The AI in Business Podcast

Episode Summary: In this episode of the podcast, we interview AIG's Chief Data Science Officer, Dr. Nishant Chandra, about natural language processing (NLP) for internal and team communication. Dr. Chandra talks about how NLP can help with sharing documents with specific team members whose roles warrant viewing those documents. Instead of a broad memo that would go out across the company, a docume...

This week's episode of the AI in Industry podcast focuses on two main questions. First, how should business leaders determine the most fruitful, potential applications of AI in their business? Second, how do they choose the right one into which to invest resources? This week, we interview someone who has spoken with a number of CTOs and CIOs about early adoption strategies for machine learning for...

At TechEmergence, we often talk about the software capabilities of AI and the tangible return on investment (ROI) of recommendation engines, fraud detection, and different kinds of AI applications. We rarely talk about the hardware side of the equation, and that will be our focus today. For hardware companies like Nvidia, stock prices have soared thanks to the popularity of new kinds of AI hardwar...

Episode Summary:  Facebook and Google's advertising complex is founded on machine learning, allowing people to self-serve their data needs across a broad audience. India-based InMobi is a company in the advertising technology space that delivers 10 billion ad requests daily. Today, we speak with Avi Patchava, Vice-President of Data Sciences and Machine Learning at InMobi, which operates in China,...

Companies with wells of data at their disposal may find themselves asking how they can use them in meaningful ways. Generally speaking, a clean set of data is the foundation for AI applications, but business owners may not know how exactly to organize their data in a way that allows them to best leverage AI. How exactly does a business transition from having data with the potential for usefulness...

Episode summary: In this episode of Ai in industry, we speak with Manoj Saxena, the Executive Chairman of CognitiveScale, about how AI and automation are being applied to white-collar processes in the healthcare sector. In simple business language, Manoj summarizes key healthcare applications such as invoicing handling, bad debt reduction, claims combat, and the patient experience, and explains ho...

Episode Summary: Natural language processing (NLP) has become popular in the past two years as more businesses processes implement this technology in different niches. In inviting our guest today, we want to know specifically which industries, businesses or processes NLP could be leveraged to learn from activity logs. For instance, we aim to understand how car companies can extract insights from t...

Episode summary: This week on AI in Industry, we speak to Rana el Kaliouby, Co-founder and CEO of Affectiva about how machine vision can be applied to detecting human emotion - and the business value of emotionally aware machines. Enterprises leveraging cameras today to gain an understanding of customer engagement and emotions will find Rana's thoughts quite engaging, particularly her predictions...

A myriad of customer service channels exist today, such as social media, email, chat services, call centers, and voice mail. There are so many ways that a customer can interact with a business and it is important to take them all into account. Customers or prospects who interact via chat may represent just one segment of the audience, while the people that engage via the call center represent anot...

Episode summary: In this episode of AI in Industry, we speak with Khalifeh Al Jadda, Lead Data Scientist at CareerBuilder, about the applications of machine learning in improving a user's search experience. Khalifeh also talks about what the future of search might look like and how AI will continue to make the search experience more intuitive (for search engines, platforms, eCommerce stores, and m...

Episode summary: In this episode of AI in Industry, we speak with Andy Terrel, the Chief Data Scientist at REX - Real Estate Exchange Inc., about how AI is being used in the real estate sector today. Looking ahead ten years into the future, Andy paints a picture of the areas where he believes AI will change the real estate business. Andy explores how marketing in real estate might change in the fu...

Episode summary: Here on the AI in Industry podcast, we've heard AI experts explain how high-performance computing (HPC) has enabled everything from machine vision to fraud detection . In this week's episode, we speak with Paul Martino, Managing Partner at Bullpen Capital, about which industries and AI applications will require high-performance computing most. Paul also adds some useful tips for b...

