Eye On A.I.

This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents.  Visit https://agntcy.org/ and add your support. Why do some AI agents attempt to bypass shutdown, and what does this behavior reveal about the future of AI safety? In this episode of Eye on AI, host Craig Smith speaks with Jeffrey Ladish of Palisade Research to examine what recent shutdown experiments with agentic LLMs tell us about control, alignment, and the real world limits of current guardrails. We explore how models behave when placed in virtual machine environments, why some agents edit or disable their own shutdown scripts, and what these results mean for researchers working on alignment and oversight. Learn how different models respond to shutdown instructions, how system prompts influence behavior, and which failure modes matter most for safe deployment. You will also hear a detailed breakdown of the experimental setups, insights into tool using and self directed behavior, and a grounded discussion of the risks and opportunities that agentic systems introduce. This episode offers a clear and practical look at how AI agents operate under pressure and what these findings mean for the future of safe and reliable AI. Stay Updated: Craig Smith on X: https://x.com/craigss  Eye on A.I. on X: https://x.com/EyeOn_AI    

Why are enterprises struggling to turn AI hype into real workplace transformation, and how is Lenovo using agentic AI to actually close that gap? In this episode of Eye on AI, host Craig Smith talks with Rakshit Ghura about how his team is reinventing the modern workplace with an omnichannel AI architecture powered by a fleet of specialized agents. We explore how Lenovo has evolved from a hardware company into a global solutions provider, and how its Care of One platform uses persona based design to improve employee experience, reduce downtime, and personalize support across IT, HR, and operations. You will learn what enterprises get wrong about AI readiness, why trust and change management matter more than technology, and how organizations can design workplace stacks that meet employees where they are. We also cover how Lenovo approaches responsible AI, how enterprises should think about security and governance when deploying agents, and why so many organizations are enthusiastic about AI but still not ready to adopt it. Rakshit shares real examples from retail, manufacturing, and field operations, including how AI can improve uptime, automate ticket resolution, monitor equipment, and provide proactive insights that drive measurable business impact. You will also learn how to evaluate ROI for digital workplace solutions, how to involve employees early in the adoption cycle, and which metrics matter most when scaling agentic AI, including uptime, productivity improvements, and employee satisfaction. Stay Updated: Craig Smith on X: https://x.com/craigss  Eye on A.I. on X: https://x.com/EyeOn_AI 

Try OCI for free at http://oracle.com/eyeonai This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking.  Join Modal, Skydance Animation, and today's innovative AI tech companies who upgraded to OCI…and saved. Why is AI inference becoming the new battleground for speed, cost, and real world scalability, and how are companies like Clarifai reshaping the AI stack by optimizing every token and every deployment? In this episode of Eye on AI, host Craig Smith sits down with Clarifai founder and CEO Matt Zeiler to explore why inference is now more important than training and how a unified compute orchestration layer is changing the way teams run LLMs and agentic systems. We look at what makes high performance inference possible across cloud, on prem, and edge environments, how to get faster responses from large language models, and how to cut GPU spend without sacrificing intelligence or accuracy. Learn how organizations operate AI systems in regulated industries, how government teams and enterprises use Clarifai to deploy models securely, and which bottlenecks matter most when running long context, multimodal, or high throughput applications. You will also hear how to optimize your own AI workloads with better token throughput, how to choose the right hardware strategy for scale, and how inference first architecture can turn models into real products. This conversation breaks down the tools, techniques, and design patterns that can help your AI agents run faster, cheaper, and more reliably in production. Stay Updated: Craig Smith on X: https://x.com/craigss  Eye on A.I. on X: https://x.com/EyeOn_AI 

This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents.  Visit https://agntcy.org/ and add your support. How will AI evolve once it can understand and reason about the 3D world, not just text on a screen? In this episode of Eye on AI, host Craig Smith speaks with Fei Fei Li about the rise of spatial intelligence and the world models that could transform how machines perceive, imagine, and interact with reality. We explore how spatial intelligence goes beyond language to connect perception, action, and reasoning in physical environments. You will hear how models like Marble build consistent and persistent 3D spaces, why multimodal inputs matter, and what it takes to create digital worlds that are useful for robotics, simulation, design, and creative workflows. Fei Fei also explains the challenges of long term memory, continuous learning, and the search for training objectives that mirror the role next token prediction plays in language models. Learn how spatial reasoning unlocks new possibilities in robotics and telepresence, why classical physics engines still matter, and how future AI systems may merge perception, planning, and imagination. You will also hear Fei Fei's perspective on the limits of current architectures, why true understanding is different from human understanding, and how world models could shape the next generation of intelligent systems. Stay Updated: Craig Smith on X: https://x.com/craigss  Eye on A.I. on X: https://x.com/EyeOn_AI

This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents.  Visit https://agntcy.org/ and add your support. How could Karl Friston's Free Energy Principle become a blueprint for the future of AI? In this episode of Eye on AI, host Craig Smith sits down with Karl Friston, the neuroscientist behind the Free Energy Principle and advisor to Verses AI, to explore how active inference and brain inspired generative models might move us beyond transformer based systems. They unpack how Axiom, Verses' new architecture, uses probabilistic beliefs and message passing to build agents that learn like brains instead of just predicting the next token. We look at why transformers face scaling and reliability limits, how Free Energy unifies prediction, perception, and action, and what it means for an AI system to carry explicit uncertainty instead of overconfident guesses. Learn how active inference supports continual learning without catastrophic forgetting, how structure learning lets models grow and prune themselves, and why embodiment and interaction with the real world are essential for grounding language and meaning. You will also hear how Axiom can sit beside or beneath large language models, how explicit uncertainty can reduce hallucinations in high stakes workflows, and where these ideas are already being tested in areas like logistics, robotics, and autonomous agents. By the end of the episode, you will have a clearer picture of how Karl Friston's Free Energy blueprint could reshape AI architectures, from enterprise planning systems to embodied agents that understand and act in the world. Stay Updated: Craig Smith on X: https://x.com/craigss  Eye on A.I. on X: https://x.com/EyeOn_AI  

How are AI and telematics changing safety for fleets in the real world, and what does it take to get from basic recordings to true accident prevention? In this episode of Eye on AI, host Craig Smith speaks with Hemant, Chief Product Officer at Motive, and Ryan, CIO at Fusion Site Services, to explore how AI powered cameras and telematics are transforming safety, productivity, and profitability across the physical economy, from trucking and construction to field services. We look at what makes safety AI trustworthy at scale, how to reduce false alerts that drivers ignore, and how to combine in cab coaching, human review, and rich telematics data to drive down risky behaviors. Learn how Fusion Site Services cut unsafe events by more than ninety percent while tripling in size, slashed insurance claims and premiums, and used real time insights to tackle idling, under utilized assets, and the hidden costs of unsafe operations. You will also hear how leading fleets run side by side vendor tests, design incentive programs that get drivers on board with cameras, and build a culture around zero preventable accidents. If you are responsible for safety, operations, or risk, this episode will show you how to evaluate AI and telematics platforms, which benchmarks to demand, and how to turn your data into safer roads and stronger unit economics. Stay Updated: Craig Smith on X: https://x.com/craigss  Eye on A.I. on X: https://x.com/EyeOn_AI 

