The Artificial Intelligence Podcast

Dr. Tony Hoang

Interviews and conversations with thought leaders in Artificial Intelligence, Machine Learning and Data Science

  1. 7 SEP

    Interview #76 Zachary Hanif, VP of AI ML at Twilio

    Join Zachary Hanif, VP of Data and AI at Twilio, as he discusses the fundamental differences between building AI systems in regulated financial services versus communication platforms, drawing from his experience at Capital One to implement rigorous model governance frameworks that reduce maintenance costs while accelerating development timelines. Hanif addresses the critical balance between explainable AI and high-performing black box models, emphasizing that organizations must identify where their use cases fall on the explainability spectrum rather than applying blanket requirements. He explores privacy-by-design principles for real-time AI systems, the challenge of moving from proof-of-concept to production (with 80% of AI pilots failing), and provides a practical framework for successful AI implementation that includes clear objective criteria, close collaboration between technical teams and domain experts, and properly tempered expectations for experimental development timelines.

    26 min

  2. 1 SEP

    Interview #75 Santosh Kaveti, CEO of ProArch

    Join Santosh Kaveti, CEO of ProArch, as he addresses the critical gap between AI ambition and execution in enterprise environments, where despite widespread C-suite commitment, only a quarter of organizations achieve meaningful AI implementation. Kaveti outlines his four-pillar framework for AI operationalization, emphasizing that AI adoption is fundamentally a people and culture problem rather than a technology issue, with 63% of companies lacking basic AI governance policies. He discusses the growing challenges of shadow AI usage, the convergence of IT and operational technology creating new security vulnerabilities in critical infrastructure, and how organizations can build compliance frameworks that won't become obsolete as AI regulations continue to evolve rapidly.

    28 min

  3. 23 AUG

    Interview #74 Suman Kanuganti, CEO of Personal AI

    Join Suman Kanuganti, CEO of Personal AI, as he discusses the shift away from the one-size-fits-all approach of large language models toward specialized personal language models that capture individual decision-making patterns and expertise. Kanuganti explains how artificial personal intelligence differs from artificial general intelligence, focusing on creating AI personas that can run efficiently on edge devices rather than requiring massive cloud infrastructure while maintaining privacy-by-design architecture. He examines the future of distributed AI systems and how smaller, specialized models can deliver superior performance for specific use cases while addressing the fundamental scalability and cost challenges facing the current AI industry dominated by power-hungry large language models.

    29 min

  4. 9 AUG

    Interview #73 Jay Dawani, CEO of Lemurian Labs

    Join Jay Dawani, CEO of Lemurian Labs, as he discusses the critical infrastructure challenges facing AI development and his company's efforts to rebuild the AI software stack from the ground up. Drawing from his experience as a former NASA AI advisor working on Mars Rover navigation and exoplanet research, Dawani explains how current AI systems are plagued by massive inefficiencies, with some data centers operating at only 10-15% utilization despite consuming enormous amounts of energy. The conversation explores how the industry must shift from kernel-based programming models designed for single GPUs to dynamic runtime systems that can efficiently manage communication and memory across hundreds of thousands of processors, ultimately making advanced AI more accessible and sustainable.

    26 min

  5. 21 JUL

    Interview #72 Richard White, CEO of Fathom

    Join Richard White, CEO of Fathom, as he discusses how AI is transforming workplace productivity through intelligent meeting transcription and note-taking solutions. White explains how modern AI can now write better notes than most humans within 30 seconds of a meeting ending, while also enabling companies to capture and disseminate organizational knowledge more effectively by analyzing patterns across thousands of hours of meetings. The conversation explores the evolution from basic transcription services to sophisticated AI workflows that can generate action items, update CRMs, and provide executives with real-time alerts about important developments across their teams, ultimately reshaping how organizations communicate and collaborate in an AI-first workplace.

    27 min

  6. 17 JUL

    Interview #71 Nadia Harhen, General Manager of AI Simulation at SandboxAQ

    Join Nadia Harhen, General Manager of AI Simulation at SandboxAQ, and Jordan Crivelli-Decker from the Biosim team as they discuss how Large Quantitative Models (LQMs) are revolutionizing drug discovery and materials science by generating synthetic data through physics-based computational chemistry rather than just predicting outcomes like traditional language models. They explain how this approach accelerates drug development timelines, reduces animal testing needs, and enables breakthrough solutions for complex molecular problems that conventional software cannot handle, including work with Nobel laureate Dr. Stanley Prusiner that moved from research to clinical trials in just 18 months. The conversation explores how combining quantum mechanics principles with machine learning creates novel molecular IP across industries from pharmaceuticals to defense applications, bridging the gap between AI capabilities and practical scientific breakthroughs.

    29 min

  7. 14 JUL

    Interview #70 Debo Dutta, Chief AI Officer at Nutanix

    Debo Dutta, Chief AI Officer at Nutanix, discusses the critical challenges enterprises face when scaling generative AI beyond proof-of-concepts, identifying skills gaps, unclear implementation pathways, and data governance concerns as primary barriers. He emphasizes that successful AI transformation requires a holistic approach addressing people, processes, and technology, with particular focus on data cleaning and creating "gold standard" datasets as foundational competitive advantages. Looking ahead, Dutta predicts the emergence of AI agents operating with human oversight rather than fully autonomous systems, while highlighting that clean, private enterprise data will become the primary moat as AI models become increasingly commoditized.

    28 min

  8. 3 JUL

    Interview #69 Michael Wu, Chief AI Scientist at PROS

    Dr. Michael Wu, Chief AI Scientist at PROS, discusses his transition from computational neuroscience research to applied AI in industry, emphasizing how his perspective without domain-specific baggage has enabled innovative problem-solving approaches. He explores the evolving landscape of AI agents and tools, highlighting the importance of Model Control Protocol (MCP) as a bridge between passive language models and actionable AI systems that can interact with existing enterprise tools. Wu emphasizes the need for organizations to create fail-safe environments that encourage AI experimentation while maintaining security, and advocates for balancing innovation speed with responsible development practices that prioritize safety, privacy, and legal compliance from the outset.

    36 min
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Interviews and conversations with thought leaders in Artificial Intelligence, Machine Learning and Data Science

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