Sarah Luger

Co-Chair, Data Sets Working Group

MLCommons

Sarah Luger host of the AI Artifacts podcast (www.aiartifacts.net) and the Co-Chair of the Data Sets Working Group for AI benchmarking organization, MLCommons. Data Sets Working Group continues the research initiated with the Rigorous Evaluation of AI Systems workshop series at AAAI Human Computation and AAAI conferences. The goal is to develop robust schemas and infrastructure supporting the Open Source hosting of benchmark evaluation data sets. The group aims to provide free storage for researchers who have human-generated data (spoken word data is the current focus) of generally high quality.

Sarah is a Contributing Member of the MLCommons AI Safety Stakeholder Engagement, Benchmarks and Tests, and Platform Technology working groups. This nonprofit engineering consortium guides the ML industry by developing benchmarks, public datasets, and best practice.

Her current AI Safety work focuses on building LLM Safety Test Sets, Creating Scoring System, and Running Benchmarks. Sarah is leading the subsequent work automating the translation of safety test prompts into in low-resource languages.

Niamh Gavin

Head of Applied AI

Groq

Hussain Chinoy

Technical Solutions Manager, Applied AI Engineering

Google

Hussain has a background in linguistics and software applications and has been working on building speech and conversational systems for the last 20 years. As a Technical Solutions Manager for Generative AI on the Applied AI Engineering team he focuses on combining Google Cloud services into solutions that accelerate customers usage of AI, including Generative AI for Marketing, Customer Experience, and Website Modernization. His technical areas of interest are in Conversation, Ethics and Governance, and application architecture. Hussain joined Google in 2020 as an application modernization and AI specialist.