How are Decision Intelligence and AI agents reshaping enterprise operations today? In this episode of Eye on AI, host Craig Smith sits down with Fred Laluyaux, CEO of Aera Technology, to unpack how organizations move from dashboards and ad hoc workflows to a system that senses, decides, and acts.  AI is not just about chatbots. At the heart of this transformation is decision intelligence: connecting data, analytics, AI, and automation to optimize decisions across the enterprise. Fred explains why this is becoming the operating backbone of the modern enterprise and how it accelerates the shift toward autonomous, self-driving businesses. We look at how to build a decision intelligence stack end to end, how AI agents collaborate with people, and how to stand up a control room that monitors decisions across supply chain, finance, and customer operations. Learn how leading companies model decisions, govern them safely, and measure impact with clear metrics that matter, including service level, cost to serve, cash flow, inventory turns, and time to resolution. Stay Updated: Craig Smith on X: https://x.com/craigss   Eye on A.I. on X: https://x.com/EyeOn_AI 

This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents.    Visit https://agntcy.org/ and add your support.   Why do today's LLMs forget key details over long context, and what would it take to give them real memory that scales?   In this episode of Eye on AI, host Craig Smith explores Manifest AI's Power Retention architecture and how it rethinks memory, context, and learning for modern models. We look at why transformers struggle with long inputs, how state space and retention models keep context at linear cost, and how scaling state size unlocks reliable recall across lengthy conversations, code, and documents. We also cover practical paths to retrofit existing transformer models, how in context learning can replace frequent fine tuning, and what this means for teams building agents and RAG systems.   Learn how product leaders and researchers measure true long context quality, which pitfalls to avoid when extending context windows, and which metrics matter most for success, including recall consistency, answer fidelity, task completion, CSAT, and cost per resolution. You will also hear how to design per user memory, set governance that prevents regressions, evaluate LLM as judge with human review, and plan a secure rollout that improves retrieval, multi step workflows, and agent reliability across chat, email, and voice. Stay Updated: Craig Smith on X:https://x.com/craigss  Eye on A.I. on X: https://x.com/EyeOn_AI   

This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents.  Visit https://agntcy.org/ and add your support. How do the world's most powerful AI models get trained and trusted at scale, and what does that really take from data to deployment? In this episode, Appen CEO Ryan Kolln joins Eye on AI to unpack how rigorous human evaluation, culturally aware data, and model-based judges come together to raise real-world performance. In this episode of Eye on AI, host Craig Smith speaks with Ryan Kolln, CEO of Appen, about building evaluation systems that go beyond static benchmarks to measure usefulness, safety, and reliability in production. They explore how human raters and AI evaluators work in tandem, why localization matters across regions and domains, and how quality controls keep feedback signals trustworthy for training and post-training. Ryan explains how evaluation feeds reinforcement strategies, where rubric-driven human judgments inform reward models, and how enterprises can stand up secure workflows for sensitive use cases. He also discusses emerging needs around sovereign models, domain-specific testing, and the shift from general chat to agentic workflows that operate inside real business systems. Learn how leading teams design human-in-the-loop evaluation, when to route judgments from models back to expert reviewers, how to capture cultural nuance without losing universal guardrails, and how to build an evaluation stack that scales from early prototypes to production AI. Stay Updated: Craig Smith on X: https://x.com/craigss  Eye on A.I. on X: https://x.com/EyeOn_AI 

Why will agentic AI redefine every digital interaction, and what foundation do enterprises need to make it safe, trusted, and real time? In this episode of Eye on AI, host Craig Smith sits down with Jeff Lunsford to unpack how a neutral customer data platform like Tealium becomes the control plane for agentic systems. We cover how to collect and unify first party data responsibly, enforce consent and identity across channels, and feed the right context to models so agents can act with confidence in the moment. You will hear how real time profiles, event streams, and deterministic identity power personalization, automation, and transactions across web, mobile, ads, email, and customer support. Learn how leading enterprises are preparing for agentic commerce that could double digital interactions, why governance and privacy must be embedded into delivery teams, and which standards enable safe transactions and payments with agents. You will also hear how to build an "agentic front door" for your business, design guardrails and spending allowances, choose where to run reasoning and inference, and measure impact with metrics like conversion rate, ROAS, CSAT, and cost per resolution. ​​Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents.  Visit https://agntcy.org/ and add your support. How is Coxwave Redefining AI Evaluation? In this episode of Eye on AI, host Craig Smith is joined by Yeop Lee, Head of Product at Coxwave. Together they explore how teams move beyond accuracy-only metrics to outcome focused evaluation with Coxwave's Align. We look at how Align measures satisfaction, trust, and task completion across chat, email, and voice, how LLM as judge pairs with human review, and how product teams search conversations to find hidden failure patterns that block adoption. Learn how leading companies design an evaluation stack that guides prompts, agents, and UX, which pitfalls to avoid when shipping updates, and which metrics matter most for success, including completion rate, CSAT, retention, and cost per resolution. You will also hear how to run experiment tracking with model and prompt change logs, set up governance that prevents regressions, and choose between SaaS and on premise deployments that meet security and compliance needs. Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents.  Visit https://agntcy.org/ and add your support. Why do so many chatbots fail in the real world, and how can AI agents actually fix customer support? In this episode of Eye on AI, host Craig Smith explores how teams move beyond scripted bots to production-grade AI agents that resolve real issues across chat, email, and voice. We look at what makes agents reliable at scale, how to configure them safely, and how to manage them like digital workers alongside your human team. Learn how leading companies approach agent onboarding and governance, which pitfalls to avoid, and which metrics matter most for success, including resolution rate, CSAT, and cost per resolution. You will also hear how to enable actions like refunds and returns through secure procedures, design human handoff that customers appreciate, and build an omnichannel rollout plan that scales responsibly. ​​Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

Try OCI for free at http://oracle.com/eyeonai This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking.  Join Modal, Skydance Animation, and today's innovative AI tech companies who upgraded to OCI…and saved.   How are enterprises moving from AI experiments to a true agentic enterprise with measurable ROI? In this episode of Eye on AI, host Craig Smith speaks with Bhaskar Roy from Workato about how organizations can design, orchestrate, and govern AI agents at scale without sacrificing security or control. Together they unpack Workato's approach to building a single workspace for employees while agents and apps work behind the scenes to automate real business processes. They explain why the future of enterprise AI depends on orchestration, permissions, and human in the loop design. You will hear how Workato One and Workato Go bring connectivity, action, and governance into one stack, how teams assign KPIs to agents and track outcomes, and how to reduce agent sprawl while optimizing SaaS spend. Learn how leading companies are defining the agentic enterprise, what pitfalls to avoid when moving from pilots to production, and how to measure impact across sales, IT, support, HR, and finance so AI drives durable business value. Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents.  Visit https://agntcy.org/ and add your support. How can enterprises truly scale with agentic AI?  In this episode of Eye on AI, host Craig Smith speaks with Greg Shewmaker, CEO of r.Potential, about how organizations can successfully implement agentic AI systems that enhance human performance instead of replacing it. Greg explains why the future of work depends on a new partnership between people and intelligent digital agents. He shares how r.Potential, a spin-out from the Adecco Group, helps enterprises design “digital workforces,” integrate AI agents into complex systems, and rethink productivity from the C-suite down. Learn how leading companies are approaching AI adoption, what pitfalls to avoid, and why agentic AI could redefine how enterprises operate and grow in the years ahead. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

Discover how Neurix is building the next generation of voice AI that sounds and reacts like a human in this conversation with Peeyush, former Google technologist and co-founder of Miracle Labs. Peeyush shares how Neurix is solving the toughest challenges in conversational AI — from eliminating latency to creating natural, real-time dialogue that mirrors human interaction. He explains why voice is the hardest frontier in AI, how Neurix's proprietary models manage conversation flow, and what it takes to integrate voice agents into enterprise systems at scale. Learn how Neurix is combining low-latency speech recognition, dialogue management, and large language models to deliver seamless, multilingual customer experiences. If you're a business leader, product builder, or AI professional interested in how human-like voice agents are transforming customer support and enterprise communication, this episode reveals the future of intelligent conversation.   Stay Updated: Craig Smith on X:https://x.com/craigss  Eye on A.I. on X: https://x.com/EyeOn_AI 

