The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) Live from TWIMLcon! Encoding Company Culture in Applied AI Systems - #305
Oct 4, 2019
Deepak Agarwal, VP of Engineering at LinkedIn, dives into the synergy between company culture and applied AI systems. He explains how standardizing processes boosts productivity and ML ROI. The conversation highlights the Pro-ML initiative, which focuses on scaling machine learning systems by aligning tools with innovation. Agarwal also emphasizes the importance of a strong business case for tech transitions and the significance of thoughtful experimentation in driving meaningful insights within a centralized AI organization.
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ML at LinkedIn
- Machine learning is deeply ingrained in LinkedIn's operations, influencing everything from connections to content recommendations.
- It's crucial for scaling processes like feed optimization, advertising, job recommendations, and platform safety.
Early ML at LinkedIn
- LinkedIn, a data-first company, pioneered people recommendations using machine learning as early as 2007.
- Initially, simpler models and offline Hadoop systems were used due to scaling challenges.
Pro-ML Platform
- LinkedIn's Pro-ML platform prioritizes large-scale applications, focusing on maximizing ROI from key areas like recommendations and search.
- It acknowledges the need for increased sophistication to achieve significant returns.