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Model Openness Framework: The Path to Openness, Transparency and Collaboration in Machine Learning Models

Offered By: CNCF [Cloud Native Computing Foundation] via YouTube

Tags

Generative AI Courses Machine Learning Courses Open Science Courses Open Data Courses Model Development Courses Open Source Courses

Course Description

Overview

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Explore the Model Openness Framework (MOF) in this insightful conference talk by Matt White from The Linux Foundation and Anni Lai from Futurewei. Delve into the challenges of transparency, reproducibility, and safety in Generative AI (GAI) commercialization. Learn about the MOF's ranked classification system for evaluating machine learning models based on completeness and openness. Discover how this framework addresses concerns about misrepresentation of open models and guides researchers in providing model components under permissive licenses. Gain insights into the Model Openness Tool demonstration and understand the benefits of MOF for both model producers and consumers. Examine how widespread adoption of MOF can foster a more open AI ecosystem, benefiting research, innovation, and the adoption of state-of-the-art models.

Syllabus

Model Openness Framework: The Path to Openness, Transparency and Collabor... - Matt White & Anni Lai


Taught by

CNCF [Cloud Native Computing Foundation]

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