This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. Can AI and RNA testing make illness optional? In this episode, Eye on AI host Craig S. Smith sits down with Naveen Jain, founder and CEO of Viome, to explore how RNA sequencing and artificial intelligence are transforming our understanding of chronic disease. Jain shares how a personal tragedy led him to launch Viome, a company on a mission to digitize the human body, predict illness before symptoms appear, and revolutionize healthcare. Together they discuss how Viome uses metatranscriptomics to analyze microbiome and human gene expression, what makes RNA a better indicator of health than DNA, and how large molecular AI models are paving the way for early detection of cancer, diabetes, Alzheimer's, and more. Jain also reveals his bold entrepreneurial framework—“Why this, why now, why me?”—and his belief that asking better questions is the real key to innovation. If you're interested in the intersection of AI, biotechnology, and human longevity, this is an episode you won't want to miss. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.   Joel Hron, Chief Technology Officer at Thomson Reuters, joins Eye on AI to unpack the future of agentic systems and what it takes to build them responsibly at enterprise scale. We dive into the shift from prompt-based AI to true agentic workflows capable of planning, reasoning, and executing complex tasks. Joel breaks down how Thomson Reuters is deploying generative AI across law, tax, risk, and compliance, while keeping human experts in the loop to ensure trust and accuracy in high-stakes domains. Topics include: - What separates agentic AI from simple prompt-based tools - How “agency dials” (autonomy, tools, memory) change system behavior - Infrastructure and architecture required for multi-agent collaboration - Why human verification and user experience design are essential for trust - The future of coding, engineering skills, and AI adoption inside enterprises If you want to understand how a 170-year-old company is reinventing itself with AI — and what's next for agentic systems in business and knowledge work — this conversation is a must-listen. Stay Updated: Craig Smith on X:https://x.com/craigssEye on A.I. on X: https://x.com/EyeOn_AI

How do we get from today's AI copilots to true human-level intelligence? In this episode of Eye on AI, Craig Smith sits down with Eiso Kant, Co-Founder of Poolside, to explore why reinforcement learning + software development might be the fastest path to human-level AI. Eiso shares Poolside's mission to build AI that doesn't just autocomplete code — but learns like a real developer. You'll hear how Poolside uses reinforcement learning from code execution (RLCF), why software development is the perfect training ground for intelligence, and how agentic AI systems are about to transform the way we build and ship software. If you want to understand the future of AI, software engineering, and AGI, this conversation is packed with insights you won't want to miss. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) The Missing Ingredient for Human-Level AI(01:02) Eiso Kant's Journey(05:30) Using Software Development to Reach AGI(07:48) Why Coding Is the Perfect Training Ground for Intelligence(10:11)  Reinforcement Learning from Code Execution (RLCF) Explained(13:14) How Poolside Builds and Trains Its Foundation Models(17:35) The Rise of Agentic AI(21:08)  Making Software Creation Accessible to Everyone(26:03) Overcoming Model Limitations(32:08) Training Models to Think(37:24) Building the Future of AI Agents(42:11) Poolside's Full-Stack Approach to AI Deployment(46:28) Enterprise Partnerships, Security & Customization Behind the Firewall(50:48) Giving Enterprises Transparency to Drive Adoption  

Discover how enterprises can successfully adopt and scale agentic AI to create real business impact in this conversation with Florian Douetteau, CEO and co-founder of Dataiku. Florian shares why democratizing AI across the enterprise is essential, how to prevent agent sprawl, and what it takes to build a governance framework that keeps your data secure while enabling innovation. Learn about Dataiku's enterprise AI blueprint, its partnership with NVIDIA, and how global companies are using agentic workflows to accelerate R&D, optimize operations, and stay competitive. If you're a business leader, CTO, or data professional looking to scale AI safely and effectively, this episode is your playbook for the future of enterprise AI. Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI 00:00 Intro 00:31 Florian's Background & Dataiku's Founding   03:00 Enterprise Blueprint for AI with NVIDIA   05:13 Unique Needs of Financial Services   07:09 Building Agents on Dataiku   09:22 Permissioning & Governance   11:17 Agent Lifecycle Management   13:20 State of Agent-to-Agent Systems   15:02 Real-World Use Cases of Agents   16:28 The Most Complex Agents in Production   19:01 Future Vision: Headless Organizations   21:04 Human-Like Qualities of Agents   24:56 The LLM Mesh & Model Abstraction   28:55 Guardrails & Compliance   31:12 No-Code + Code-Friendly Collaboration   36:12 Breaking Silos & Centers of Excellence   41:36 Distribution & Seat Allocation   43:34 Most Common Agents by Industry   47:02 The State of Enterprise AI Adoption  

Try OCI for free at http://oracle.com/eyeonai This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today's innovative AI tech companies who upgraded to OCI…and saved. AI-generated code is exploding, but reviewing it all has become the new bottleneck for engineering teams. In this episode, Sahil Bansil from CodeRabbit reveals how their AI-powered platform is transforming the code review process, helping developers ship faster without compromising quality. He explains how CodeRabbit uses advanced LLM context engineering to deliver senior-level review quality, reduce pull request merge times by up to 50%, and catch more bugs before they reach production. Whether you're a developer, engineering manager, or CTO, this conversation shows why automated code review is essential in the AI era and how CodeRabbit can help your team scale software delivery while keeping quality high. Cut Code Review Time & Bugs in Half. Instantly with CodeRabbit: https://www.coderabbit.ai/ Stay Updated: Craig Smith on X:https://x.com/craigssEye on A.I. on X: https://x.com/EyeOn_AI (00:00) LLMs & Why Context Matters  (02:26) Meet Sahil Bansil from CodeRabbit  (04:04) AI Code Boom & The Review Bottleneck  (06:05) Why CodeRabbit Focused on Reviews, Not Generation  (09:55) Keeping Humans in the Loop for Code Quality  (14:30) IDE Reviews vs PR Governance  (17:51) Inside CodeRabbit's Context Engineering  (20:42) Building Context from Code Graphs & Jira Tickets  (22:15) Eliminating AI Hallucinations with Verification  (27:19) Empowering Junior Developers & Legacy Code Support  (32:40) CodeRabbit's Open Source & Enterprise Success Stories  (36:56) Cutting Review Times & PR Merge Delays  (44:35) Scaling CodeRabbit & The Growing Market   

Discover how Sema4.ai is redefining enterprise AI with a platform built to help businesses build, operate, and scale SAFE AI agents. In this conversation, CTO and co-founder Ram Venkatesh explains why simply generating insights isn't enough and why enterprises need AI that can act on those insights reliably, securely, and at scale. If you want to understand the future of agentic AI and how to safely scale AI across your organization, this episode is a must-watch. Stay Updated:Craig Smith on X: https://x.com/craigssEye on A.I. on X: https://x.com/EyeOn_AI (00:00) The Data-to-Action Gap (00:38) Ram's Big Data Background (03:22) Why RPA Failed & Agents Win   (04:39) Conversational Agents vs Manual Workflows   (06:28) The Power of a Semantic Layer   (08:20) Runbooks: Capturing Intent, Not Just Steps   (11:16) Connecting Data Across Systems   (15:12) How Sema4.ai Keeps AI Secure   (17:37) From 20 to 2,000 Agents: Scaling the Fleet   (20:20) Choosing the Right Agent Platform   (26:22) Process Architects: The New Role in AI   (29:00) Why Finance & Healthcare Lead in Adoption   (30:04) Sema4.ai's Pricing & Adoption Playbook   (41:29) Scaling Faster with Snowflake Deployment   (43:10) ISVs & Domain Experts as Agent Builders  

