Artificial Intelligence In Industry With Dan Faggella

Today is episode five out of five of this week’s special series on Achieving ROI with Early AI Projects. We’ve heard from leaders from Intel, Oracle, and other big names, and today, we’re wrapping this series up with someone from the startup world. Our guest is Nikunj Mehta, Founder and CEO of Falkonry. Falkonry is an AI services business focused on heavy industry and manufacturing based in the Bay Area. In this episode, Nikunj describes a portfolio approach to find several related AI projects and capabilities that are likely to turn into a win. He also discusses why an enterprise’s most important objectives are not always the best fit for early AI projects. Stay tuned until the end of this episode to learn about the AI ROI reports that we’re making available for a limited period.

Today’s episode is part four out of five in our Achieving ROI with Early AI Projects series. This week, we have published one episode per day, starting with the Head of the AI Centre of Excellence for Intel. Today, we’re bringing it down to more of a consultancy and vendor perspective from someone who has worked with some of the largest enterprises in the world. Our guest is Dr. Charles Martin, a Silicon Valley AI Consultant with hands-on machine learning experience with organizations like Ebay, BlackRock, and more. In this episode, Charles discusses the concept of data quality mismatch, which can serve as a useful diagnostic tool for estimating what kinds of tasks it will be best suited for. He also speaks about picking projects where you have the data assets to achieve ROI. Be sure to visit emerj.com/p1 to access Emerj’s frameworks for AI readiness, ROI, and strategy.

Today is the third episode of this five-part series being published every day this week on achieving ROI with early AI projects. We’ve heard from the Head of the AI Center of Excellence at Intel and the Head of Insure AI at Munich Re, and today, we speak with the VP of Engineering for Oracle’s Digital Assistant, Raefer Gabriel. Raefer was a previous guest on the show, and he’s also worked on Amazon, including their Alexa platform, and had a startup before then. In this episode, we speak from his perspective on how we can achieve that early AI ROI. He also details how you can diagnose the data assets required to meet a specific goal to determine if your data would be a good fit and start with more modest projects on the crawl, walk, run scale. Be sure to tune in to the rest of the series to gain valuable insights and advice from enterprise leaders on achieving ROI with early AI projects.

This is the second episode of our five-part series on achieving ROI, with early AI projects taking place this week. This series brings together great perspectives from various leaders around advice that can help us bypass typical mishaps to achieve AI ROI. Today’s guest is Michael Berger, Head of Insure AI at Munich Re. Munich Re is a $60B insurance giant heavily invested in cyber insurance and AI insurance. This episode focuses on risk and, more specifically, what kinds of questions we can ask upfront to screen for risk. Michael also provides advice for enterprise leaders in various industries to make smarter decisions regarding risk. During this special series week, we are giving away some of our AI ROI reports here at Emerj. Be sure to tune in until the end of this episode to learn more about these offers for our listeners and subscribers.

Today is the start of a five-day series covering achieving ROI from early AI projects. In this series, we interview diverse experts from companies large and small about what it takes to pick AI projects with the highest chance of ROI. Our first guest is Gopalan Oppiliappan, Head of the AI Centre of Excellence at Intel Corporation. In this episode, Gopalan discusses how to structure project selection and AI project management in a purpose-built to find ROI. As we launch this series this week, we have also made the “AI ROI in Action” report free for download at emerj.com/r5. Previously only available to Emerj Plus members, you can get it for free now to learn more about predicting the costs and returns of AI projects and how to communicate these findings to leadership in a way that sets the right expectations.

Today’s guest is Emmanuel Walckenaer, CEO of YSEOP. YSEOP is a natural language generation AI vendor serving life sciences and drug development. In today’s episode, Emmanuel speaks about speeding up the drug development process through the lens of the life sciences industry being in extreme flux and what happens when a new normal is achieved and how companies have to scramble to keep up with it. Emmanuel also talks about the expansion of AI projects and capabilities in the enterprise. Today’s episode is brought to you by YSEOP. If you’re an AI vendor looking to reach a global enterprise audience, you can learn more about how we work with vendors from sponsored podcasts, articles, co-branded research, lead generation, and more at emerj.com/ad1.

