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On this episode of the AI For All Podcast, Manasi Vartak, CEO of Verta, joins Ryan Chacon to discuss AI governance, AI regulation, and AI bias. They talk about generative AI and its risks, reducing AI bias, responsible AI, and how regulation will impact AI adoption. Manasi Vartak is the founder and CEO of Verta, the Menlo Park, California-based provider of the Verta Operational AI platform and Verta Model Catalog. Manasi invented experiment management and tracking while at MIT CSAIL when she created ModelDB, the first open-source model management system deployed at Fortune 500 companies and the progenitor of MLflow. After earning her PhD from MIT, Vartak went on to data science positions at Twitter, where she worked on deep learning for content recommendation as part of the feed-ranking team, and Google, where she worked on dynamic ad-targeting, before founding Verta. Emerging from the AI innovations at MIT, Twitter, NVIDIA, Google, and Facebook, Verta, based in Silicon Valley, specializes in Model Catalog, Model Lifecycle Management, and AI portfolio management. Since its inception in 2018, it has served Fortune 500 companies and digital pioneers, and was recognized as a 'Gartner Cool Vendor AI Core Technologies' in 2022. More about Verta: https://www.verta.ai Connect with Manasi: https://www.linkedin.com/in/manasi-vartak/ Key Questions and Topics from This Episode: (00:00) Intro to the AI For All Podcast (01:13) Intro to Manasi Vartak and Verta (01:44) What is generative AI? (02:52) Current state and future of generative AI (04:05) Generative AI risks (05:32) AI bias (06:54) Reducing AI bias (10:58) What makes generative AI possible? (12:34) AI governance and responsible AI (15:30) Who is responsible for making AI responsible? (18:41) AI regulation (23:52) How will regulation impact AI adoption? (27:51) Will we struggle to govern AI in the future? (28:37) Learn more about Verta Subscribe on YouTube: https://bit.ly/43dYQV9 Join Our Newsletter: https://ai-forall.com Follow Us on Twitter: https://twitter.com/_aiforall