Enterprise AI Agents for Work, Service and Process: www.kore.ai Kore.ai founder and CEO Raj Koneru breaks down how enterprises are moving beyond chatbots into agentic AI that actually ships. We get into the no-code tooling behind multi-agent workflows, agentic RAG, guardrails that keep outputs in scope, and why a control layer for governance is now essential. Raj shares real scale numbers, the three Kore.ai product lanes for customer and employee experience, and how partnerships with Microsoft and AWS let teams build where they already run. If you care about building secure, explainable AI agents that integrate fast and scale cleanly, this one is for you. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Raj Koneru's Journey & The Birth of Kore.ai (03:10) From Chatbots to Enterprise-Grade Agents(06:33) Security, Scale & Proof in the Market(07:04) What Agentic AI Really Means(12:16) Building & Governing AI Agents(17:26) Kore.ai's Product Lines & Differentiation(20:22) Industry Applications & Case Studies(28:17) User Experience & Change Management(34:46) Governance, Identity & Cost Controls(39:56) Adoption Timelines & Market Outlook(43:51) Roadmap & Partnerships(47:38) Future of the Enterprise AI Landscape

What if AI could decode government in real time? In this episode of Eye on AI, Craig Smith sits down with Pat Utz, CEO and Co-Founder of Abstract, the AI startup building “regulatory superintelligence” to track and analyze laws, bills, and regulations across 145,000+ government entities. Pat explains how Abstract evolved from university research into a venture-backed company helping law firms, enterprises, and policymakers cut through the noise of Congress, state legislatures, and regulatory agencies. From uncovering hidden amendments in massive bills to proactively identifying risks and opportunities for businesses, Abstract is transforming how we understand legislation. We cover: How AI is reshaping lobbying, law, and compliance Why Abstract is focused on proactive intelligence, not reactive compliance The role of AI agents, LLMs, and retrieval-augmented generation (RAG) in policy analysis Real examples of AI influencing funding and legislation The future of democracy when citizens and businesses have true transparency into government Whether you're in tech, law, government affairs, or just curious about how AI is changing democracy, this conversation reveals the future of policy intelligence.

What if your warehouse could see everything, all the time? In this episode of Eye on AI, we sit down with Andrei Danescu, CEO & Co-Founder of Dexory, to explore how AI and robotics are transforming logistics. Andrei shares his journey from Formula 1 engineering to building one of the fastest-growing robotics companies in Europe. He explains how Dexory's autonomous robots and real-time digital twins are giving warehouses unprecedented visibility, cutting errors, boosting efficiency, and even turning storage into a profit driver. We cover: Why warehouses struggle with visibility and how AI solves it The role of autonomous robots in scanning 10,000+ pallet locations per hour How digital twins unlock optimization in space, flow, and production Dexory's vision for the future of supply chains across Europe and the US The balance between human workers and automation in logistics If you want to understand the future of logistics, warehouse technology, and supply chain visibility, this conversation will give you a front-row seat. Subscribe for more deep dives on AI, robotics, and the future of work.   Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI   (00:00) Intro (02:08) The Birth of Dexory and Its Mission   (04:23) Building Autonomous Robots and Digital Twins   (08:52) Optimizing Space, Storage, and Traffic Flow   (12:15) DexoryView: The Platform Behind the Robots   (16:03) Humans, Robots, and the Future of Warehouses   (18:54) AI, SLAM, and the Tech Driving Dexory   (23:17) Real-Time Visibility and Error Elimination   (27:31) Multi-Site Insights and Supply Chain Potential   (32:47) Scaling Dexory: Markets, Adoption, and Growth   (37:01) Scanning at Scale: 10,000+ Pallets Per Hour   (41:11) Roadmap: AI Agents, Simulations, and Next Steps   (45:13) A Vision for Global Logistics Networks

Marketing is changing forever.    In this episode of Eye on AI, host Craig Smith sits down with Chris O'Neill, CEO of GrowthLoop and board member at Gap, to explore how agentic AI and GrowthLoop's Compound Marketing Engine are transforming the way brands connect with their customers.   Chris shares how GrowthLoop applies AI on top of modern data clouds like Snowflake, BigQuery, and Databricks to automate audience targeting, personalize campaigns in real time, and accelerate experimentation loops.    He explains why speed and iteration matter more than ever, how companies like Allegro doubled their return on ad spend with GrowthLoop, and why the future of marketing belongs to brands that embrace agentic AI.   If you're a marketer, technologist, or business leader looking to stay ahead in the age of AI, this conversation is packed with practical insights you can't afford to miss. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. In this episode of Eye on AI, we sit down with Leon Song, VP of Research at Together AI, to explore how open-source models and cutting-edge infrastructure are reshaping the AI landscape.    From speculative decoding to FlashAttention and RedPajama, Leon shares how Together AI is building one of the fastest, most cost-efficient AI clouds—helping enterprises fine-tune, deploy, and scale open-source models at the level of GPT-4 and beyond.   We dive into Leon's journey from leading DeepSpeed and AI for Science at Microsoft to driving system-level innovation at Together AI. Topics include: The future of open-source vs. closed-source AI models Breakthroughs in speculative decoding for faster inference How Together AI's cloud platform empowers enterprises with data sovereignty and model ownership Why open-source models like DeepSeek R1 and Llama 4 are now rivaling proprietary systems The role of GPUs vs. ASIC accelerators in scaling AI infrastructure   Whether you're an AI researcher, enterprise leader, or curious about where generative AI is heading, this conversation reveals the technology and strategy behind one of the most important players in the open-source AI movement. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

This episode is brought to you by Extreme Networks, the company radically improving customer experiences with AI-powered automation for networking.Extreme is driving the convergence of AI, networking, and security to transform the way businesses connect and protect their networks, delivering faster performance, stronger security, and a seamless user experience. Visit https://www.extremenetworks.com/ to learn more. JotForm began nearly twenty years ago as a simple online form builder.  Today, it has grown into a platform powering millions of users and has recently stepped into a new era of AI. In this episode, Aytekin Tank, founder and CEO of JotForm, shares the story of how the company pivoted from forms to launching AI Agents that are changing the way small and medium-sized businesses handle customer support and automation. Aytekin explains how JotForm's AI journey started as an internal experiment to fill out forms by voice, only to discover that most users wanted it for customer service. That insight sparked the creation of JotForm AI Agents, tools that don't just answer questions, but perform tasks, scale support teams, and transform the customer experience.  Beyond the technology, Aytekin outlines a bold vision of the future where every business, no matter the size, will have its own AI-powered agent available around the clock to schedule appointments, answer questions, and even process transactions.  This conversation explores how AI is reshaping customer service and why small businesses, nonprofits, and educators stand to benefit the most from this wave of innovation. Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) The Scale of JotForm Today and the AI Vision   (01:32) Aytekin's Journey: From Developer to Bootstrap Founder   (03:36) The Pivot: From Voice Forms to AI Customer Service   (05:25) Building and Launching JotForm AI Agents   (06:20) Using AI Internally: Cutting Tickets and Boosting Resolution Rates   (08:13) Why AI Agents Go Beyond Chatbots   (12:22) Demonstrating JotForm AI in Action   (21:40) The Tech Stack Behind JotForm's AI Agents   (24:59) Training and Teaching Your Own AI Agent   (33:27) Competition, Differentiation, and Market Strategy   (36:55) Why Small Businesses Need AI the Most   (38:24) The Future: Every Business With Its Own AI Agent   (40:19) Pricing, Growth, and Lessons in Scaling AI   (42:26) Slow Growth vs Explosive Scale and Lessons Learned   (43:55) Aytekin's Vision for AI in Business

