AI Master Group

Jim Griffin
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AI Master Group

Hosted by Jim Griffin, this show features the researchers and leaders who are building the future of AI in their work today. Join us for thought-provoking conversations about the evolving world of artificial intelligence.

  1. NOV 24

    Tapan Khopkar: A ‘MasterClass’ in Marketing Mix

    Tapan is the Executive Director of Marketing Sciences at OMD. This episode is a very thorough compendium of marketing science principles and practices, as applied to decisions about paid media. Topics include: •    Marketing Mix Modeling (MMM) vs Multi-Touch Attribution (MTA) vs experiments, including how to use each and for what purpose •    KPIs: Incremental sales vs top-of-funnel metrics like awareness and consideration •    How to design incremental changes in the direction that a model is pointing •    Testing a new marketing mix in various geo markets •    Judicious use of model hyperparameters, such as AdStocks •    The best cadence for measurement •    Third-party cookies (Implications of the shift towards user choice) •    Recent tools: Google Meridian (a Bayesian approach) vs Meta Robyn (a frequentist approach) These ideas are brought to life with an example from a financial services brand, planning a big launch, with a need to answer questions like: How should the paid media budget be allocated? Should the focus be branding first and performance later? How should ad spend be flighted (Always-On vs Burst and Trickle)? In effect, this show is a Master Class regarding marketing science, as described by one of the world’s top authorities on the topic, who’s currently an Executive Director at OMD, which is the world’s largest media agency network.

    50 min

  2. NOV 16

    Aida Farahani: From 2D to 3D in Seconds

    With a specialization in 3D deep learning, Aida is doing ground-breaking work related to 3D simulations. In this episode, she first describes why meshes or point clouds are computationally-expensive for simulating changes to shapes. She then describes why “implicit fields” are much more efficient for this, as described in the widely-cited “DeepSDF paper.” Next she describes a special-case problem: Predicting the deformation of 2D objects into 3D shapes, such as when metal blanks are stamped into the shape of a car door, for example, which is a case that violates one of the assumptions for DeepSDF. However in this episode, Aida describes a method for using implicit fields to solve this problem too, thereby transforming a simulation process that used to take 20 minutes per trial to just a few seconds per run. In effect, this show is a preview of her soon-to-be-published doctoral dissertation!

    21 min

  3. NOV 9

    Nikhil Patel: Inside Sally Beauty’s Data Strategy

    Nikhil is the Data Science Director at Sally Beauty Holdings, which is a $3.7 billion specialty retailer, with more than 10,000 products sold through over 4,000 stores, as well as online. Prior to his current role, Nikhil held a senior leadership role at Harman International, working with panel data from top CPG brands like P&G, Unilever and Kraft. In this episode, Nikhil describes his 19-year journey, starting from a Masters degree in Applied Mathematics, leading up to his current role at Sally Beauty. Within that, he describes several times when he needed to supplement his formal education with ad hoc or certification-led studies, in order to stay current and relevant. He also discusses omni-channel marketing, customer journeys and Segment of One, as well as emotional understanding of the consumer, beyond pure data science. And he describes how one-on-one experiences, like Studio by Sally (in store) or “licensed colorist on demand” (online), can change customer journeys, and can provide valuable insights for new product development.

    32 min

  4. NOV 2

    Victor Perrine: From Bananas to $Billions

    Victor (Viko) Perrine is the Global Director of New Growth Initiatives at Circle K. Prior to that, he’s held senior leadership roles at Delek US Holdings and at UGP Inc.  In this episode, Viko describes a major new initiative called Lift that's unique to Circle K, which just launched in Europe, plus future development plans for that. Building on this, he describes the day-to-day for a global innovation leadership role, and he shares the success factors that help him to identify good target projects for innovation and growth. He also describes a project from earlier in his career that used lidar and computer vision to count banana trees on a 6,000 acre planation in the Philippines, which was the first time that had ever been done in that country. And with all this as context, he concludes with actionable tips for people who’d like to get the nod for leadership roles in innovation.

