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Discover how to take retrieval-augmented generation (RAG) and search to the next level with Mixedbread’s latest open-source release: mxbai-rerank-v2. In this session from the "Learning Together" Series, Mixedbread CEO Aamir will present key insights into these next-generation reranking models, which are purpose built for high performance across diverse retrieval tasks. What you’ll learn: • How mxbai-rerank-v2 achieves benchmark-leading results using reinforcement learning • Practical steps for integrating these models into your own RAG or search systems • Performance insights across multilingual text, code, and tool retrieval scenarios • How improved retrieval quality simplifies enterprise AI workflows Register to receive the recording!

Boosting RAG and Search

Boosting RAG and Search

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Jonah Wu

Global Sales & Technical Strategist | Doctorate in Business Administration | 20+ Layer HDI & High-Speed PCB Expert | Quick-Turn Specialist | India, EU & US Focus | Sales Lead @ Glocom

3d

Innovation thrives where tradition falters; learn, adapt, and excel.

Vanessa Riley

CEO & Founder, KhonsuAI | CIO, IDNPSA | Family Nurse Practitioner | Transforming Healthcare Through AI Innovation & Clinical Leadership

1w

This sounds like a fantastic session. Reranking is such a critical piece for improving relevance and precision in RAG and search pipelines, especially as use cases grow more complex and multilingual. I am especially interested in how Mixedbread’s reinforcement learning approach drives better performance across diverse retrieval tasks and how that translates into simpler enterprise workflows. Looking forward to learning more about practical integration steps and real-world benchmarks. Thanks for sharing this opportunity! #AI #MachineLearning #RAG #SearchTechnology #KhonsuAI

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