This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more. Download NetSuite’s popular KPI Checklist, designed to give you consistently excellent performance - absolutely free, at NetSuite.com/EYEONAI. On episode #133 of the Eye on AI podcast, Craig Smith sits down with Michael Jordan. A revered scientist and distinguished professor at the University of California, Berkeley, Michael’s expertise spans machine learning, statistics, and artificial intelligence. In this episode we explore the intricate landscape of deep learning, its statistical bedrock, and the myriad applications of machine learning methods. We dig deeper into the cloud computing revolution, ignited by deep learning, which has empowered behemoths like Amazon to streamline their logistics and commerce data. The dialogue continues as we uncover the trends in deep learning, its role in the grand scheme of AI, and the persisting challenges in the domain. We conclude by contemplating the repercussions of AI and optimization in complex systems. We examine its historical roots in the mid-20th century, its potential to replace jobs, and its application in various sectors such as financial markets, healthcare, and education. (00:00) Preview (01:00) Introduction (01:36) NetSuite by Oracle (03:53) Deep Learning Advancements in AI (12:56) AI Optimization in Complex Systems (28:53) Future of Machine Learning in Healthcare (39:45) Privacy and Value in Multi-Agent Learning (54:48) Learning Systems, Avatars, and Music Business (1:02:20) Single Source of Truth for Business Owners (1:04:28) NetSuite by Oracle Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

Michael Jordan, a leading Professor at UC Berkeley, dives into the future of AI and its planetary-scale potential. He discusses the integration of machine learning, computer science, and economics to tackle complex challenges. The conversation highlights the issues of uncertainty in AI, the importance of collective intelligence in decision-making, and how reliable data can enhance predictive accuracy. Jordan emphasizes the need for responsible technology that positively impacts society, balancing innovation with the necessity for authentic human creativity.