875: How Semiconductors Are Made (And Fuel the AI Boom), with Kai Beckmann

Why are semiconductors so essential in this digital age, and how are they made? Jon Krohn speaks to electronics CEO Kai Beckmann about Merck KGaA, Darmstadt, Germany’s intricate manufacturing process, how we can use AI to develop materials that power next-gen AI technologies, and how a chip with the processing power of the human brain might one day be able to run on the power of a low-watt light bulb. Additional materials: www.superdatascience.com/875 This episode is brought to you by the Dell AI Factory with NVIDIA. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (06:26) How Merck KGaA, Darmstadt, Germany supports groundbreaking developments in AI  (13:42) Material science’s biggest challenges for AI  (29:55) What heterogeneous integration is (34:37) How optical tech influences the electronics industry  (49:04) Navigating upturns and downturns in the semiconductor industry  (53:08) How AI regulations benefit humanity

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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.