In the third episode of our AI Success Factors series, we’re discussing a public sector application of AI. This Monday series is designed to deliver concise, industry-agnostic insights to start your week with a specific use-case and the most crucial success factor that brought it to life. Today, our guest is Richard Benjamins, Chief AI and Data Strategist at Telefónica. As one of the world’s largest telecommunications companies, Telefónica is a business that makes over $50B in annual revenue and has more than 100,000 employees worldwide. In this episode, Richard speaks to us about a specific project designed to reduce COVID cases by using data related to the movement of people. He also discusses the project’s results detailing how it was used in the real world and what factors led to its success. If you enjoyed this episode, be sure to tune in for the rest of the AI Success Factors series on The AI in Business Podcast at podcast.emerj.com.

Today’s guest is Daniele Cordioli, Head of Solutions Consulting for EMEA at Expert.ai. In this episode, Daniele discusses what contract analytics means and the concrete use-cases we can get from it. There are two big transferable lessons that Daniele highlights in this interview. The first lesson is determining the low-hanging fruit cases where AI can save money and reduce risk when dealing with your volume of contracts. Second, the proper method to establish where the business value lies in your own business. This episode is sponsored by expert.ai. If you’re interested in reaching Emerj’s global AI-focused executive audience through podcasts, emails, sponsored content, and more, you can contact us at emerj.com/ad1.

This is our second episode of our new Monday series highlighting AI Success Factors. Our guest is Beena Ammanath, the current Executive Director of the Global Deloitte AI Institute. Beena is also the Founder of Humans for AI, an organization that provides AI education for underrepresented female minorities, and recently wrote a new book called "Trustworthy AI". In this episode, she discusses one of GE’s early AI projects around procurement and how using a crawl, walk, run strategy can lead to tens of millions of dollars in savings. Be sure to tune in next Monday for the next episode in this series and start your week with pivotal insights about how to turn AI into ROI no matter what industry you’re in.

Today’s guest is Carlos Escapa, AI Global Business Development Manager at Meta (formerly Facebook), and in this episode, we explore what business leaders need to know about open source. Carlos clarifies what open source is and what is relevant for enterprise leaders, and the kinds of situations in which open source tools might be more suitable. He also discusses where leveling up and retaining talent crosses over with open source. Be sure to join Emerj Plus at emerj.com/p1 to unlock our entire library of AI use-cases, best practice guides, white papers, frameworks, and more.

Today’s episode is the first of our new Monday series, AI Success Factors. This series will feature a short episode every Monday for the next four months geared towards starting your week with a look at what it takes for AI to succeed across industries and sectors. Our first guest of this series is Raefer Gabriel, VP of Engineering for Oracle’s Digital Assistant. Raefer previously worked as Head of Engineering for Conversational AI at Amazon. In this episode, he explores a book recommendation use-case, looking at Amazon’s roots from a new perspective. Raefer also identifies two key success factors: firstly, communicating value and strategically selecting projects, and secondly, picking your battles. Tune in next week for the second episode of this series to learn how to make your AI projects and ideas even sharper.

This week’s guest is Peter Tu, Chief Scientist for Artificial Intelligence at GE Global Research. Peter joins us to discuss the transition from the previous era of AI into the current “third wave” of AI in a way that will make sense for business people. He also shares insight on what it’ll take for AI to make the leap to contextual adaptation and what this might mean for business leaders in terms of how it could affect their current processes. If you’re interested in discovering AI trends and being able to identify AI use-cases and trends in your industry, be sure to stay tuned until the end of this episode to learn more about Emerj’s tools designed for business leaders and how to access them to discover more AI opportunities and maximize AI ROI.

This week’s guest is Rajkumar Bondugula, Fellow and Luminary Scientist at Verizon. Rajkumar holds a Ph.D. in Machine Learning and was previously the Principal Data Scientist at Equifax. In this episode, Rajkumar clarifies some of the critical differences between business intelligence, analytics, and data science. He also discusses how these concepts build upon one another and help businesses level up their services. If you’re interested in more insights on building AI maturity, building proper data science teams, being able to identify high-value AI projects and move them forward, be sure to check out Emerj Plus at emerj.com/p1 to unlock our AI best-practice guides, whitepapers, and entire AI use-case library.