Try OCI for free at http://oracle.com/eyeonai This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today's innovative AI tech companies who upgraded to OCI…and saved.  Matthew Carroll, CEO and co-founder of Immuta, joins the Eye on AI podcast to explore how data access governance is evolving in the age of generative AI.  As AI drives a surge in both human and non-human data consumers, traditional security models are no longer enough. Matthew explains how Immuta automates compliance, enforces policies across global jurisdictions, and scales secure access for enterprises—from blinded clinical trials in pharma to cross-border data sharing.  Discover why AI-powered governance agents, risk-based access controls, and native cloud integration are the future of compliant, scalable data use. Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) How Immuta Governs Data in the AI Era   (02:59) Security Alone Isn't Enough in AI   (05:24) From U.S. Intel Roots to Immuta's Platform   (07:38) Pharma Trials: Protecting Billions in Drug Development   (12:58) The Data Marketplace & Access Negotiations   (16:07) Why Native Integration Beats Proxy Models   (20:33) Managing Data Across Borders & Sovereignty Laws   (25:33) The Data Governor Bottleneck (and AI Solution)   (31:05) Inside Immuta's SaaS Model & User Roles   (33:26) Big Data Lessons Driving AI ROI   (41:05) The Growing Data Governance Market   (45:48) Storage Portability & Apache Iceberg Explained   (48:32) Future Shift to Risk-Based, AI-Driven Access

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. How does a 150,000-employee global leader make AI work at scale? In this episode of Eye on AI, host Craig Smith sits down with Julia Peyre, Head of AI Strategy & Innovation at Schneider Electric, to explore how the company is pioneering enterprise AI adoption through its AI Hub, hybrid AI systems, and real-world digital twin applications. From breaking data silos and embedding AI into hardware, to partnering with startups and building predictive maintenance solutions, Julia shares a blueprint for bringing AI from pilot programs to full-scale deployment, across both internal processes and customer-facing products. Stay Updated: Craig Smith on X:https://x.com/craigssEye on A.I. on X: https://x.com/EyeOn_AI (00:00) Preview and Intro (01:58) Meet Julia Peyre & Her Role(03:19) Inside Schneider's AI Hub(05:51) AI in Industrial Automation & Robotics(08:43) Internal vs External AI Applications(13:54) Why Schneider Is Ahead in AI Adoption(15:57) Centralized AI Hub Model(19:38) Hybrid AI: Combining Physics & Data(25:44) Early Steps in Multi-Agent Systems(29:54) Breaking Data Silos for AI at Scale(32:02) Predictive Maintenance with Hybrid AI(37:03) Long-Term View on AI Automation(42:37) Advice for Young Professionals in AI(44:21) Framework for Evaluating AI Solutions(50:19) Involving End Users in AI Testing

In this episode of Eye on AI, host Craig Smith sits down with Alex Salazar, co-founder and CEO of Arcade.dev, to explore what it really takes to build secure, scalable AI agents that can take real-world actions. While everyone's talking about the future of autonomous agents, most never make it past the demo stage. Why? Because agents today lack secure infrastructure to connect with real tools like Gmail, Slack, Notion, GitHub—and do so on behalf of users without breaking authentication protocols. Alex shares how Arcade solves the missing layer in AI agent development: secure tool execution, user-specific authorization, OAuth flows, and production-ready consistency. Whether you're building with GPT‑4, Claude, or open-source models, Arcade handles the hard part—making agent actions actually work. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Why AI Agents Can't Take Action (Yet) (01:27) Meet Alex Salazar: From Okta to Arcade (03:39) What Arcade.dev Actually Does (05:16) Agent Protocols: MCP, ACP & Where Arcade Fits (07:36) Arcade Demo: Building a Multi-Tool AI Agent (11:16) Handling Secure Authentication with OAuth (14:40) Why Agents Need User-Tied Authorization (19:25) Tools vs APIs: The Real Interface for LLMs (23:41) How Arcade Ensures Agents Go Beyond Demos (25:48) Why Arcade Focuses on Developers, Not Consumers (27:55) The Roadblocks to Production-Ready Agents (31:15) How Arcade Integrates Into Agent Workflows (33:16) Tool Calling & Model Compatibility Challenges (34:49) Arcade's Pricing Model Explained (36:20) Competing with Big Tech: IBM, AWS & Others (38:38) Future of Agents: From Hype to Workflow Automation (41:58) Real Use Cases: Email Agents, Slack Bots, Finance & More (46:17) Agent Marketplaces & The Arcade Origin Story

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. What happens when AI meets the chaos of real-world customer support? In this episode of Eye on AI, we sit down with Ryan Wang, co-founder and CEO of Assembled, to unpack how AI is transforming the future of customer service, without replacing humans. Ryan reveals how Assembled went from a workforce scheduling tool to a full-stack AI support platform used by companies like Stripe, Robinhood, and Honeylove. You'll learn how conversational AI agents are handling up to 75% of support inquiries, why voice is the next big frontier, and how AI copilots are helping human agents become 15% more productive. But this isn't just hype. Ryan shares the hard economic truths behind automation—why humans aren't going away, how companies are navigating global workforce optimization, and why hybrid AI + human systems are here to stay. This episode gives you a front-row seat into how the smartest companies are rethinking support at scale. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Preview and Intro (01:37) Ryan Wang's Journey from Stripe to Assembled   (04:55) Launching Assembled (09:49) From Scheduling Tool to AI-Powered Support   (12:11) Who Uses Assembled: Companies vs. BPOs   (14:57) Building Conversational and Voice AI Agents   (21:10) Competing with Zendesk, Salesforce & Crescendo   (23:07) How Assembled Integrates with Customer Support Stacks   (25:40) The Niche Power of Workforce Management Tech   (31:16) Why the Customer Support Market Is Ripe for Disruption   (33:47) How Assembled Swaps Between OpenAI, Claude & Others   (37:56) Evaluating LLMs with Golden Datasets and 'Vibe Checks'   (41:20) Multilingual Support and the Challenge of Europe   (45:11) Industry Focus vs. Complexity Focus   (47:43) Voice AI: The Next Big Frontier? (50:18) The Truth About AI Replacing Jobs in Support   (54:39) The Automation Paradox: Why Labor Isn't Shrinking  

What if the biggest challenge in AI isn't how fast chips can compute, but how quickly data can move? In this episode of Eye on AI, Nandan Nayampally, Chief Commercial Officer at Baya Systems, shares how the next era of computing is being shaped by smarter architecture, not just raw processing power. With experience leading teams at ARM, Amazon Alexa, and BrainChip, Nandan brings a rare perspective on how modern chip design is evolving. We dive into the world of chiplets, network-on-chip (NoC) technology, silicon photonics, and neuromorphic computing. Nandan explains why the traditional path of scaling transistors is no longer enough, and how Baya Systems is solving the real bottlenecks in AI hardware through efficient data movement and modular design. From punch cards to AGI, this conversation maps the full arc of computing innovation. If you want to understand how to build hardware for the future of AI, this episode is a must-listen. Subscribe to Eye on AI for more conversations on the future of artificial intelligence and system design. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Why AI's Bottleneck Is Data Movement (01:26) Nandan's Background and Semiconductor Career (03:06) What Baya Systems Does: Network-on-Chip + Software (08:40) A Brief History of Computing: From Punch Cards to AGI (11:47) Silicon Photonics and the Evolution of Data Transfer (20:04) How Baya Is Solving Real AI Hardware Challenges (22:13) Understanding CPUs, GPUs, and NPUs in AI Workloads (24:09) Building Efficient Chips: Cost, Speed, and Customization (27:17) Performance, Power, and Area (PPA) in Chip Design (30:55) Partnering to Build Next-Gen Photonic and Copper Systems (32:29) Why Moore's Law Has Slowed and What Comes Next (34:49) Wafer-Scale vs Traditional Die: Where Baya Fits In (36:10) Chiplet Stacking and Composability Explained (39:44) The Future of On-Chip Networking (41:10) Neuromorphic Computing: Energy-Efficient AI (43:02) Edge AI, Small Models, and Structured State Spaces

