Artificial Intelligence In Industry With Dan Faggella

Natural language processing has gained more and more attention with the raise of (or rather, the "fad" of) chatbots. Despite the flurry of press releases from companies about their conversational agents (only a few of which seem to be delivering real business value), few business leaders understand the value of NLP for customer service, sales enablement, or eCommerce. In this week's episode of AI in Industry we interview Narjes Boufaden, computational linguistics PhD and CEO of Keatext, an NLP company based in Montreal. Narjes explores the possible business applications of NLP - specifically for customer service and customer experience - and she also explains (in layman's terms) how NLP systems are trained and integrated into businesses today. The ROI on this episode (in my opinion), is a firm understanding of what NLP can and cannot do, and what business applications it can realistically solve today. I was fortunate to meet Narjes in person during my Montreal trip, and I'm glad we were able to bring her on t

As a human, we can often understand the mood, intention, and future action of another person just by looking at them. We see their posture, their facial expression, where their eyes are focused, and we can get a decent understanding of what they might do next. The problem of computer vision for body language is a much harder problem to solve, but we are indeed making progress. Our guest this week is Paul Kruszewski, an computer science PhD who's spent nearly the last 20 years focused on 3D modeling and artificial intelligence. Today, he's CEO of Wrnch, a Montreal-based AI company focused on reading and understanding human body language. Paul explains how advances in 3D modeling and computer vision have allowed researchers to get machines to "understand" the posture, movements, and intentions of human being - and he also helps explore the future applications that this technology might have in security, retail, sports, and more. For more interviews on the applications of AI in business, visit: TechEmergence.com

In the future, the vast majority of photos and videos recorded won't be seen and used by humans - they'll be seen and used by machines. This week we interview Allan Benchetrit, CEO at Algolux - a Montreal-based AI company focusing on computational imaging. If you take an image for a human being in a consumer application (maybe an iPhone app or a recreational DSLR camera), you probably want it to be visually appealing and clear to the human eye. As it turns out, machines don't need pretty images, they need to do their jobs. If a computer vision system needs to detect road signs, or suspicious people in an airport, or the presence of weeds in a cornfield - it may create images that are ugly to the human eye, but perfectly calibrated for being interpreted by machines for their jobs. As it turns out, this is a complicated AI-related problem itself, and Allan walks us through it. If your business uses cameras heavily - or may do so in the future - this interview will provide an around-the-corner look at what it ta

Procurement isn't usually seen as a "sexy" aspect of a business's operations. Procurement personnel are responsible for sourcing suppliers or vendors, determining criterion of success, negotiating deal terms, and tracking results and deliverables - all of which could be considered "under appreciated" work. This week, Tamr's Eliot Knudsen walks us through the ways that AI is making it's way into the procurement process, and what it means for the future of this job function. For more executive interviews about the applications and implications of AI, visit: www.TechEmergence.com

This week we speak with Bastiaan Janmaat (CEO and co-Founder of DataFox) about the current and future applications of artificial intelligence in the CRM. No matter what business you're in, there's a high likelihood that managing relationships with customers, wholesalers, suppliers, or affiliates is important to your daily operations. Artificial intelligence is currently being employed to help with automating data entry, automating email and phone reminders, and even prompting salespeople with the right phone scripts in real time. In addition to covering "what's being done now" - spend the end of the interview asking Bastiaan about his predictions of the most likely AI-for-CRM capabilities that will become commonplace in the next 5 years. For more AI executive interviews, and insights into current and future AI trends that are shaking up industries, visit: www.TechEmergence.com  

Artificial intelligence is coming - should be worried about our jobs? Well, it depends. Our guest Dr. Kevin LaGrandeur spent the last two years researching the impacts of automation and artificial intelligence on society and the job market. In this interview on AI in Industry, we explore the near future of AI's impact on the world of work, and I ask Kevin some important questions, including: What skills are least "automate-able" in the next decade? What middle class professions have the greatest risk of automation, and what should those professionals be doing now to hedge against job loss? What should business leaders be doing now to prepare for "phasing out" work while still taking care of their employees? For more interviews with AI executives and researchers (and more insight on applying AI in your organization) - visit us online at: www.TechEmergence.com

