Modern WisdomArtificial Intelligence, Big Data & China | Martin Schmalz | Modern Wisdom Podcast 144
Episode Details
EPISODE INFO
- Released
- February 20, 2020
- Duration
- 1h 9m
- Channel
- Modern Wisdom
- Watch on YouTube
- ▶ Open ↗
EPISODE DESCRIPTION
Martin Schmalz is a professor of Finance at Oxford University and an author. We're receiving constant warnings about the advent of Artificial Intelligence. And big data. And China. But how do all of these fit together? Expect to learn why your phone's GPS data on a night time is affecting your credit score, how the speed which you complete an online form in could change the price, where the REAL computing power behind AI is being deployed at the moment, and much more. Extra Stuff: Follow Martin on Twitter - https://twitter.com/martincschmalz Buy The Business Of Big Data - https://amzn.to/2HHg2Li Thank you to The Browser - https://thebrowser.com/ Take a break from alcohol and upgrade your life - https://6monthssober.com/podcast Check out everything I recommend from books to products - https://www.amazon.co.uk/shop/modernwisdom #bigdata #artificialintelligence #machinelearning - Listen to all episodes online. Search "Modern Wisdom" on any Podcast App or click here: iTunes: https://apple.co/2MNqIgw Spotify: https://spoti.fi/2LSimPn Stitcher: https://www.stitcher.com/podcast/modern-wisdom - Get in touch in the comments below or head to... Instagram: https://www.instagram.com/chriswillx Twitter: https://www.twitter.com/chriswillx Email: modernwisdompodcast@gmail.com
SPEAKERS
Martin Schmalz
guestNarrator
otherChris Williamson
host
EPISODE SUMMARY
In this episode of Modern Wisdom, featuring Martin Schmalz and Narrator, Artificial Intelligence, Big Data & China | Martin Schmalz | Modern Wisdom Podcast 144 explores how Big Data And AI Quietly Reshape Business, Privacy, And Power Finance professor Martin Schmalz explains that most real-world AI is not science fiction but industrial-scale prediction: using huge datasets to forecast behavior, risk, and demand far better and cheaper than humans. He argues the real disruption comes from combining machine-learning prediction with economic thinking to redesign business models, industries, and jobs, with China currently several years ahead because of scale, super-apps, and weaker privacy constraints.
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