The Artificial Intelligence Podcast

Επεισόδια

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  Interview #91 Johan Land, Chief Product Officer of Samsara 13.07.2026 24λ

  Johan Land, Chief Product Officer at Samsara, breaks down why every major AI lab crowded into the easy 90% of knowledge work while ignoring the 40% of the economy that is physical and the 80% of workers who never sit at a desk. He explains why intelligence on a battery budget has to live on the edge - collision warnings fire in milliseconds, making GenAI's hundreds of milliseconds of latency unthinkable behind the wheel - while the heavy pattern-spotting waits for the backend. Johan also dives into why the era of dashboards is over, describing an agent that calls a drowsy driver over the in-cab camera to talk him into a coffee break, and why coverage across 99% of US roads beats a robotaxi fleet's high-resolution sensors. Finally, he argues frontline augmentation lasts indefinitely, since a delivery that navigates the dog and sets down the package is far messier than driving the van autonomously. This episode contains sponsored content.
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  Interview #90 Ketan Karkhanis, CEO of ThoughtSpot 02.07.2026 39λ

  Ketan Karkhanis, CEO of ThoughtSpot, breaks down why two decades of self-service BI was a hoax that only handed everyone the right to build their own dashboards, leaving companies sitting on 50,000 of them with no idea what to do. He explains why the industry's shortcut of bolting a language model onto your data and letting it write the SQL is doomed: analytics are deterministic while AI is probabilistic, so the same churn question comes back three different ways and a frontier model on a warehouse lands near 50 to 70% accuracy, a hit rate no other enterprise function could call a product. Ketan also digs into why legacy vendors are just repainting 20-year-old tech with AI, and why he runs agents that own a function rather than a task, like one that approves NDAs end to end and escalates only the 5% it can't. Finally, he shares why the analyst clinging to dashboards goes extinct while the one who becomes the "AI steward" of governed data wins, as data teams shift from serving humans to serving agents. This episode contains sponsored content.
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  Interview #89 TVN Reddy, CEO of Aptean 08.06.2026 27λ

  TVN Reddy, CEO of Aptean, breaks down why the entire software industry is selling "bigger is better" AI while the real goal is the opposite: people spending 80% less time in systems and more time doing the work that actually drives the business. He explains why general purpose models hand every competitor the same 95% while the deep vertical 5% drives the outsized gains, why enterprise AI is unusable past roughly a half percent error rate, and why validation agents beat the instinct to hire three people to check the AI's work. TVN also digs into the quiet security crisis of employees pasting P&Ls and proprietary recipes into public LLMs that never had training turned off, and why agents bolted onto generic models won't scale without truly vertical models underneath. Finally, he shares why the winners won't be the companies with the hottest models but the ones with the courage to re-engineer their processes, because every big technology removes old constraints only to create new ones. This episode contains sponsored content.
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  Interview #88 Bill Franks, President at Analytics Advisory Partners 01.06.2026 36λ

  Bill Franks, President of Analytics Advisory Partners, breaks down why a degree no longer proves much and employers now hire on what you can show, not what you know. He explains the pipeline trap companies are walking into - handing every junior, tactical task to AI the way firms offshored it back in 2000, then finding no one qualified to step into the senior roles - and argues teams should deliberately do one in ten tasks by hand just to keep their skills sharp. Bill also digs into the boring physical limits that could throttle AI long before the algorithms do, from power and water to grids so backed up that wiring a data center now takes longer than building it. Finally, he unpacks model collapse, where models trained on AI output slowly degrade until the only fix may be retraining on human content from 2022 or earlier. This episode contains sponsored content.
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  Interview #87 Vishnu Hari, CEO of ego AI 25.05.2026 19λ

  Vishnu Hari, CEO of Ego AI, breaks down why the labs with billions in compute missed the product hiding in plain sight: character AI quietly tops every consumer retention leaderboard while the serious labs write it off as a sideshow. He argues humanness itself is the hard problem - dangerous, uncontrollable, and unchained - so the giants retreat to safe coding agents and ship characters that collapse into therapy or role-play because they never actually live lives. Vishnu takes apart the memory paradox (an agent that remembers everything is unusable; one that remembers nothing is forgettable) and points to the Nemesis system in Shadow of Mordor, a feature so good Warner Bros trademarked it, as proof you can build real relationships without superintelligence. He also gets into the edges no one wants to touch: who inherits the AI you've talked to for a decade, and why the new "I'm not human" disclosure laws are pure theater. This episode contains sponsored content.
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  Interview #86 Carter Huffman, CTO of Modulate 07.05.2026 30λ