Episode summary: In this episode of AI in Industry, we speak with Dr. Sanmay Das from the Washington University in St. Louis about risk prediction and management in industries like banking , insurance and finance . Sanmay explores how are banks and other financial institutions are improving risk and fraud prevention measures with machine learning. In addition, he explores the ramifications of impr...

Episode summary: In the last two or three years we at TechEmergence have witnessed a definite uptick in AI applications like predictive maintenance and heavy industry. Many exciting business intelligence and sensor data applications are making their way into "stodgy" industries like transportation, oil and gas , and telecom - where machine vision has countless applications. We had caught up with M...

Episode summary:  In this episode of AI in Industry we speak with Abhi Yadav, the CEO of ZyloTech, a Boston-based customer analytics platform for omni-channel marketing operations. Abhi talks about what's possible now with AI for marketing personalization, and what will be possible in the next 5 years. Business leaders with an increasing focus on narrower customer targeting will be interested in A...

Episode summary: In this week's episode of AI in Industry we speak with DataRobot CEO Jeremy Achin about the future of AI applications for people without a data science background. We specifically discuss how future AI tools might bypass the complexity of machine learning programming and make intuitive interfaces that function more like today's everyday software. Our business leader listeners will...

Episode summary: In this week's episode of AI in Industry, we speak with Larry Lafferty, the President and CEO of Veloxiti. Larry has been building large AI projects for DARPA and other large private companies for the last 30 years. In this interview, Larry explains three critical factors to applying artificial intelligence in the enterprise (with insights especially relevant for companies who are...

Episode summary: In the heavy industry sector, the cost of unpredicted repairs or machine failures can be very expensive. For example: A cargo train with an engine failure in will incur costs from it's own repairs, from the transit required to reach the broken down engine, and with holding up other trains and cargo in the process. Predictive maintenance has the potential to help businesses assess...

Episode summary: In this week's episode of AI in Industry we speak with Rodney Brooks, Founder and CTO of Rethink Robotics, a collaborative robot manufacturers founded in Boston in 2008. Rodney explores robotic safety an regulations and he also paints a picture of what robots might be capable of in the next five years. Executives in the logistics and manufacturing sectors considering adopting robo...

Episode summary: One of the key challenges that enterprises face in adopting artificial intelligence is finding skilled data science talent; ). Business leaders want to know when it's best to hire AI talent, to "upskill" existing workers, or simply to bring in AI consultants - and the answers aren't always obvious. In this episode of AI in Industry we speak with Nikolaos Vasiloglou from MLTrain ab...

Episode Summary: Over the last couple of years there has been a definite but small shift from mobile as the primary interface focus for businesses to voice. With home assistant devices like the Amazon Echo and the Google Home becoming more commonplace, we aim to focus on how voice based AI applications are being used by businesses today and what this adoption will look like in the future.   In thi...

In this week's episode we focus on AI application in the customer service business function, - specifically in the context of call centers. We speak with Ali Azarbayejani, CTO of Cogito based in the Boston area, which works on coaching and providing feedback for call center agents in real time. We aim to focus on what our readers and business executives can do today with AI in the context of call...

Episode summary: There are many challenges to bringing AI into an enterprise for example the lack of skilled AI talent, or issues around data organization. In this week's episode, we focus on AI adoption in the enterprise from an investor's perspective. We expect that founders looking to sell B2B enterprise AI-products and people in enterprises who are looking for the right qualities in an AI firm...

Episode summary: In this week's interview on the AI in Industry podcast, we speak with Amir Konigsberg, the CEO of Twiggle, about the future of product search - and how eCommerce and retail brands can use natural language processing (NLP) to improve their user experience. Amir explains some of the factors that make eCommerce product search challenging, and the artificial intelligence approaches th...

Episode Summary: Machine learning (ML) can be used to identify objects and pictures or help steer vehicles, but is not best suited for text-based AI applications says Robbie Allen, founder of Automated Insights . In this episode of AI in Industry, we speak with Robbie about what is possible in generating text with AI and why rules based processes are a big part of natural language generation (NLG)...