    25 min

  5. OCT 28

    Ray Pettit: New Models for AI Literacy?

    Ray is the Chief Data and Analytics Officer at Valhalla AI Solutions. Prior to that, he held senior leadership roles at the Advertising Research Foundation, at the Institute for Experiential AI, and at comScore. In this episode, Ray discusses challenges associates with promoting meaningful AI literacy in business, starting with fundamental questions, like what is “AI literacy” exactly? (Is it merely the ability to use AI tools, or is a deeper understanding of the science behind those tools required?) He also discusses the reverse problem, where recent graduates from AI/ML programs lack sufficient domain knowledge to be full partners with key leaders at the companies that hire them. The end result is that many companies struggle to have meaningful dialog between their domain experts and their experts in AI and ML. On a more optimistic note, Ray describes a variety of initiatives in Canada, Germany and in select states in the US, that show promise for deepening the domain understanding of data scientists, while also empowering domain experts with a better understanding of data science.

    24 min

  6. OCT 26

    Ivan Pinto: A Year of AI Testing in Software Dev

    Ivan is an Associate VP of Delivery at Robosoft Technologies. His team does application development, engineering and QA for US clients, including web (HTML, CSS), mobile (Android, iOS, Samsung, LG) and streaming, including Roku TV. In this episode, Ivan shares what he learned in his experiments over the past year using Gen AI to improve the efficiency and quality of code produced by his 300-member team, including results that he describes as “amazing,” with time savings of 40-50% in writing code. The technologies he discusses include GitHub Copilot, Amazon CodeWhisperer, Tabenine, Codeium, TestGrid and LambdaTest. And he describes how he chose between those, and also which ones he has his eye on for the future. Tests were done in various parts of the development lifecycle, including boilerplate code for new projects, bug fixing, unit testing, integration QA, and migrating from one language to another. Since not all of these situations benefited equally from AI-powered tools, Ivan describes what worked well, and where there are gaps that need further development work by vendors.

    24 min

  7. OCT 18

    Sam Marks: Big Data, Big Bad Bruins

    Sam is the Director of Business Strategy, Solutions & Analytics at the Boston Bruins & TD Garden. Prior to that, he directed strategy and analytics for the Arizona Coyotes, and at VaynerMedia. In this episode, Sam sheds light on the world of analytics and business strategy for sports teams, including the differences in strategy and focus for teams vs at the league level. He also talks about the size and structure of analytics teams in the sports world, as compared to equivalent teams in consumer packaged goods, for example. And he describes how he uses AI and analytics conferences as part of his overall approach to team development.

    21 min

  8. OCT 12

    Celia Wanderley: AI Innovator of the Year

    Celia is the Chief Innovation Officer at Bits In Glass (BIG), a top Canadian IT consulting firm. Prior to that, she held senior leadership roles at AltaML and at Deloitte Canada. Celia was recognized as the AI Innovator of the Year, by Women in AI. In this episode, Celia shares insights from trends she’s seen in her recent work involving intelligent automation of business processes at scale. A key topic is the idea of embedding AI agents into multiple steps within business processes, such as contract analysis or banking regulatory change management, in order to achieve business results that would probably not be achievable with a one-shot AI solution. She also describes successful efforts at transforming front-line user experience of field workers, replacing clumsy gadgets with voice-activated workflows. And she discusses critical success factors for taking AI projects into full production, confirming that AI and ML solutions frequently work quite well in a completely different context or industry from the one where they were originally created. She concludes by making a case for a blended approach to resourcing AI projects – one that involves in-house teams, third-party solutions, and external partners.

    31 min
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About

Hosted by Jim Griffin, this show features the researchers and leaders who are building the future of AI in their work today. Join us for thought-provoking conversations about the evolving world of artificial intelligence.

Information

  • Creator
    Jim Griffin
  • Years Active
    2K
  • Episodes
    15
  • Rating
    Clean
  • Copyright
    © 2024
  • Show Website
    AI Master Group

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