Managing Marketing is a weekly podcast hosted by TrinityP3. Each one is a conversation with a marketing thought-leader, professional, practitioner or expert on the issues and topics of interest to marketers and business leaders everywhere. In this special series, TrinityP3's Anton Buchner, discusses the rise of Artificial Intelligence and the impact it is having on marketing. Henry Innis is the Chief Strategy Officer and Founder of Mutiny Group, a team of data scientists, engineers and strategists that help put the rigour and measurability back into marketing. He talks about how cloud computing and advances in deep learning models that sit within a neural network now help marketers to look forward and predict results, rather than viewing data as a retrospective exercise. Welcome to Managing Marketing, a weekly podcast where we sit down and talk with marketing thought leaders and experts on the issues and topics of interest to marketers and business leaders everywhere. To discuss this I'm sitting down today with Henry Innes. Henry is the chief strategy officer and founder of Mutiny. Now before we jump in I know your background a little bit. We met I think first when you were at Edge. It was probably my first advertising job. You've been an angel investor advisor. You've been through a couple of different agencies, VML, YNR. I think you were on the STW High Performers Programme--hotshot--years ago.

Superintelligence: What happens in a world with AI that is hundreds or thousands of times smarter than humans? In this episode, we chat with research scientist Roman Yampolskiy. He's a professor at the University of Louisville, and his most recent book is Artificial Superintelligence: A Futuristic Approach. Subscribe wherever you find podcasts: If you listen to podcasts, here's where you can subscribe to future39 and here more interviews like this on the future. What happens in a world with AI that's hundreds or thousands of times smarter than we are? He's a professor at the University of Louisville, and his most recent book is Artificial Superintelligence: A Futuristic Approach. John Koetsier: Thank you so much for coming on the show. You have an amazing background there, I love it.

Dr. Jianfeng Gao is a veteran computer scientist, an IEEE Fellow and the current head of the Deep Learning Group at Microsoft Research. He and his team are exploring novel approaches to advancing the state-of-the-art on deep learning in areas like NLP, computer vision, multi-modal intelligence and conversational AI. Today, Dr. Gao gives us an overview of the deep learning landscape and talks about his latest work on Multi-task Deep Neural Networks, Unified Language Modeling and vision-language pre-training. He also unpacks the science behind task-oriented dialog systems as well as social chatbots like Microsoft Xiaoice, and gives us some great book recommendations along the way! Jianfeng Gao: Historically, there are two approaches to achieve the goal. One is to use large data. The idea is that if I can collect all the data in the world, then I believe the representation learned from this data is universal. Because I see all of them. The other approach is that, since the goal of this representation is to serve different applications, how about I train the model using application-specific objective functions across many, many different applications? Host: You're listening to the Microsoft Research Podcast, a show that brings you closer to the cutting-edge of technology research and the scientists behind it. Host: Dr. Jianfeng Gao is a veteran computer scientist, an IEEE Fellow and the current head of the Deep Learning Group at Microsoft Research. He and his team are exploring novel approaches to advancing the state-of-the-art on deep learning in areas like NLP, computer vision, multi-modal intelligence and conversational AI. Today, Dr. Gao gives us an overview of the deep learning landscape and talks about his latest work on Multi-task Deep Neural Networks, Unified Language Modeling and vision-language pre-training. He also unpacks the science behind task-oriented dialog systems as well as social chatbots like Microsoft Xiaoice, and gives us some great book recommendations along the way! What gets you up in the morning? Jianfeng Gao: It's like all the world-class research teams, our goal, ultimate goal, is to advance the state-of-the-art and we want to push the AI frontiers by using deep learning technology or developing new deep learning technologies.

Dr. Jianfeng Gao is a veteran computer scientist, an IEEE Fellow and the current head of the Deep Learning Group at Microsoft Research. He and his team are exploring novel approaches to advancing the state-of-the-art on deep learning in areas like NLP, computer vision, multi-modal intelligence and conversational AI. Today, Dr. Gao gives us an overview of the deep learning landscape and talks about his latest work on Multi-task Deep Neural Networks, Unified Language Modeling and vision-language pre-training. He also unpacks the science behind task-oriented dialog systems as well as social chatbots like Microsoft Xiaoice, and gives us some great book recommendations along the way! Jianfeng Gao: Historically, there are two approaches to achieve the goal. One is to use large data. The idea is that if I can collect all the data in the world, then I believe the representation learned from this data is universal. Because I see all of them. The other approach is that, since the goal of this representation is to serve different applications, how about I train the model using application-specific objective functions across many, many different applications? Host: You're listening to the Microsoft Research Podcast, a show that brings you closer to the cutting-edge of technology research and the scientists behind it. Host: Dr. Jianfeng Gao is a veteran computer scientist, an IEEE Fellow and the current head of the Deep Learning Group at Microsoft Research. He and his team are exploring novel approaches to advancing the state-of-the-art on deep learning in areas like NLP, computer vision, multi-modal intelligence and conversational AI. Today, Dr. Gao gives us an overview of the deep learning landscape and talks about his latest work on Multi-task Deep Neural Networks, Unified Language Modeling and vision-language pre-training. He also unpacks the science behind task-oriented dialog systems as well as social chatbots like Microsoft Xiaoice, and gives us some great book recommendations along the way! What gets you up in the morning? Jianfeng Gao: It's like all the world-class research teams, our goal, ultimate goal, is to advance the state-of-the-art and we want to push the AI frontiers by using deep learning technology or developing new deep learning technologies.

