning The Customer Experience (Cx) Battle In Life Sciences: The Role Of AI Automation With MLOps As The Key Enabler

This whitepaper provides Life Sciences leaders with critical insights on transforming Customer Experience (CX) through Machine Learning Operations (MLOps).

Industry : Life Sciences

Data Observability

Data Observability enables real-time monitoring and understanding of a data system’s behavior and performance, looking at aggregated metrics and insights about the data system and its processes to identify issues, patterns, trends, and causes to eliminate or quickly resolve malfunction.

Connected Intelligence – Supply Chain: A Force Multiplier

The author of this paper defines the fundamentals of a connected supply chain and the challenges for adoption and implementation. He goes on to illustrate the objectives and approaches to deploying a connected intelligence framework and generating business value. The author also advocates the integration of AI-powered platforms for streamlining functions within the supply chain and optimizing operations.