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The InfoQ Podcast
Susan Shu Chang on Bridging Foundational Machine Learning and Generative AI
Jan 6, 2025
Susan Shu Chang, Principal Data Scientist at Elastic, delves into the synergy between foundational machine learning and generative AI. She emphasizes the critical role of collaboration between machine learning practitioners and software engineers to ensure effective model deployment. Chang discusses the challenges of harnessing large language models for summarizing log data and explores practical tools for developing generative AI applications. Additionally, she shares strategies for navigating machine learning job interviews, highlighting the importance of a well-rounded skill set.
30:48
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Quick takeaways
- The significance of foundational machine learning techniques remains critical in real-world applications, despite the growing prominence of generative AI.
- Effective deployment of machine learning models necessitates understanding user interface integration and the importance of relevant skill preparation for job candidates.
Deep dives
Foundational Insights in Machine Learning
The discussion highlights the significance of foundational machine learning techniques that remain highly relevant in the current landscape, despite the rising hype around generative AI. Personalized recommendations on platforms like YouTube, Spotify, and Netflix are examples of how traditional machine learning, such as recommender systems and reinforcement learning, fundamentally drives user experiences. The track emphasized the challenges of deploying machine learning models in production, emphasizing that having a robust algorithm is not enough if it cannot be integrated effectively to deliver value to users. This serves to remind software engineers about the importance of pragmatism in applying machine learning techniques to real-world applications.
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Discover
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