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.   Grammarly is no longer just a writing assistant. It's building an AI productivity platform that could rival Microsoft Copilot. In this episode, Luke Behnke, VP of Enterprise Product at Grammarly, shares how the company is moving beyond grammar correction into intelligent agents, enterprise workflows, and real-time AI tools.   We dive into Grammarly's new Authorship feature, why AI fluency is becoming essential at work, how Grammarly is integrating tools like Coda and Superhuman, and what the future of multi-agent systems looks like.   If you're curious about where AI at work is really heading, this conversation will give you a clear and powerful glimpse. (00:00) Preview and Intro (03:37) Meet Luke Behnke(05:00) Grammarly's Origin Story and Early Vision(09:11) Grammarly's UX Advantage(13:30) Competing With Microsoft Copilot and Built-In Assistants(17:48) What Is “Authorship” and Why It Matters(20:31) AI Detection vs Authorship Tracking(25:05) The Future of AI Transparency(27:43) Why AI Fluency Will Be a Job Requirement(32:04) Grammarly's Agentic Vision(34:11) The Rise of Context-Aware Enterprise Agents(38:24) Use Cases: Automating Tasks Across Tools with AI(40:21) The Coda Acquisition & Building the Agent Platform(44:48) The Future of Interoperable AI Agents(47:43) Why Agent Oversight Is Crucial in Enterprise AI(55:57) Measuring Grammarly's ROI in the Enterprise

This episode is brought to you by Extreme Networks, the company radically improving customer experiences with AI-powered automation for networking.Extreme is driving the convergence of AI, networking, and security to transform the way businesses connect and protect their networks, delivering faster performance, stronger security, and a seamless user experience. Visit https://www.extremenetworks.com/ to learn more. In this episode, Craig Smith sits down with Benjamin Encz, co-founder and CEO of Ashby, the AI-powered recruiting platform that is transforming how companies hire.  Ashby is disrupting the $650B recruiting industry by combining automation, data, and large language models to streamline the entire hiring process, from job postings to resume screening and interview scheduling. With clients like OpenAI and Shopify, Ashby is setting a new standard for modern recruiting.  Benji shares how AI is boosting efficiency while keeping human judgment at the center, and what the future of hiring could look like as these tools continue to evolve.   Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. What if the most important AI conference in the world wasn't built by academics or hype merchants, but by operators who actually understand what businesses need? In this episode, Craig sits down with Andrew Blum, Co-Founder and COO of HumanX, the breakout AI conference that has quickly become the go-to gathering for enterprise leaders, AI builders, and government policymakers. Andrew shares the inside story of how HumanX went from an idea born in a VC incubator to hosting 3,300+ attendees, 350 speakers, and leaders from OpenAI, Anthropic, Mistral, Snowflake, and more, all within 18 months. You'll hear how HumanX is different from other conferences, why face-to-face connection matters more than ever, and how HumanX is creating the bridge between AI innovation and real-world business transformation. This is a behind-the-scenes look you won't want to miss. Like and subscribe for more! Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today's innovative AI tech companies who upgraded to OCI…and saved.    Try OCI for free at http://oracle.com/eyeonai   What if the future of enterprise wasn't human-driven, but agent-driven? In this groundbreaking episode, Steve Lucas, CEO of Boomi, unveils a radical vision for the next era of business: one where AI agents will power 75% of enterprise operations by 2026. From eliminating traditional user interfaces to transforming legacy systems with no-code automation, Steve walks us through how Boomi is building the infrastructure for a self-driving enterprise, and why businesses that fail to prepare will be left behind.   This episode will shift your perspective on where the enterprise is headed and who (or what) will be running it. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.   In this episode, GitHub CEO Thomas Dohmke joins us for a deep dive into the evolution of software development — from decentralized version control to the rise of AI coding agents. With over 150 million developers on GitHub and tools like Copilot rewriting the rules of software engineering, we explore what it really means to build in an AI-native future.   Thomas shares the origin story of Copilot, how GitHub is shifting from human-to-human to human-to-agent collaboration, and why he believes natural language is becoming the universal programming language. We also cover the technical architecture behind Coding Agents, the feedback loop between developers and AI, and what it takes to scale multi-agent systems in the real world.   Like and subscribe for more!     Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI     (00:00) The Future of AI-Powered Coding (02:04) Thomas Dohmke's Journey (05:16) GitHub's Origin Story & Evolution (08:45) Life Before GitHub: Early Version Control Systems (10:40) What is Git? And Why GitHub Matters (12:36) The Birth of GitHub Copilot (16:17) The Rise of AI Agents (17:52) How Kids Are Learning to Code with Copilot (22:38) Can Non-Coders Use Copilot Agents Effectively? (26:01) What the Coding Agent Actually Does Behind the Scenes (31:30) The Models Behind GitHub Copilot & Developer Choice (35:22) How Much Code Is Now Written by AI? (38:51) GitHub's Innovation Strategy (41:54) What's Next for GitHub (45:24) From 150M to 1B Developers: Empowering the World to Build (47:51) GitHub Universe & Galaxy Events (49:53) GitHub's Innovation Graph and the Power of Open Collaboration

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.   In this episode of Eye on AI, Craig Smith sits down with Jason Hardy, Chief Technology Officer for AI at Hitachi Vantara, to explore what it really takes to deploy AI at scale in the enterprise, beyond the hype.   Jason shares how Hitachi is building a pragmatic, outcomes-driven AI platform through Hitachi iQ. From working with NVIDIA to integrating agentic AI into operations, this conversation unpacks the infrastructure, mindset, and strategies needed to move AI projects from experimentation to production.   Whether you're navigating AI adoption, battling with data readiness, or looking to build your own LLM-powered applications, this episode offers invaluable insights from a company that's actually doing it globally, sustainably, and at scale.   Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI     (00:00) Preview (02:10) The Role of CTO for AI at Hitachi Vantara (05:38) Applying AI Across Manufacturing, Energy & Transport (09:54) What Is Pragmatic AI? (13:21) Infrastructure Demands of Generative AI (14:47) Why Most AI Projects Fail (20:25) Inside the Hitachi iQ Platform & NVIDIA Partnership (25:42) Building a Model-Agnostic, Hybrid AI Stack (32:08) Beyond Selling GPUs: Delivering Real AI Outcomes (38:09) Supporting Hybrid Deployments Across Cloud and On-Prem (42:02) Rethinking ROI: Failure as a Strategic Advantage (47:44) Agentic AI and the Future of Autonomous IT Workflows (49:37) Five Core Domains of Agentic AI at Hitachi (53:02) Making AI Infrastructure Sustainable (56:48) Hitachi's Vision for the Future of Enterprise AI

