The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) Building an Autonomous Knowledge Graph with Mike Tung - #319
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Nov 21, 2019 
Mike Tung, Founder and CEO of Diffbot, dives into the unique world of autonomous knowledge graphs. He explains how Diffbot's approach differs from traditional search engines like Google and Bing. The conversation highlights the importance of structured data in AI, challenges of knowledge fusion, and the developer experience with tools like Extraction API and Crawlbot. Tung also discusses their dual role in research and commercial viability, offering insights into their subscription model for accessing the knowledge graph.
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Diverse Career Path
- Mike Tung held various jobs, including software engineer at Microsoft, eBay, and Yahoo, and founder of startups acquired by Cisco and Facebook.
- While pursuing AI research, he also worked as a patent attorney to fund his ventures.
The Importance of Data in AI
- Improving AI depends on hardware, software/algorithms, and data, with data being a key driver.
- Diffbot aims to create a comprehensive, machine-readable map of human knowledge from the web, like an ImageNet for language.
Diffbot's Knowledge Graph vs. Google's
- Google's Knowledge Graph originated from Wikipedia and curated data, making it limited in scope.
- Diffbot's Knowledge Graph, autonomously built, is larger, includes everyday entities, and is commercially available.