Contextual Machine Learning
Mutar explores how machine learning models can adapt to context, enhancing binary classifiers by incorporating additional data such as logos and user history. She discusses the challenges of real-time streaming of harmful content and how smaller models on edge devices can address these issues. Additionally, she highlights the importance of proprietary data in building defensible commercial AI systems, sharing insights on her development process using various technologies.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
683: Contextual A.I. for Adapting to Adversaries — with Dr. Matar Haller
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