'Collective intelligence' is defined as the capacity of human communities to cooperate intellectually in creation, innovation and invention. As our society becomes more and more knowledge-dependent, this collective ability becomes of fundamental importance. It is therefore vital to understand, among other things, how collective intelligence processes can be expanded by digital networks. It is one of the keys to success for modern societies. Pierre Lévy is one of the world's leading thinkers, not only in the vast area of cyberculture, but also in the fundamental field of knowledge and its processes. He was essentially the first to focus research on collective intelligence when it became a determining factor in the competitiveness, creativity and human development of knowledge-based societies. Michael Peters (MP): May I call you'Pierre'? Can you tell us something about your education, especially over the three institutions of your experience as a graduate?

We present Meena, a multi-turn open-domain chatbot trained end-to-end on data mined and filtered from public domain social media conversations. This 2.6B parameter neural network is simply trained to minimize perplexity of the next token. We also propose a human evaluation metric called Sensibleness and Specificity Average (SSA), which captures key elements of a human-like multi-turn conversation. Our experiments show strong correlation between perplexity and SSA. The fact that the best perplexity end-to-end trained Meena scores high on SSA (72% on multi-turn evaluation) suggests that a human-level SSA of 86% is potentially within reach if we can better optimize perplexity. Additionally, the full version of Meena (with a filtering mechanism and tuned decoding) scores 79% SSA, 23% higher in absolute SSA than the existing chatbots we evaluated.

Long before Meg Mitchell founded the Ethical AI team at Google in 2017, she loved Boggle, the classic game where players come up with words from random letters in three minutes or less. Looking back at her childhood Boggle-playing days, Meg sees the game as her early inspiration to pursue studying computational linguistics. "I always loved identifying patterns, solving puzzles, language games, and creating new things," Meg says. "And Boggle had it all. It was a puzzle, and it was creative."

After years in the (mostly Canadian) wilderness followed by seven years of plenty, Deep Learning was officially recognized as the "dominant" AI paradigm and "a critical component of computing," with its three key proponents, Geoffrey Hinton, Yann LeCun, and Yoshua Bengio, receiving the Turing Award in March 2019. Turing Award winners (from left to right) Yoshua Bengio, Yann LeCun, and Geoffrey Hinton at the ... [ ] ReWork Deep Learning Summit, Montreal, October 2017. In October 2012, a deep neural network achieved an error rate of only 16% in the ImageNet Large Scale Visual Recognition Challenge, a significant improvement over the 25% error rate achieved by the best entry the year before. Yann LeCun: "The difference there was so great that a lot of people, you could see a big switch in their head going'clunk.' Now they were convinced;" Geoffrey Hinton: "Until we could produce results that were clearly better than the current state of the art, people were very skeptical;" Yoshua Bengio: "[Anyone hoping to make the next Turing-winning breakthrough in AI] should not follow the trend--which right now is deep learning." Deep Learning is a "critical component of computing"… or biology? As customary for Turing Awards laureates, Hinton, LeCun and Bengio delivered the A. M. Turing Lecture.

At the AIMed conference 2019, UCI's sophomore, and Dalai Lama Scholar Karishma Muthukumar gave an opening speech about her idea of using empathy-based artificial intelligence to improve human connection in the healthcare field. AIMed conference is an annual conference dedicated to bringing technologists, entrepreneurs, clinicians, and healthcare professionals to define AI-enabled solutions to create efficient, humane, and patient-centric solutions for the future of medicine. At the age of 14, while she was in high school, Karishma came up with the idea of using an emoji-based communication board for patients with Locked-in Syndrome. These patients are mentally aware but unable to move or verbally communicate. Her emoji-based communication board, OutLoud, won the abstract competition for Artificial Intelligence and Big Data in the International Society of Pediatric Innovation's annual Pediatrics 2040 conference. In 2018, she was named the 2018 Young Innovators to Watch, a national scholarship program by Living in Digital Times and Lenovo.

Seasoned software executive brings full suite of global retail and technology leadership experience to drive Symphony RetailAI's focus on worldwide customer success, AI-powered innovation and growth Symphony RetailAI, a leading global provider of AI-powered platforms and customer-centric solutions for customer-centric merchandising, marketing and supply chain solutions that deliver profitable growth for retailers and CPG manufacturers, announced the appointment of Chris Koziol as CEO and a member of the company's board of directors. Dr. Pallab Chatterjee, who previously served as CEO, has retired after a long career in technology, including several years at Symphony Technology Group. Koziol has an extensive background in retail and enterprise software and brings with him over 35 years of executive experience and success in the software technology sector, including 20 years in CEO, president and chief operating officer positions for mid-size and billion-dollar businesses. He most recently served as president and CEO of Aspect Software where he helped reposition the company as a $330M cloud-based software company. Prior to that, Koziol was COO of JDA Software and was instrumental in JDA's rapid growth during his tenure, presiding over its expansion into supply chain optimization and planning solutions through a combination of acquisitions and organic growth.