Uploaded August 2023 | Updated September 2026, 2 days ago
Today, I had the pleasure of interviewing Vin Vashishta. Vin is the author of the Wiley book, βFrom Data To Profit.β Itβs the playbook for monetizing data and AI. Vin is the Founder of V-Squared and built the business from client 1 to one of the worldβs oldest data and AI consulting firms. His background combines over 25 years in strategy, leadership, software engineering, and applied machine learning. In this episode, Vin gives his take on the AI hype, what makes us uniquely human, and how companies can with with strategic changes around new large language models. This is a great conversation that can benefit data leaders and data scientists alike. Enjoy!
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Vin's Links:
https://www.datascience.vin/
Vin's Book: amzn.to/3OZDXbl
Listen to Ken's Nearest Neighbors on all the main podcast platforms!
On Apple Podcasts: podcasts.apple.com/us/podcast/kens-nearest-neighbors/id1538368692 (Please rate if you enjoy it!)
On Spotify: open.spotify.com/show/7fJsuxiZl4TS1hqPUmDFbl
On Google: podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5idXp6c3Byb3V0LmNvbS8xNDMwMDQxLnJzcw?sa=X&ved=0CAMQ4aUDahcKEwjQ2bGBhfbsAhUAAAAAHQAAAAAQAQ
MORE DATA SCIENCE CONTENT HERE:
π€My Twitter - twitter.com/KenJee_DS
π LinkedIn - linkedin.com/in/kenjee
π Kaggle - kaggle.com/kenjee
π Medium Articles - medium.com/@kenneth.b.jee
π» Github - github.com/PlayingNumbers
π My Sports Blog - playingnumbers.com
π£οΈ 66DaysOfData Discord Server - discord.com/invite/4p37sy5muZ
Today, I had the pleasure of interviewing Vin Vashishta. Vin is the author of the Wiley book, βFrom Data To Profit.β Itβs the playbook for monetizing data and AI. Vin is the Founder of V-Squared and built the business from client 1 to one of the worldβs oldest data and AI consulting firms. His background combines over 25 years in strategy, leadership, software engineering, and applied machine learning. In this episode, Vin gives his take on the AI hype, what makes us uniquely human, and how companies can with with strategic changes around new large language models. This is a great conversation that can benefit data leaders and data scientists alike. Enjoy!
Podcast Sponsors, Affiliates, and Partners:
- Pathrise - pathrise.com/KenJee | Career mentorship for job applicants (Free till you land a job)
- Taro - jointaro.com/r/kenj308 (20% discount) | Career mentorship if you already have a job
- 365 Data Science (57% discount) - 365datascience.pxf.io/P0jbBY | Learn data science today
- Interview Query (10% discount) - interviewquery.com/?ref=kenjee | Interview prep questions
Vin's Links:
https://www.datascience.vin/
Vin's Book: amzn.to/3OZDXbl
Listen to Ken's Nearest Neighbors on all the main podcast platforms!
On Apple Podcasts: podcasts.apple.com/us/podcast/kens-nearest-neighbors/id1538368692 (Please rate if you enjoy it!)
On Spotify: open.spotify.com/show/7fJsuxiZl4TS1hqPUmDFbl
On Google: podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5idXp6c3Byb3V0LmNvbS8xNDMwMDQxLnJzcw?sa=X&ved=0CAMQ4aUDahcKEwjQ2bGBhfbsAhUAAAAAHQAAAAAQAQ
MORE DATA SCIENCE CONTENT HERE:
π€My Twitter - twitter.com/KenJee_DS
π LinkedIn - linkedin.com/in/kenjee
π Kaggle - kaggle.com/kenjee
π Medium Articles - medium.com/@kenneth.b.jee
π» Github - github.com/PlayingNumbers
π My Sports Blog - playingnumbers.com
π£οΈ 66DaysOfData Discord Server - discord.com/invite/4p37sy5muZ










