The Artificial Intelligence Podcast

Hao Yang, VP and Head of AI at Splunk, breaks down why sampling an AI system's output cannot earn trust: a fraction of ten thousand probabilistic calls will be wrong, and a spot check is unlikely to find them. He explains why a small model can grade a frontier model reliably inside a narrow context but not outside one, and why prompt injection follows from the architecture rather than being a bug, since following instructions is how these systems work. Hao also digs into why time series is still not a first class citizen in frontier models even as multimodal training reaches vision and audio, and why he rejects routing prompts to the cheapest model, arguing cost is meaningless without value. Finally, he argues against the single super agent, which by design holds access to everything it might ever need, and for guided autonomy, where an agent asks before first reaching for a tool and the user grants it once, for the session, or never. Be a guest on the show: https://tonyphoang.com/guest Live interviews at your conference: https://tonyphoang.com/live Music and credits: https://tonyphoang.com/credits

Mangesh Pimpalkhare, SVP and GM of Splunk Platform at Cisco, breaks down why agentic AI generates more telemetry than the systems it monitors, and why nobody can yet say when observing AI costs more than running it. He explains the decade spent preaching centralized data was always partial, since machine data never sat in one system, and that what broke was volume rather than architecture, pushing a whole category to abandon the ingestion pricing it ran on for 15 years. Mangesh also digs into why an agent acting on a bad signal is usually a context failure, not a data failure, since a model trained on everything still lacks up-to-the-second context, and why autonomy arrives on a sliding scale against governance as trust is earned. Finally, he argues control, not data, is the moat, since customers own their data and fragmentation only grows, leaving the advantage with whoever supplies the guardrails that stop agents doing the wrong thing. Be a guest on the show: https://tonyphoang.com/guest Live interviews at your conference: https://tonyphoang.com/live Music and credits: https://tonyphoang.com/credits

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. Be a guest on the show: https://tonyphoang.com/guest Live interviews at your conference: https://tonyphoang.com/live

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. Be a guest on the show: https://tonyphoang.com/guest Live interviews at your conference: https://tonyphoang.com/live

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. Be a guest on the show: https://tonyphoang.com/guest Live interviews at your conference: https://tonyphoang.com/live

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. Be a guest on the show: https://tonyphoang.com/guest Live interviews at your conference: https://tonyphoang.com/live

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. Be a guest on the show: https://tonyphoang.com/guest Live interviews at your conference: https://tonyphoang.com/live

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. Be a guest on the show: https://tonyphoang.com/guest Live interviews at your conference: https://tonyphoang.com/live

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. Be a guest on the show: https://tonyphoang.com/guest Live interviews at your conference: https://tonyphoang.com/live

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. Be a guest on the show: https://tonyphoang.com/guest Live interviews at your conference: https://tonyphoang.com/live

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. Be a guest on the show: https://tonyphoang.com/guest Live interviews at your conference: https://tonyphoang.com/live

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. Be a guest on the show: https://tonyphoang.com/guest Live interviews at your conference: https://tonyphoang.com/live

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.

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."

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.

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.

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.

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.

Join Brandon Barbello, COO, and Nick Gillian, Head of AI at Archetype AI, as they discuss Newton, a multimodal foundation model that processes sensor data to power applications in home security, industrial automation, and more. Newton enables resource-constrained teams to build AI solutions effortlessly by leveraging existing sensors and historical data for smarter, adaptive systems. They explore the rise of physical AI, where foundation models integrate diverse sensors to enhance real-world decision-making across industries.

Join Hikari Senju, CEO of Omneky, as he discusses the evolution of advertising from ancient Roman signs to today's AI-driven personalized content generation. Senju explains how Omneky is revolutionizing the advertising industry by using AI to generate and optimize creative content at scale, while also addressing key challenges around copyright, enterprise adoption, and liability in the emerging AI advertising landscape. Looking toward the future of advertising, Senju emphasizes that while AI is creating abundance in content generation, human attention remains the scarcest and most valuable commodity in the modern marketing landscape.