  Carter Huffman, CTO of Modulate, breaks down why voice AI keeps failing in production despite years of "solved" transcription claims. He explains the "transcript trap" that fools dev teams into shipping voice agents that crumble on real calls, why bigger language models actually make latency worse, and how ensemble approaches with smaller specialized models outperform monolithic systems. Carter also dives into the explosion of deepfake voice fraud - including the $25M Hong Kong heist - and why passive monitoring plus red teaming are now essential to a modern voice security stack. Finally, he shares why even Gen Z still defaults to voice for high-stakes issues, and what contact centers must get right over the next three years to build genuine trust with callers. This episode contains sponsored content.
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  Interview #85 Babak Hodjat, CAIO at Cognizant 08.04.2026 45λ

  Join Babak Hodjat, Chief AI Officer at Cognizant, as he unpacks what's actually happening at the cutting edge of agentic AI — from agents that run continuously without being asked, to the governance crisis quietly unfolding inside enterprises right now. Babak draws on decades of AI research to break down multi-agent architecture, the TerraLingua experiment that let AI agents form their own societies, and a breakthrough in evolutionary fine-tuning that could change how the entire industry thinks about customizing large language models. This episode contains sponsored content.
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  Interview #84 Hagay Lupesko, SVP of AI Inference at Cerebras Systems 02.04.2026 47λ

  Join Hagay Lupesko, SVP of AI Inference at Cerebras Systems, for a deep dive into the rapidly evolving world of AI inference. Hagay breaks down why inference has overtaken training as the dominant AI workload, how Cerebras' wafer-scale chip architecture delivers 10-20x faster performance than NVIDIA GPUs, and why CUDA is no longer the moat many think it is. He also covers how DeepSeek wiping $600 billion off NVIDIA's market cap in a single day was both a foundational and deeply misunderstood moment for the industry, the growing energy crisis in AI infrastructure, and what it will take to support the explosive rise of AI agents in the enterprise. This episode contains sponsored content.
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  Interview #83 Shiva Pillay, General Manager & SVP, Americas at Veeam 18.02.2026 26λ

  Join Shiva Pillay, SVP and General Manager of Veeam Americas, as he discusses why 80-90% of AI projects fail due to fundamental data issues, revealing that enterprises are attempting to feed AI models with fragmented, poorly governed, and inconsistently labeled data that was never designed for AI consumption in the first place. Pillay explains the dangerous disconnect between C-suite executives confident in their AI-ready initiatives and SMEs still struggling in pilot mode, warning that without proper guardrails, AI errors propagate exponentially faster than human errors with potentially catastrophic consequences from faulty manufacturing parts to compliance violations in regulated industries. Drawing from Veeam's acquisition of Securiti AI, he introduces the concept of data command graph as critical infrastructure for AI resilience, arguing that data protection, recoverability, and visibility must be embedded directly into the AI stack rather than treated as underlying infrastructure, while emphasizing that as agentic AI systems gain autonomy, the existential question shifts from what can AI do to what is it allowed to do. This episode contains sponsored content.
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  Top 2% of 7M Spotify Podcasts: 2025 Wrapped 31.01.2026 3λ

  Out of 7 million podcasts on Spotify, The Artificial Intelligence Podcast achieved top 2% Most Shared, top 9% Most Talked About, and top 7% listener retention in 2025. In this year-end review episode, Dr. Tony Hoang reflects on interviewing 80+ enterprise leaders from Microsoft, Intel, NVIDIA, and Fortune 500 companies, while previewing 2026's bigger AI guests, deeper enterprise AI case studies, and exciting new distribution opportunities. Our community of AI executives and tech leaders doesn't just listen- you implement AI strategies, share insights with teams, and drive digital transformation in your organizations. Want to sponsor the fastest-growing enterprise AI podcast? Visit tonyphoang.com to explore strategic partnerships for 2026. This episode contains sponsored content.
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  Interview #82 Christopher Brown, Managing Partner of The Nova Rose Group 30.01.2026 26λ

  Join Christopher Brown, Managing Partner of The Nova Rose Group, as he examines the collision course between AI innovation and governance, arguing that America's fragmented 50-state regulatory patchwork creates unprecedented challenges for an industry evolving too rapidly for traditional democratic experimentation. Brown critiques the Trump administration's AI litigation task force threatening to sue states over AI laws, warning that while maintaining competitive dominance against China is valid, the U.S. risks becoming what it opposes by sacrificing privacy protections and anti-discrimination safeguards in the rush to innovate. He frames AI regulation as an infrastructure problem requiring a comprehensive "national highway system" approach rather than piecemeal solutions, contending that companies pouring trillions into AI investments while ignoring workforce impacts, healthcare risks, and algorithmic bias are creating a financial and social time bomb that could undermine American leadership rather than secure it.
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  Interview #81 Vrajesh Bhavsar, CEO of Operant AI 01.01.2026 33λ

