The Analytics Edge The Impact of Generative AI on Business with Amit Prakash, Co-Founder and CTO at ThoughtSpot
This episode features an interview with Amit Prakash, Co-Founder and CTO at ThoughtSpot, a market leading business intelligence platform that helps anyone explore, analyze, and share real time business analytics and data easily with AI powered analytics.
Amit has deep experience in building large-scale analytics systems. Prior to ThoughtSpot, Amit led multiple analytics engineering teams in the Google AdSense businesses, contributing $50M+ quarter-on-quarter growth to the business by improving analytical algorithms for AdSense. Previously, Amit was a founding engineer in the Bing team at Microsoft, where he implemented the pagerank algorithms for search from scratch. Amit received his PhD in Computer Engineering from the University of Texas at Austin and a Bachelor of Technology in Electrical Engineering from the Indian Institute of Technology, Kanpur.
In this episode, Amit talks about his journey in helping create ThoughtSpot, how data leaders should specifically be thinking about large language models, and the impact generative AI will have on business.
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Key Quotes
“The trick is to capture the mental model of the end user so that you know what they're already anticipating. If they're already anticipating an increase during Christmas season, you can see that from the previous trend. If they're already anticipating the amount of revenue they produce from a particular state to be proportional to the number of stores in that state, can you capture that and then that way you can de-noise these insights and meaningful insights surface a lot more. And that requires a two-way conversation between the algorithm and the end user. And these are the kinds of things that you can do with LLM that wasn't possible before.” - Amit Prakash
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Episode Timestamps
(02:29) How data leaders should be thinking about LLMs and generative AI
(06:46) Amit’s career journey and helping create ThoughtSpot
(15:06) Considerations around building a trustworthy AI system
(18:39) Unpacking large language models
(29:57) Institutional knowledge for good data reasoning and intelligence
(34:45) Modern data stack and data warehousing
(37:25) Moving towards generative AI and the impact it will have on business
(41:35) ThoughtSpot Generative AI Meetup
(43:57) Hosts’ after-thoughts
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Links