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Avoid the AI-hype trap: 3 simple how-tos

By Janani Ravi

For much of the past decade, famous investors, technology executives and the press have fallen over themselves in a race to participate in the AI/ML Gold Rush. All the while, engineers and practitioners have kept focus on one simple question: Beyond the hype, beyond the negativity, can AI/ML be made to deliver real wins in a typical enterprise?

Join data, ML and AI expert Janani Ravi as she explains why the answer to this question is an astounding yes—provided you keep a few, relatively simple, practical points in mind (and really understand what they mean):

  • Avoid overfitting

  • Handle real-time data correctly

  • Monitor your deployed models

About the author

Janani Ravi has a master's degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework. After spending years working in tech in the Bay Area, New York and Singapore at companies such as Microsoft, Google and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providing high-quality content for technical skill development. Loonycorn is working on developing an engine (patent filed) to automate animations for presentations and educational content.

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