AI & ML in Practice: Toy vs Enterprise Use Cases
AI & ML in Practice: Toy vs Enterprise Use Cases
Brazos F
Baruch Sadogursky
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Principal Developer Productivity Engineering Advocate, Gradle
Ran Romano | VP of Product & Engineering, JFrog ML
Damian Curry | Community and Alliances Technical Director - NGINX
Melissa McKay | Head of Developer Relations, JFrog
Brian A. Randell | Staff Developer Advocate, GitHub
Tue 03:50PM - 04:30PM, September 10th
Ran Romano | VP of Product & Engineering, JFrog ML
Damian Curry | Community and Alliances Technical Director - NGINX
Melissa McKay | Head of Developer Relations, JFrog
Brian A. Randell | Staff Developer Advocate, GitHub
Artificial Intelligence and Machine Learning are current buzzwords, and organizations are jumping at the chance to cash in on new opportunities afforded by new developments in this space. Gartner estimates 90% of NEW apps will contain AI by 2027. But what exactly are we developing? How do we actively integrate AI and ML technologies in ways that are beneficial to developers, our organizations, and our customers? What kinds of applications have an ROI that makes sense and what proof of concepts turn out to be toys that never make it to production? Join this expert panel discussion about relevant use cases to pursue and perhaps some to avoid or that may require more thought before implementation.