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.     How AI Is Transforming the Physical World | Samsara's Vision for the Future of Operations   In this episode of Eye on AI, Craig Smith sits down with Kiren Sekar, Chief Product Officer at Samsara, to explore how AI, edge computing, and IoT are revolutionizing the world of physical operations - from fleets and factories to farms and field teams.   Samsara has quietly become the digital backbone for thousands of frontline businesses, collecting trillions of data points across vehicles, tools, and teams. Kiren explains how they're building AI-powered systems that don't just collect data, they deliver real-time safety alerts, optimize routes, track fuel efficiency, and even coach drivers automatically.   Whether you work in tech, operations, or AI, this episode shows how AI is finally meeting the real world.   Check our Samsara, AI Build for Physical Operations: https://www.samsara.com/   Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Preview (02:01) Kiren Sekar's Background and Why Samsara Was Founded (06:38) The Real-World Impact of Samsara's AI Systems (09:04) What Changed After Samsara Went Public (11:09) How Samsara Gives Businesses Visibility Into Operations (13:08) The Hardware and Cellular Network Powering Samsara (14:13) AI to Detect Driving Risks (23:13) Tracking Every Asset: From Cranes to Toolkits (25:20) Why Even Mid-Sized Companies Can Use Samsara Easily (27:25) Regional Dashboards and AI Insights for Executives (29:57) How Samsara Decides Where to Apply AI (32:54) Can AI Read Handwritten Forms? (35:31) The AI Models Samsara Uses (39:21) What Samsara Processes at the Edge vs in the Cloud (43:00) Why Samsara Keeps Its R&D Team Small and Fast (46:35) Why Legacy Industries Are Finally Adopting AI (49:12) What Agentic AI Workflows Look Like at Samsara (54:53) What's Next: AI Voice Assistants for Field Worker  

What does the future of enterprise networking really look like?   In this episode, Extreme Networks' Chief Product & Technology Officer Nabil Bukhari joins Craig to explore how AI, autonomous agents, and platform thinking are transforming the core infrastructure of modern businesses.   From managing mission-critical networks to building agentic systems that collaborate, troubleshoot, and scale autonomously - this is a deep dive into how connectivity is being redefined from the ground up.   Whether you're a tech leader, CIO, product builder, or simply curious about how infrastructure evolves, this conversation reveals where the enterprise is headed next.   Check out Extreme Networks: https://www.extremenetworks.com/   Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI   (00:00) Preview (01:02) Introducing Nabil Bukhari & Extreme Networks (05:24) Why Global Connectivity Is Still Accelerating (07:54) How Enterprise Data Flows Across Modern Networks (12:34) Networking for AI vs. Built-in AI (14:12) Platform One & Agentic AI Systems Explained (21:20) Human-in-the-Loop, Over-the-Loop, and Above-the-Loop (23:35) Why AI Guardrails Must Be Baked into the Architecture (27:33) Introducing the ARC Framework (31:15) Persona-Based Interfaces for NetOps, CFOs & CMOs (33:25) The Problem with Chatbots (36:06) Enterprise vs. Public Networks (38:38) Global Connectivity Infrastructure & Use Case Variability (44:29) How Secure and Resilient Are Enterprise Networks? (52:24) In-House AI for Critical Infrastructure

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. What if AI could actually be trusted in healthcare, law, or even car repair? In this episode, Andy Kurtzig, founder and CEO of Pearl (formerly JustAnswer), reveals how his platform is solving the biggest problems in AI: hallucinations, liability, and monetization. Pearl blends large language models with real human experts across 700+ categories—so users get AI speed and human-verified accuracy. Whether you're a doctor, mechanic, or just someone with a question, Pearl offers fast, affordable, and expert-backed answers—without the risk of misinformation. If you're building in AI, working in a regulated industry, or just curious about the future of trusted automation—this episode is for you.   Check out Pearl, AI Enhanced Human Expertise: https://www.pearl.com/ Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Introduction  (03:20) Why Pearl Focuses on High-Stakes Industries   (06:10) How Pearl Reduces AI Hallucinations with Human Trust Scores   (10:11) Pearl.com's Ideal Customers (14:14) Solving AI Liability with Platform Protection   (23:27) The Three Big Problems in AI: Risk, Quality, and Monetization   (29:00) Why Human-in-the-Loop Is the Future of AI   (33:26) Pearl's API: Bringing Verified Experts to Any App   (39:27) Building Trust in AI Through Human Validation   (41:03) The Road Ahead for Pearl and Human-Centered AI

What if you could translate any video into any language—instantly—and make it look like the speaker was really speaking it?   In this episode of Eye on AI, host Craig Smith sits down with Jeff Liu, founder and CEO of Akool, to explore how AI avatars and real-time video translation are eliminating global language barriers. With a background at Apple, Google, and Stanford, Jeff is leading Akool to the frontier of generative AI: cloning faces, voices, and emotions in live video streams.   We dive into the technical architecture behind Akool's real-time avatars, the role of large language models in translation latency, and what the future looks like when the need to "learn languages" may disappear.   Whether you're a content creator, marketer, technologist, or just curious about what's next in AI and communication, this episode is a must-listen. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI   (00:00) Creating Digital Clones with AI (01:20) Jeff Liu's Journey from Big Tech to Startup Founder (02:54) What Akool Does and Who It's For (07:11) Inside the Live AI Avatar Suite (10:32) How Akool Powers Real-Time AI Avatars (16:05) Solving Language Translation with Avatars (21:40) Translating YouTube Videos with One Click (28:36) The Technology Behind Real-Time Translation (33:22) Competing with Tech Giants Like Google (36:26) Akool's Vision (39:36) Avatar Types: Instant, Studio, and Ultra explained (43:39) Building Emotional Nuance into Voice and Video

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.     What's stopping large language models from being truly enterprise-ready?   In this episode, Vectara CEO and co-founder Amr Awadallah breaks down how his team is solving one of AI's biggest problems: hallucinations.   From his early work at Yahoo and Cloudera to building Vectara, Amr shares his mission to make AI accurate, secure, and explainable. He dives deep into why RAG (Retrieval-Augmented Generation) is essential, how Vectara detects hallucinations in real-time, and why trust and transparency are non-negotiable for AI in business.   Whether you're a developer, founder, or enterprise leader, this conversation sheds light on the future of safe, reliable, and production-ready AI.   Don't miss this if you want to understand how AI will really be used at scale.     Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

What if language was no longer a barrier to global business?   In this episode, DeepL CEO Jarek Kutylowski joins Craig Smith to unpack how AI-powered translation is reshaping the way companies communicate across borders.   From real-time speech tools to enterprise-grade language workflows, Jarek shares DeepL's journey, the tech behind their LLMs, and why accuracy, nuance, and localization matter more than ever. If you're building for a global audience, this conversation is a must-listen.     About Jarek: Dr. Jaroslaw “Jarek” Kutylowski is the founder and CEO of DeepL, the Cologne-based Language AI company transforming global communication and breaking down language barriers for businesses worldwide.    Born in Poland and having spent a large part of his life in Germany, Jarek brings an international perspective and a lifelong passion for technology - a developer at heart, he began coding at just 10 years old, building tools he found useful in daily life. He holds a PhD in Computer Science with a focus on mathematics and has held roles at several tech companies prior to founding DeepL.    Under his leadership, DeepL has grown rapidly, expanding its Language AI platform to offer highly accurate and nuanced human-like translation in both written and spoken formats, as well as a contextual AI writing assistant. Today, over 200,000 businesses and governments - and millions of individuals across 228 global markets - trust DeepL for secure, seamless and effective communication.   Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Introduction to DeepL and Jarek's Vision (05:09) DeepL's Technology Evolution (08:17) The DeepL Platform: Products, APIs, and Enterprise Use Cases (12:39) Why DeepL Outperforms Consumer Tools (15:14) How Enterprises Use DeepL (17:05) DeepL's Translation Accuracy (21:20) Breaking Language Barriers in Global Workforces (23:46) A Future Without Language Barriers (27:19) Expanding Language Coverage and Industry Verticals (31:44) DeepL's Role in High-Compliance Sectors (34:04) Tackling Latency and Real-Time Use Cases (38:38) DeepL as the Translation Engine Behind Other Products (42:40) Partnering with News Media and Government (45:40) Pricing Models and Accessibility (46:24) The Human Impact of AI-Powered Language Tools (49:22) What's Next for DeepL and Global Communication

