AI Podcast Interviews Articles and Reports

Episode Summary: Right now, you can take a picture of a flower in your garden and post it on social media to see if anyone knows its proper name. Wouldn’t it be nice, though, if a machine could identify the correct name and species in the picture you just took? Solving this problem in applications of machine vision is something that CEO Igal Raichelgauz and his team are working on at Cortica, a machine learning company that is not focused on deep learning, but is instead taking a more "shallow" approach. In this episode, Raichelgauz articulates Cortica's approach, which is based on neurology and goes against some of the current approaches in getting machines to learn. We discuss some of these primary differences and dive into Cortica's goals for applying machine vision in consumer products.

Episode Summary: This week’s guest is Kimberly Powell, senior director of business development at NVIDIA. In an interview conducted at the 2016 AI Summit in San Francisco, Emerj kicked off the conversation by asking Powell, 'What is a GPU?' Powell explains not only the difference between GPUs and CPUs but also the factors that are making the former easier to use. She also delves into how Nvidia and others are working to make deep learning technology and related innovations more accessible to small businesses and startups across industries, a topic of interest to many companies in the Bay area and beyond. Powell is one of several female executives in the AI field who we've been fortunate enough to interview this year.

Episode Summary: Accenture is a leading global professional services company in the tech space, providing services to many of the Fortune 500 and their global equivalents. The company recently conducted a study, combined with expertise from economists and AI researchers, about the longer-term economic impact of artificial intelligence around the world. In this episode, I spoke with Chief Technology Officer Paul Daugherty, who has been with Accenture since 1986, and who was joined by Global Technology R&D Lead Marc Carrel-Billiard. We met up at a coffee shop after an AI Summit in San Francisco, and I asked Paul and Marc about what they had learned from this newly-published study and what they consider to be the significant impacts of *AI and automation on the future job market.

Episode Summary: Crowdsourcing is a relatively common term in technical vernacular today. Even if you're not a self-identified "techie", you may very may well have leveraged crowdsourcing in journalism, the sciences, public policy, or elsewhere. One area in which this concept hasn’t really taken off is in finance and hedge funds. In this episode, we speak with Numerai Founder Richard Craib, whose company is crowdsourcing a machine learning hedge fund. Their model is based on pooling data science talent from all over the world and using "anonymous" models to train financial data. These models compete against one another, and the winning models' creators are rewarded in bitcoin - a process based entirely on encryption and anonymity. Craib speaks about his overarching vision for the company, and also delves into his thoughts on the past, present, and future of AI applications in finance.
 

Episode Summary: What does the world look like when we can replicate human expertise in an assistant? Are we close to developing human-level chatbots that we can ask about law or medical conditions? We dive into this topic with Founder and CEO of exClone, Dr. Riza Berkan, whose personal assistant and chat-bot company is leveraging day-to-day human conversational templates in machine learning technology in order to better approach the tough task of replicating human expertise through a machine. Berkan talks about the edge layer of his company's “secret sauce”, and touches on the future applications of what might manifest in this field in 5 to 10 years in medical and other consumer applications.

Episode Summary: CEO Chris Nicholson speaks on Skymind machine learning applications, which integrate with Hadoop and Spark. In this episode, Nicholson sheds light on current machine learning trends that he sees across industries and best practices for implementing AI solutions in order to gain consistent return on investment. For our readers who enjoyed out consensus on future trends in artificial intelligence consumer applications, it may be interesting to hear some of Chris's specific use cases in industry.

Episode Summary: We've interviewed a number of guests on Emerj, but very few who have had a serious part of their career in selling automobiles. But Michael Perry did just that for 5 years before founding Kit, his third startup - an AI-powered Virtual Employee that works in marketing for small businesses and was acquired by Shopify in April 2016. In this episode, Perry speaks about how Kit and Shopify leverage AI on a daily basis, and how a “non-tech” person with no formal background in AI or data science can build a team for an AI project.

Episode Summary: Martin Ford started off as a software entrepreneur in Silicon Valley, but became better known for his speaking and writing on robotics' and automation's influence on the job market after writing his best-selling book, Rise of the Robots: Technology and the Threat of a Jobless Future. In this episode, Martin talks about why he believes 'white collar' jobs (as opposed to blue) are at a higher risk for automation, and gives his predictions on how automation and robotics will impact the job market over the next 5 to 10 years.