Michael is the Global Head of AI in the Group Digital team of Prudential plc. He joined Prudential from Silicon Valley based Pivotal Labs where he led the Data Science team. His experience lies in the application of artificial intelligence methods to large-scale, multi-structured data sets, in particular neural network based deep learning techniques. Michael previously founded and sold a'Silicon Roundabout' based startup and prior to that was a partner at a major consulting firm. Michael holds a PhD in theoretical physics from the University of Cambridge and is a Fellow of the Royal Statistical Society.

You might have heard about those ATMs that use facial recognition instead of cards and PIN numbers for authentication. You might also have seen on the news a smart security algorithm that helps police identify suspects and cracks criminal cases. Artificial intelligence (AI), the wiz behind these advanced technologies, is permeating our daily lives--everything from financial services to public safety to healthcare and transportation. YITU Technology, one of China's front-running AI startups, has developed solutions that help solve real-world problems. YITU now has the ability to enable accurate facial recognition with a large database of over 1 billion faces in just one second, and their technology has in fact assisted Chinese law enforcement in criminal investigations.

Al Martin: Hi folks, this is Al Martin from Making Data Simple, the series, if you will. Today I have Jean-Francois Puget. Jean-Francois Puget: Yes, you did great. You passed your French test. Al Martin: All right, good, I'm going to give you the [name] JFP from now on, is that all right? So JFP is the distinguished engineer for machine learning and optimization, that's the topic today and we're going to go into that. I also have with me [Steve Moore], who is a senior content designer and storage strategist. Al Martin: So Steve wanted to join the conversation, ask a few questions. So he'll ask the intelligent questions, I will ask the normal, blockhead questions, if you will. So, thank you for being here. We've done a lot, well we've done at least, I think two podcasts on machine learning. We've done one on machine 1.15 learning for dummies, one for IBM machine learning, how to [help], if you haven't heard those, go back, so we can't do enough, and I notice that on your title JFP is machine learning and optimization.

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Martin Welker is the chief executive of Axonic. Even with the support of AI frameworks like TensorFlow or OpenAI, artificial intelligence still requires deep knowledge and understanding compared to a mainstream web developer. If you have built a working prototype, you are probably the smartest guy in the room. Congratulations, you are a member of a very exclusive club. With Kaggle, you can even earn decent money by solving real-world projects. All in all, it is an excellent position to be in, but is it enough to build a business?

For a field that was not well known outside of academia a decade ago, artificial intelligence has grown dizzyingly fast. Tech companies from Silicon Valley to Beijing are betting everything on it, venture capitalists are pouring billions into research and development, and start-ups are being created on what seems like a daily basis. If our era is the next Industrial Revolution, as many claim, A.I. is surely one of its driving forces. It is an especially exciting time for a researcher like me. When I was a graduate student in computer science in the early 2000s, computers were barely able to detect sharp edges in photographs, let alone recognize something as loosely defined as a human face. But thanks to the growth of big data, advances in algorithms like neural networks and an abundance of powerful computer hardware, something momentous has occurred: A.I. has gone from an academic niche to the leading differentiator in a wide range of industries, including manufacturing, health care, transportation and retail.

On this week's If Then, Slate's April Glaser and Will Oremus try to make sense of Twitter CEO Jack Dorsey's rare honest assessment of his company's shortfalls, and what new state regulations mean for self-driving cars and trucks. Cody Wilson, the man behind the first 3-D–printed gun, joins the hosts to talk about his vision of a "WikiLeaks for guns" and why he thinks gun control is no longer possible. And as always, Don't Close My Tabs: This week Will looks at the "deepfakes" video phenomenon and April discusses former Trump aide Sam Nunberg's email inbox exhaustion.

Artificial intelligence is a hot topic right now--but whether or not it is going live up to what some are calling the new healthcare reform is still up for discussion. Mayo Clinic Chief Information officer Christopher Ross and Pricewaterhousecooper Managing Director James Golden, tackled questions about the future of AI at HIMSS18.

On today's episode of "The Interview" with The Next Platform, we focus on how geographic information systems (GIS) is, as a field, being revolutionized by deep learning. This stands to reason given the large volumes of satellite image data and robust deep learning frameworks that excel at image classification and analysis–a volume issue that has been compounded by more satellites with ever-higher resolution output. Unlike other areas of large-scale scientific data analysis that have traditionally relied on massive supercomputers, our audio interview (player below) reveals that a great deal of GIS analysis can be done on smaller systems. However, with the addition of deep learning, the field could be investing in more GPU systems for training and still others for inference at scale. Using lower end TitanX GPUs from Nvidia, the team, which includes Sudeep Sarkar and Mauricio Pamplona Segunda that created a CNN approach to GIS land classification described here, it was shown that deep learning can be a successful tool in the box of GIS analysts.

Professor Brian Cox, BBC presenter and the Royal Society Professor for Public Engagement in Science, joins Eric Schmidt, former Executive Chairman of Google's parent company Alphabet Inc., for a discussion on Artificial Intelligence. Artificial Intelligence is having a remarkable impact on science, technology and people's lives, so how does it help us now and what might it mean for our imminent futures? With the help of the audience at the Science Museum, Brian will be asking Eric Schmidt: what lies ahead for AI?