Two-Shot: {Shreya Shankar}{PhD Student, UC Berkeley EECS}

Two-Shot: {Shreya Shankar}{PhD Student, UC Berkeley EECS}

In this episode of Two-Shot, host Julia welcomes Shreya Shankar [https://www.sh-reya.com/], a software engineer and AI researcher pursuing her PhD at UC Berkeley's EECS department. Shreya, known for her work on machine learning infrastructure and LLM evaluation, shares insights from her research on human-centered, AI-powered data processing. From testing frameworks to evaluation metrics, they explore the practical challenges of assessing large language models and discuss innovative solutions for developers working with these systems. This episode offers valuable perspective on the evolving landscape of AI evaluation and deployment, making it essential listening for ML practitioners and technology enthusiasts.

Two-Shot: {John Berryman} {Principal Consultant, Arcturus Labs} {ex-GitHub Copilot}

In the debut episode of Two-Shot, host Julia welcomes John Berryman⁠ [https://www.linkedin.com/in/john-berryman-864b1713/], an AI and search expert, to discuss the intricacies of prompt engineering and the evolution of search technology. John, author of "Relevant Search" [https://www.manning.com/books/relevant-search] and the upcoming "Prompt Engineering for LLMs," [https://www.oreilly.com/library/view/prompt-engineering-for/9781098156145/] shares insights from his work on GitHub Copilot and explores how large language models are reshaping the tech landscape. From the challenges facing developers to the potential of retrieval-augmented generation (RAG), this episode offers a fascinating glimpse into the future of AI and search, making it a must-listen for both seasoned professionals and AI enthusiasts.