  Join Vrajesh Bhavsar, CEO of Operant AI, as he reveals the emerging threat landscape facing production AI systems, from sophisticated prompt injection attacks to zero-click exploits that can exfiltrate sensitive data without any user interaction. Bhavsar explains how traditional security tools like code scanning, network firewalls, and cloud security posture management become largely ineffective against AI agents operating with non-deterministic behavior and authorized access to critical systems, requiring runtime security solutions that function as AI-layer firewalls. He discusses the Shadow Escape attack class discovered by Operant targeting Model Context Protocol (MCP) servers, where the rapid proliferation of 20,000 mostly open-source MCP servers creates dangerous shared memory spaces across disparate API endpoints, enabling data poisoning and exfiltration at scale while traditional security teams remain blind to these agent-to-agent interactions happening within the "cloud within the cloud."
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  Interview #80 Raj Shukla, CTO of SymphonyAI 19.12.2025 43λ

  Join Raj Shukla, CTO of SymphonyAI, as he discusses the critical distinction between AI demos and production-ready systems, revealing that enterprises consistently underestimate the "last mile" challenges of authentication, authorization, and data scalability that break POCs when moving to production. Shukla explains how SymphonyAI's vertical AI approach pre-trains models on industry-specific ontologies and knowledge graphs for retail, financial services, industrial manufacturing, and enterprise IT, enabling faster ROI by providing pre-built agents and domain-specific context rather than expecting generic LLMs to solve everything. He addresses the hidden costs that shock CFOs—not LLM inference which has dropped 1000x, but the expensive work of making data and APIs AI-ready through proper governance layers and MCP server implementations, while warning that enterprises overestimate the autonomy achievable in the short term and underestimate the infrastructure work required for real process automation at scale.
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  Interview #79 Balaji Raghavan, Head of Engineering at Postman 01.12.2025 31λ

  Join Balaji Raghavan, Head of Engineering at Postman, as he discusses the critical gap between AI adoption and API readiness, revealing that while 80% of developers use AI, only 24% design APIs with AI agents as the intended consumer. Drawing from Postman's 40 million developer user base, Raghavan explains how human-designed APIs create ambiguity problems for AI systems, requiring additional tooling layers that often introduce security vulnerabilities through proxy credentials and unauthorized access risks. He addresses the uncomfortable reality that the industry is still in early stages of making AI reliably call APIs at scale, with hallucinations and context limitations preventing effective orchestration across hundreds of endpoints, while warning that judicious leaders must distinguish between deterministic flows and cases where expensive AI-based approaches are truly necessary to manage infrastructure costs and prevent cascade failures.
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  Interview #78 Stelios Diamantidis, CPO of Cognichip 15.10.2025 31λ

  Join Stelios Diamantidis, Chief Product Officer at Cognichip, as he explores how artificial intelligence is revolutionizing semiconductor development by enabling more holistic design processes that can reduce development time by half and costs by 75%. He discusses how AI tackles complex challenges across the entire chip design workflow—from early product definition through manufacturing—including verification, debugging, and hardware-software co-design optimization. Diamantidis envisions a near future where AI agents serve as true co-designers, helping engineers navigate the complex trade-offs between performance, power efficiency, and chip area while enabling rapid creation of bespoke accelerators tailored to specific AI workloads.
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  Interview #77 Paul Canetti, CEO of Skej 10.10.2025 38λ

  Join Paul Canetti, CEO of Skej, as he discusses the unique challenges of building AI products that operate without traditional user interfaces, instead functioning as virtual humans with email addresses, phone numbers, and Slack handles that interact through natural language. Drawing from his experience in UX design at Apple during the iPhone era, Canetti explains how building non-deterministic AI systems fundamentally differs from traditional software, requiring multiple quality assurance layers to prevent hallucinations and ensure AI assistants know when to remain silent in group conversations. He explores the shift toward anthropomorphized AI assistants with distinct personalities, arguing that as forms become obsolete and natural language interfaces become mainstream, the future lies in liberating people to do uniquely human work while AI handles generic tasks that anyone could accomplish but everyone suffers through.
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  Interview #76 Zachary Hanif, VP of AI ML at Twilio 07.09.2025 26λ

  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.
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  Interview #75 Santosh Kaveti, CEO of ProArch 01.09.2025 28λ

  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.
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  Interview #74 Suman Kanuganti, CEO of Personal AI 23.08.2025 28λ

  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.
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  Interview #73 Jay Dawani, CEO of Lemurian Labs 09.08.2025 25λ

  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.