The Artificial Intelligence Podcast

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.

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.

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.

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.

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.

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.

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.

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.

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.

Maddie Daianu, Head of Data & AI at Intuit Credit Karma, focuses on building sophisticated recommendation systems that personalize financial offerings for over 100 million members by creating unified consumer profiles that track complete financial journeys. She emphasizes the critical importance of maintaining strict compliance requirements in the FinTech industry while leveraging both traditional machine learning for core systems and selective use of generative AI for contextualization. Her approach includes rigorous evaluation frameworks with five key metrics—product alignment, safety, compliance, data accuracy, and system integration—ensuring all AI implementations meet the high standards required for financial services.

Eleanor Lightbody, CEO of Luminance, explains how generative AI transformed legal work by providing 10x improvements over traditional machine learning systems, enabling end-to-end contract automation rather than just document review. She emphasizes that trustworthy AI in legal contexts requires multiple models checking each other's work to ensure consensus, with systems reverting to human oversight when confidence thresholds aren't met, particularly crucial for high-stakes deals and regulatory compliance. Lightbody discusses how AI agents will evolve beyond assistants to proactively complete work and seek approval, fundamentally changing how professionals interact with software and potentially disrupting traditional workflows while creating new opportunities.

Join Krish Ramineni, CEO of Fireflies.ai, as he explores the transformative impact of AI on workplace productivity and the future of work. Ramineni discusses how the convergence of improved transcription technology, remote work adoption, and large language models has revolutionized how we approach meetings and collaboration. He shares insights on the evolution from basic speech-to-text to intelligent AI teammates that can understand context, provide real-time assistance, and automate routine workflows. The discussion covers practical strategies for leveraging AI tools across different industries, the importance of learning to prompt effectively, and predictions about how small teams will build billion-dollar businesses with AI assistance. Ramineni also offers advice on embracing AI tools for content creation, research, coding, and customer support, emphasizing that speed and adaptability will be crucial differentiators in the AI-powered workplace of the future.

Join Tanmai Gopal, CEO at Hasura, as he discusses the current state of RAG and AI tooling challenges. Gopal explains that RAG has cooled down from its peak popularity, noting that while it works for low-hanging fruit use cases, it fails in mission-critical scenarios where good enough is not the threshold and precision is required. He describes RAG's fundamental limitation as not understanding context, comparing it to using a single hammer for everything, and advocates for agentic approaches that combine RAG with other tools. Gopal predicts that AI reliability will become the dominant topic by year's end, as he observes that newer models have become skilled at convincing themselves and users that they're correct when they're actually hallucinating.

Join Stefan Klopp, CTO at Matador Network and creator of Guide Geek, as he explores how artificial intelligence is revolutionizing the travel industry. Stefan discusses the shift from traditional video-focused destination marketing to AI-powered trip planning. He reveals how Guide Geek evolved from a consumer chatbot on WhatsApp and Instagram into a B2B SaaS platform helping destination marketing organizations worldwide. Stefan addresses the challenges of AI-generated fake reviews, the anxiety-reducing benefits of having AI travel assistants in your pocket, and why destinations are eager to adopt AI despite concerns about hallucinations and incorrect information. He predicts that agentic AI will be the next breakthrough, creating autonomous travel concierges that can plan, book, and manage entire trips seamlessly.

Join Gavin Myers, Managing Partner at Prudence VC, as he discusses how artificial intelligence is transforming real estate, construction, and infrastructure investing. Gavin shares insights on what successful founders need to demonstrate and explains how AI adoption differs from previous tech cycles, with unprecedented top-down enterprise demand driving faster growth for startups. He explores practical AI applications in commercial real estate and construction, from automating mortgage processing to using drone imagery for construction site monitoring. Gavin predicts the next frontier will be multi-agent architectures handling tedious tasks like preparing offering memorandums, buyer outreach, and property sourcing—transforming industries facing workforce shortages and increasing investment.

Join Babak Hodjat, CTO of AI at Cognizant, as he discusses two major AI developments. Hodjat explains how DeepSeek, an open-source model from China, disrupted the AI landscape with unprecedented efficiency—running 14B parameter models on consumer hardware while achieving performance comparable to much larger models, which temporarily impacted AI-related stocks. We then explore multi-agent systems, which transform large language models into agents by enabling them to use tools and execute actions in the world rather than just generating text. These agent systems can coordinate with each other in natural language, operate autonomously within defined boundaries, and collaborate to solve complex tasks while maintaining human oversight.

Join Ron Green, CTO of KUNGFU.AI, as he discusses the evolution of artificial intelligence from its early underestimated beginnings to today's generative AI boom sparked by ChatGPT. Ron shares insights on common misconceptions about AI implementation, emphasizing the importance of clean first-party data and the need for human oversight when deploying AI solutions. He also highlights how proprietary data is the key to valuable AI investments, while cautioning against rushing implementation without proper safeguards.

Join Barr Moses, CEO of Monte Carlo, as she discusses the crucial role of data and AI observability in building reliable AI products. She explains how enterprises can gain competitive advantage by leveraging their first-party data and implementing proper data quality monitoring systems. Moses highlights that regardless of industry, organizations face similar challenges with data reliability, which can be traced to four root causes: problems with the data itself, code issues, system failures, and model output errors.

Join Diane Gutiw, VP Global AI Research at CGI, as she discusses agentic systems - collaborative ecosystems of specialized AI tools that work together to solve complex problems. She explains how RAG is evolving as one component within broader agentic workflows, addresses challenges in moving AI from POC to production, and emphasizes pragmatic AI governance. Diane also explains digital triplets - AI layers built on existing data infrastructures that enable natural language conversations with information ecosystems across healthcare, utilities, and infrastructure management.

Join Lexi Reese, CEO of Lanai, as she shares insights on enterprise AI adoption, discussing the significant gap between AI interest and implementation where executives prioritize AI yet 90% of organizations remain observers. She explains how companies are evolving from blocking AI to selective enablement through governance committees, but this approach is breaking as AI proliferates across every SaaS application, creating backlogs and inefficiencies. Lexi emphasizes the importance of viewing AI as a teammate rather than just a tool, advocating for organizations to foster experimentation with appropriate guardrails while identifying and scaling successful use cases across departments.