851: Quantum ML: Real-World Applications Today, with Dr. Florian Neukart

Are our passwords safe, even with the increasing accessibility of quantum computing? Florian Neukart, Chief Product Officer at Terra Quantum AG, thinks so. In this episode, he outlines the three key elements of quantum-safe security. He speaks to Jon Krohn about the resourceful applications of quantum computing and workarounds for the demands of quantum computing on operational times and cooling systems. And if you’re interested in making the switch to quantum computing from machine learning, he also explores what you need (and don’t need) to make change happen. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (17:12) The real-world applications of quantum computing (23:35) The chips needed for quantum computing  (31:18) How quantum computing meets key business challenges (46:33) The ethical challenges of quantum technology (49:28) How to become proficient in quantum computing  (1:01:21) The future of quantum computing Additional materials: www.superdatascience.com/851

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.