843: Safe, Fast and Efficient AI, with Protopia’s Dr. Eiman Ebrahimi

What’s holding your AI projects back from success? Dr. Eiman Ebrahimi, CEO of Protopia AI and former NVIDIA scientist, takes us on a fascinating journey through the challenges of AI data security and enterprise scalability. Learn how to escape "proof of concept purgatory," unlock profitable AI solutions, and tackle the trade-offs between cost, speed, and security. Plus, discover how the philosophy of Alan Watts can inspire innovation and drive meaningful change in the world of AI. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (02:53) Protopia’s role in AI data security and privacy (11:45) The functionality behind Stained Glass Transform (22:20) Eiman’s journey from NVIDIA to founding Protopia (25:37) Challenges enterprises face with ROI on AI projects (36:40) Multi-tenancy in AI systems (55:37) Stained Glass Transform’s privacy-preserving capabilities (01:09:31) Emerging trends in AI (01:14:55) Alan Watts’ philosophies and their link to entrepreneurship Additional materials: www.superdatascience.com/843

Om Podcasten

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact. Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.