The AI in Business Podcast

When Google's DeepMind won against one of the best modern Go champions, is used multiple AI approaches and exposed gaps in some individual strategies. This even has shed more light on AI, but also on the utility in combining approaches to AI for individual problems. Data security is one of these problem areas where multiple AI approaches is being used to make our information safer. Dr. Sal Stolfo has been a professor at Columbia in Computer Science since 1972 and is now also the CEO of Allure Security, with a focus on engineering network intrusion detection solutions using AI applications. In this episode, Stolfo talks about the various styles of AI and statical methods that have been and are being used to detect malicious activity, as well as how he believes the future of security is going to have to adapt as increasing amounts of data become available.

It isn't by chance that birds fly in flocks and fish swim in schools - they're actually smarter when they act in a group. Could it be possible to extend that collective intelligence to human beings, and even AI? Louis Rosenberg is a PhD from Stanford, previously founder of Immersion and who now runs Unanimous AI, a company focusing on harnessing swarm intelligence with human beings. In this episode, Rosenberg speaks about how this collective-intelligence approach has been applied to human beings in terms of garnering improvements in a range of predictions, and he also touches on what this type of swarm intelligence might mean when we talk about multiple AI's in the future.

Predictive analytics and machine learning are all the rage in Silicon Valley, but how do companies actually derive value by leveraging these technologies? We asked this question to Dr. Ronen Meiri, CTO and Founder of DMWay, a predictive analytics and machine learning platform company based in Israel. In this episode, Ronen speaks about what his company does and how smart executives are starting to make decisions how to choose and decide on the a smart, user-friendly platform that fits their business' needs.

Our guest in this episode has spent a large part of his life on figuring out how to make machines more intelligent. LoopAI Chief Scientist Patrick Ehlen has worked on a number of important projects, from DARPA projects to big-company AI solutions at places like AT&T. LoopAI works on getting AI to make sense and meaning of unstructured text, and Ehlen talks about the potential business applications for this technology and where it's making way its way into industry. Ehlen also touches on the implications for developers in the nascent AI field - like LoopAI - that are vying to implement its technology as an industry standard, and how such organizations will have to market themselves and deliver services to develop a thriving AI ecosystem.

This week's guest is Senior Vice President of SPARK, an economic development organization dedicated to getting startups and other early-stage companies off the ground in Ann Arbor. Skip Simms speaks on how to convey complex technologies to investors who don't necessarily have your technical expertise, and still close the deal and get the investment. Simms talks about companies he's seen do this well (and not so well), and how aspiring companies can do a better job of convincing investors to get in on new or unfamiliar technologies, something many AI company founders will have to deal with in some shape or form in launching a new entity.

For some companies, big data remains an abstraction; for others, it's an integral part of the lifeblood of a business. Mat Harris is vice president at Sojern, a travel marketing platform that has leveraged big data to grow $3 billion in bookings and 1/3 of a billion traveler profiles across its platform. In this episode, Harris speaks about how Sojern and other businesses are using a combination of their data and other sources of data (what he calls third and "second" data sources) in order to make informed marketing decisions and better market their services to buyers. Harris sheds light on the direct ROI for big data in different businesses, and it's an interesting episode from the perspective of an executive who is using big data to make decisions on business directions.

Companies looking to raise money are often asking what investors think of their company, their industry, and how they're making investment decisions in related companies. In this episode, I ask these questions of Robert Seidel, who is managing partner of Motus Ventures, an investment firm focusing on autonomous Vehicles and the IoT. Seidl talks about various data sources and the people and networks from which investors draw information when they don't have what they need on-hand and need to make important investment decisions. He also shares his perspective on the high-energy and competitive investment world of AI, including his thoughts on the most exciting (and confusing) areas in the industry.

This week's interview was recorded live at Nuance's Silicon Valley office with guest Charlie Ortiz, director of the AI and Natural Language (NL) Processing Lab for Nuance Communications in Silicon Valley. In this episode, Ortiz speaks about what he sees as the most important developments in natural language processing (NLP) over the last few years, what advancements brought us to where we are today, and where progress might take NLP in the coming years ahead (both at Nuance and beyond).

Fifteen years ago, investing in AI may have seemed a bit far-fetched, but today it's not at all a rare occurrence; however, it's more rare to find entire firms dedicated to investing entirely in AI. In today's episode, we're joined by Saman Farid, co-founder of Comet Labs, an investment firm focused on investment in AI companies across industries. He speaks about his investment hypothesis in the future of AI, why he's decided to hone his funds in this domain, and the different domains where he believes AI is ripe to disrupt on a global level in the coming few years.

One of the most memorable moments from this interview is when our guest mentioned that Larry Page hired him to solve intelligence; very few people can say this, and this says something about today's guest, Dr. Nando de Freitas - a senior researcher at Google and professor at Oxford - as well as the gravity of his present work. Today, I speak with Nando about a topic well known through his research at Google, deep learning. de Freitas gives his perspective on the basics of deep learning, the applications in conversational interfaces and recognizing images and videos, and what the future of this technology might look like in the nearer future.