Join Nikolaos Vasiloglou, VP of Research ML at RelationalAI, as he traces the evolution of AI from early neural networks through kernel methods, gradient boosted trees, and the deep learning revolution that transformed the field. He shares valuable insights on addressing hallucinations in AI systems through fact-checking, human annotation, and offline curation, while emphasizing the growing importance of Graph RAG (Retrieval-Augmented Generation) as a practical solution that bridges neural networks' generalization capabilities with symbolic AI's accuracy and speed. He explores agentic systems, both macro and micro approaches, and offers his perspective on recent developments like DeepSeek's R1 model, suggesting that while efficiency improvements are inevitable, they don't necessarily threaten established players in the field.

Join Aaron Painter, CEO of Nametag, as he shares his journey from a 14-year Microsoft career spanning multiple countries to founding a company focused on solving modern identity verification challenges after witnessing widespread identity theft during the pandemic. Painter discusses how fraud has evolved from simple check scams to sophisticated digital impersonation using deepfakes, particularly highlighting the surge in remote work-related security threats and the rise of elaborate payroll scams targeting major corporations. His company, Nametag, tackles these challenges through DeepFake Defense technology, which utilizes mobile platforms' security features to prevent injection attacks and verify authentic identities, while emphasizing the continued importance of Multi-Factor Authentication and maintaining healthy skepticism in digital interactions.

Join Will Lu, CTO of Orby AI, as he shares insights from his journey from Google Cloud, where he helped develop Vertex AI and Document AI, to founding Orby AI, an enterprise platform focused on building AI agents for complex business processes. Lu discusses the evolution of AI accessibility, from the early days of deep learning to today's foundation models, and explains how Orby's Generative Process Automation (GPA) platform uses an observe-and-learn approach to help enterprises automate repetitive tasks with high accuracy. Lu shares his vision for the future of enterprise AI, including the potential of human-computer interaction data and Orby's open-source release of their ActIO model on HuggingFace.

Join Kathleen Walch, Global Head and General Manager of Project Management Institute (PMI), as she discusses the evolution of AI project management and PMI's recent acquisition of Cognilytica, her AI research and advisory firm. She shares insights on PMI's CPMAI methodology, which helps organizations manage AI projects through six phases and seven distinct patterns of AI implementation. Looking at AI adoption challenges, particularly with generative AI and chatbots, she emphasizes starting small and iterating often. Walch addresses global AI regulations, emerging trends like agentic AI, and PMI's initiatives including their AI assistant Infinity.

Join Heidi Golledge, CEO of Jobot, as she shares her entrepreneurial journey from founding CyberCoders (which sold for over $100M) to launching Jobot, an AI-powered recruitment platform that serves 10 million users and 15,000 open jobs. She discusses how AI is transforming the recruitment landscape through tools like Jax (Jobot Automated Experience) while emphasizing the continued importance of human elements like attitude and cultural fit in hiring. Golledge provides insights on the future of work, suggesting that AI will become as fundamental as electricity in every industry while advising job seekers to focus on building personal brands, embracing AI tools, and aligning career choices with their desired lifestyle rather than just pursuing high salaries.

Join Will Hu, CTO of Flagler Health, as he discusses the evolution of AI in healthcare to today's advanced AI-powered services that can handle everything from appointment scheduling to clinical diagnostics. Hu emphasizes that while previous decades focused on point solutions, current healthcare AI is shifting toward comprehensive service-oriented approaches that integrate with existing workflows, though he notes that policy changes around payment models and reimbursement are crucial for wider AI adoption. Looking to the future, Hu is excited about the potential of combining ambient clinical data capture with patient interactions outside the clinic to create truly holistic care, while maintaining that AI will augment rather than replace healthcare workers, creating more jobs in the field.