Though we don't think about it on a daily basis - the technologies around us often "work" because of an underlying standard that they depend on. These technologies include: Wifi, ethernet, fax, and much of the internet itself. Do certain AI applications need their own set of standards in order to scale? Imagine if you needed a new type of cable or input every time you wanted to jack your computer into the wall? Imagine if you needed different hardware to pick up wifi in every location you moved around to? Imagine if all websites had totally different protocols for how they were loaded or served to your computer? If this were the case, it would be extremely challenging for a robust "ecosystem" of internet companies and technologies to emerge, because the technology wouldn't scale or work well at all. This week we interview Konstantinos Karachalios,‎ Managing Director of the Standards Association at the Institute of Electrical and Electronics Engineers (IEEE). Konstantinos holds a PhD in Physical and previously

It would be great if instead of having our car break down - could have them fixed as soon as the underlying problem began. It would be great if instead of having to diagnose a malfunctioning piece of mechanical equipment - would could have the right "fix" presented to us immediately. As it turns out, artificial intelligence may be working its way to accomplish both of those goals in the not-so-distance future. This week we interview Tilak Katsuri, CEO of Predii, a predictive maintenance AI company based on Palo Alto. Predii focuses on helping service people by using AI and sensor data to prescribe proper repairs. In this episode, Tilak speaks with us about what's currently possible within the world of "predictive maintenance," as well as the possible ramifications of industrial IoT and AI in the next 5 years. For more interviews about the real-world applications of artificial intelligence in business, visit: www.TechEmergence.com

A huge percentage of digital advertising dollars today go to Google and Facebook, who dominate that sector - and are inevitably central for the future of programmatic advertising. There’s a lot of evidence to suggest that the growth in digital advertising in the last two to three years has gone almost entirely into their coffers. At least for the foreseeable future, Facebook and Google will retain the ability to dominate that space. The ability to be able to bid for the attention of particular target audiences, whether they’re searching for a specific term, live in a specific place or they like a specific sports team, is something that doesn’t seem to be going away, and seems to be rather efficient, thanks in the large part to Artificial Intelligence. In this episode we talk to Lior Tasman who is the CEO of PredictiveBid, an Israeli-based predictive advertising optimization start-up. The team focuses on applying AI to some of the bigger issues in programmatic advertising to help draw out more ROI from ads. We

The big tech giants, such as Amazon, Google and Netflix, tend to set the stage in a lot of different domains and set public expectations to raise the aggregate tide of consumer experience. Our online experience is somewhat different each time we use these and other sites. This is because many of these tech giants alter their experience user per user in a real time iterative fashion in order to create sticky experiences and to beat their competitors. In this episode we talk to Adam Spector, the Co-Founder & Chief Business Officer at LiftIgniter, a company which provide a service which modulates website experience per users, for an array of different businesses. Adam and I discuss what the tech giants are doing to customize their business experiences, what data they’re using to continually alter user experience and what industries and sectors might be impacted by this aggregate trend as it moves forward. See more interviews with AI industry innovators at: www.TechEmergence.com

Imagine you work in a large organization with tens of thousands of employees across multiple countries, a business that’s been around for over a hundred years, and all of a sudden you have people in one department who are interested in applying chatbots, colleagues in another department who wish to implement sentiment analysis and still another department that wants to begin using AI for fraud and risk analysis. How do you manage to put all these pieces together? That is exactly the situation that Muriel Serrurier Schepper found herself in.  Muriel is the Business Consultant Advanced Data Analytics & Artificial Intelligence at Rabobank Digital Bank in Naarden, Netherlands. In this episode, Muriel and I discuss the Artificial Intelligence Center of Excellence at Rabobank, where she manages projects and has connected ad virtual and physical team across the company which is comprised of over 60,000 employees spread across the world. For more interviews on the applications of AI in industry, visit: www.TechEm

If you work in healthcare, or in an established business that is looking to implement AI for the first time - then this won't be an interview you'll want to miss. AYASDI is one of those rare AI startups that has raised over $100MM since its inception in 2008. This week on the "AI in Industry" podcast,

Marshall Brain discusses how wetware (the human brain) is increasingly becoming a part of a bigger system which may in itself be managed by software systems. The roles and relationships of humans and machines are rapidly changing. With the increasing advances in technology, there are fewer and fewer skills or activities that an enterprise needs from human beings, and they only need those until they can be replaced by software or hardware. For example, computer vision systems are often still not as effective as the human eye, so we still need human vision systems to recognize text or to recognize object placement, and take action accordingly (in a store, warehouse, or other setting). A human can fill that role as a piece of wetware until the software or the hardware catches up. How will man and machine collaborate in the future? We explore these dynamics in depth in this week's interview. For more interviews and insights from leading thinkers in AI and automation, visit: www.TechEmergence.com