Our guest this week is Stacey Shulman, Vice President Internet of Things Group / GM Health, Life Sciences and Emerging Technologies at Intel Corporation. In this episode, Stacey discusses where she sees AI make its way into healthcare now, how Covid has affected how adoption has been prioritized, and its consequences in the future. Stacey’s insights about how healthcare is evolving are correlated to how other enterprises are also adjusting their strategies or potentially should be in the setting of the ongoing pandemic. If you’re interested in unlocking our AI best practice guides, frameworks for AI ROI, and specific resources for AI consultants, visit emerj.com/p1.

Today’s guest is Anand Mahurkar, Founder and CEO of Findability Sciences. With about 100 employees worldwide, Findability operates in a variety of industries, including manufacturing. In this episode, Anand provides an in-depth overview of the workflows that are impacted in predicting inventory and resource use in manufacturing. He also discusses what it looks like to determine the data sources you’re going to use and influence the workflows you will use to make more informed forecasting decisions. This episode is sponsored by Findability Sciences. If you’re interested in finding more high ROI use-cases in your sector, be sure to download our free PDF brief, “3 Ways to Detect AI Trends in Any Sector,” at emerj.com/t3.

Today’s guest is Bob Gaines, Managing Director of Business Development at SambaNova Systems, a firm based in the Bay Area that has raised $1B to date. Bob has worked in financial services and technology with companies like IBM, Cray Supercomputing, Deephaven Data Labs. In this episode, he brings his perspective on how this technology has evolved regarding AI’s impact in finance and where it’s going. He also discusses how AI is being used not just to look at the individual entities exchanging funds but also to look at the behavior of the entities around them and the entities they do business with. This episode is sponsored by SambaNova Systems. Visit emerj.com/ad1 to learn more about reaching our global audience.

Our guest this week is Dr. Seth Dobrin, the Global Chief AI Officer at IBM, one of the biggest names in artificial intelligence. In this episode, Seth returns to the podcast to speak about AI governance in terms of enabling innovation and driving better results for enterprises. He also discusses the right way to structure and think about AI governance to allow for efficiency and higher quality products. This episode is sponsored by IBM. If you’re interested in reaching Emerj’s business audience, be sure to visit emerj.com/ad1 to learn more about our media services.

Today’s guest is Remi Duquette, Vice President of Innovation and Industrial AI at Maya HTT. Maya HTT is an engineering and industrial AI services firm that Remi’s been with for twenty years. Remi draws on his hands-on experience to discuss the challenges and opportunities of improving productivity with AI in manufacturing. Today’s episode focuses on the question of where artificial intelligence can be implemented into existing workflows to improve output. This episode is sponsored by Maya HTT. If you’re interested in reaching Emerj’s global enterprise audience, check out emerj.com/ad1 to learn more.

This week’s guest is Gregory Diamos, Machine Learning Systems Engineering at Landing AI. Run by one of the most prominent names in the business AI world, Andrew Ng, Landing AI has raised over $50M to date. Before Andrew founded Landing AI, he and Gregory worked together in the Baidu Silicon Valley Research Lab. In today’s episode, Gregory discusses a broad set of AI use-cases in agriculture that he thinks are going to make the most significant impact in the years ahead. If you’re interested in unlocking our AI best practice guides, frameworks for AI ROI, and specific resources for AI consultants, visit emerj.com/p1.

Today’s guest is Joe Bradley, Chief Scientist, SVP Data Science & ML at LivePerson. Joe was previously the Senior Director for Data and Personalization Science at Nike before joining the team at LivePerson. In this episode, Joe breaks down how LivePerson approaches the conversational interface dynamic with their customers. Joe also discusses some of the challenges in getting to a genuinely conversational level and what’s possible today. If you’re interested in more NLP use-cases or want to learn more about chatbots or search-and-discovery, be sure to download our free PDF brief “The Executive Guide to NLP” at emerj.com/nlp1.