Machine learning currently faces a number of obstacles which prevent it from advancing as quickly as it might. How might these obstacles be overcome and what impact would this have on the machine learning across different industries in the coming decade? In this episode we talk to Dr. Hanie Sedghi, Research Scientist at the Allen Institute for Artificial Intelligence, about the developments in core machine learning technology that need to be made, and that researchers and scientists are working, on to further the application of machine learning in autonomous vehicles. We also touch on some of the impact that might be made if machine learning is able to overcome its own boundaries in terms of computational research, in terms of certain algorithms, and what kind of impact that might have in the arena of autonomous driving and in the realm of natural language processing (NLP). See more episodes online at: www.TechEmergence.com

Fraud attacks have become much more sophisticated. Account takeovers are happening more often. Many security attacks involve multiple methods and unexpected attacks can devastate businesses in just a few days, as we saw with Neiman Marcus and Target. False promotion and abuse is seen not only on social media sites but is also targeted at business. To combat these risks, fraud solutions need to be smarter to keep pace with fraudsters to prevent attacks and react quickly when they do happen. This requires a fast-learning solution with the ability to continually evolve. In this episode we talk to Kevin Lee from Sift Science and examine the shifts in the info security landscape over the past ten or fifteen year. Lee also highlights what new kinds of fraud are now possible and what machine learning solutions are available. See more episodes at: www.TechEmergence.com  

Unlike the field of self-driving cars, the fields of construction, mining, agriculture, and other classes of “heavy industry” involve a huge variety of equipment and use-cases that go beyond traveling from A to B. The heavy industry leaders of today are no farther behind automakers in their understanding that AI and automation will be essential for the future of their companies. In this episode, guest Dr. Sam Kherat discusses the areas in heavy industry where AI is currently playing a role in heavy industry, what type of capabilities and functions are automatable, and at what level. He also shines a light on how AI might affect the future of the industry within the next 2-3 years, and in what ways we can expect large equipment to become more autonomous.

Although machine learning in finance is far from new, it is merely at the cusp of a much wider set of applications (in all segments of finance, from insurance to bookkeeping and beyond). Already machine learning has overhauled so many aspects of the financial landscape, from accounting to trading, and it is destined to have more and more impact as it develops further. Guest Alexander Fleiss and his team at Rebellion Research are developing and using AI which uses quantitative analysis to pick investments. Fleiss discusses the current status of machine learning in the world of finance as well as lesser-known niche applications that don’t make headlines - but do make a big impact on how businesses are run. He then goes on to explore the effects of future innovative applications of AI in the financial domain.

Guests Will Jack and Nikhil Buduma co-founders of Remedy Health Inc discuss the challenges involved in collecting, setting up and structuring data in order to implement AI in healthcare. By the end of this episode, listeners will have gained insight into the challenges of healthcare data systems, and the potential solutions to cleaning and organizing this data for healthcare AI applications.

If there's any industry ripe for disruption by AI and ML applications, it's healthcare. This week, we speak with ElevenTwo Capital's Founder and Managing Partner Shelley Zhuang, whose investment focus (among other spaces) is on innovative healthcare services. In addition to discussion how AI is helping propel genomics, diagnostics, therapeutic treatment, and other innovations, she touches on what the healthcare space might look like in the next 10 years. For healthcare startups looking to break into the healthcare market, Zhuang doesn't pretend to have simple answers; however, she identifies commonalities among companies that have been successful in smart preparation for meeting regulatory and other industry considerations. This interview was recorded live in San Francisco at Re-Work's Machine Intelligence in Autonomous Vehicles Summit in March 2017.  

In the last few months, we've had a string of fantastic interviews with investors and have gained a cross-industry picture of what's important for start-ups and emerging trends in the AI and ML space. This week's interview is no exception. Ann Miura-Ko, co-founder and partner at Floodgate, starts with an explanation of the "self-driving enterprise" concept, her functioning idea about AI investing and the future of software in general. Her high-level insights embody an interesting emphasis on the dynamic of human-machine interactions and relationships cross industries, including the constant workflows and interactions of people using software and bolstering the predictive and prescriptive analytics capabilities of that software. While forward-thinking, Miura-Ko also paints a picture of how these synergistic relationships between humans and machines are happening with companies today.