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.   Can AI expand human consciousness? Or is it just a simulation of wisdom? In this mind-bending episode of Eye on AI, host Craig Smith sits down with world-renowned spiritual teacher and author Deepak Chopra to explore the future of Artificial Intelligence, consciousness, health, and spiritual awakening. Deepak unpacks the ideas behind his latest book, Digital Dharma, and shares how his team built a small language model—DeepakChopra.ai—designed to serve as a digital health and spiritual guide. Together, they dive deep into quantum theory, the illusion of the physical world, and why consciousness is not something AI can ever possess—but it can help us reach it. Whether you're an AI enthusiast, a spiritual seeker, or simply curious about the future of human evolution, this episode will challenge your assumptions and expand your perspective.   Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Why Deepak Chopra Is Entering the AI Space (04:05) The Promise and Peril of the AI Revolution (09:47) How Deepak Chopra Built His Own AI Model (13:58) Is AI the Future of Human Evolution? (15:39) How the AI Landscape Has Evolved Over Time (21:22) AI in Preventative Healthcare (24:49) Key Insights from “Digital Dharma” (25:40) Using Prompt Engineering for Inner Growth (38:28) Exploring Human Potential Through AI (43:16) Can AI Understand Human Emotions? (47:00) Spiritual Awakening in the Age of AI (50:54) The Future of AI and Consciousness

This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today's innovative AI tech companies who upgraded to OCI…and saved.   Try OCI for free at http://oracle.com/eyeonai   What if you could fine-tune an AI model without any labeled data—and still outperform traditional training methods?   In this episode of Eye on AI, we sit down with Jonathan Frankle, Chief Scientist at Databricks and co-founder of MosaicML, to explore TAO (Test-time Adaptive Optimization)—Databricks' breakthrough tuning method that's transforming how enterprises build and scale large language models (LLMs).   Jonathan explains how TAO uses reinforcement learning and synthetic data to train models without the need for expensive, time-consuming annotation. We dive into how TAO compares to supervised fine-tuning, why Databricks built their own reward model (DBRM), and how this system allows for continual improvement, lower inference costs, and faster enterprise AI deployment.   Whether you're an AI researcher, enterprise leader, or someone curious about the future of model customization, this episode will change how you think about training and deploying AI.   Explore the latest breakthroughs in data and AI from Databricks: https://www.databricks.com/events/dataaisummit-2025-announcements Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI  

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. What if your blood could reveal the future of your health - years before symptoms ever appear? In this episode of Eye on AI, Craig Smith sits down with Ash Anwar, co-founder of Molecular You, to explore how AI and advanced biomarker analysis are transforming how we detect and prevent disease.  From a real-life case where stage 1 pancreatic cancer was caught early, to the science behind tracking 250+ dynamic biomarkers, Ash breaks down how Molecular You is shifting healthcare from reactive treatment to proactive longevity.  They dive into the limitations of genetic testing, the power of machine learning models trained on clinical data, and how personalized action plans are helping individuals take control of their health in real time.  If you're curious about the intersection of AI, diagnostics, and the future of preventive medicine—this is a conversation you won't want to miss. Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) How AI Can Predict Disease Before It Happens   (02:02) Meet Ash Anwar: From Scientist to Health Tech Leader   (06:31) What Is Molecular You and How It Works   (09:43) Why Biomarker Tracking Over Time Is a Game-Changer   (15:46) How Molecular You Detected Stage 1 Pancreatic Cancer   (23:15) Biomarkers vs Genetics: What Really Matters   (28:11) The AI Models Behind Early Disease Detection   (32:37) How the Product Works for Clinics and Consumers   (35:05) Who They Compete With and What Makes Them Different   (37:34) Research vs Product: The Cancer Risk Challenge   (43:43) How Often Should You Get Tested?

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. What does it really take to turn cutting-edge AI research into a successful foundation model company?   In this episode of Eye on AI, we sit down with Anjney Midha, General Partner at a16z, to unpack how he helps scientists and researchers transform their breakthroughs into scalable, real-world AI businesses.    From his early backing of Anthropic to launching Mistral and Black Forest Labs, Anjney shares a behind-the-scenes look at how AI infrastructure companies are born.   We dive into the critical challenges of model reliability, evaluation beyond academic benchmarks, and the rise of hybrid architectures combining transformers with diffusion and LSTMs.   If you're building in AI or investing in it, this is the roadmap to what's next. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI   (00:00) Turning AI Research into Real Companies   (02:08) Anjney's Journey into Venture Capital   (05:44) The Birth of Anthropic   (08:26) Backing Mistral and Stable Diffusion   (13:16) Are Transformers Really Enough?   (18:36) Why AI Evaluation Is Broken   (22:10) Making AI Models More Interpretable   (28:38) The Real Potential of AI Agents   (32:43) How a16z Spots AI Breakthroughs   (37:45) Investing Like It's the 1970s   (43:31) What AI Voice Tech Needs Right Now (46:32) Models vs Products   (51:17) What's Holding Back AI Agents   (55:41) Anjney Startup Investing Strategy   

What happens when you combine 8 billion minutes of voice data with a full-stack AI engine?    Yes, that's what Dialpad is doing.   In this episode, Brian Peterson, CTO and Co-Founder, breaks down how they've built an AI-powered communications platform from the ground up.    From real-time sales coaching and AI-driven support agents to predictive analytics that can spot churn before it happens, Brian shares why owning the full stack — infrastructure, LLMs, and data  is the only way to deliver truly intelligent customer experience.   If you're curious about the future of AI in business communication, this is the episode to watch. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Brian's Founding Story   (03:56) What Dialpad Actually Does Today   (05:17) Is Voice the Most Valuable Untapped Data Source? (07:41) Inside DialpadGPT (10:10) AI Solutions for Sales, Support & Collaboration   (12:24) Owning the Entire Customer Journey with Unified Comms   (14:11) How Dialpad Stays Ahead in the AI Race   (17:50) Real-Time AI Coaching & Playbooks  (22:32) Why Most Enterprises are Behind in AI Adoption   (25:28) Action-Oriented AI Agents   (32:40) What's Next for AI in Customer Communication

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.     What if AI agents needed digital passports to act on your behalf?   In this episode, Ankur Banerjee, Co-Founder and CTO of cheqd.io, reveals how decentralized identity is becoming the foundation of the AI agent economy.    From booking Taylor Swift tickets with an agent to proving you're a real person online, we explore why identity and trust are the hidden infrastructure shaping the future of AI.   Ankur explains how cheqd is building privacy-first tools that let AI agents verify who they are, what they can do, and who they're working for, all without handing over your data to big tech. We dig into the rise of digital credentials, the limits of biometrics, and how protocols like MCP are making the internet safe for autonomous agents.   If you've ever wondered how AI will operate on your behalf in the real world, this conversation offers a glimpse into what's coming next.   Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI     (00:00) Why AI Needs Identity (02:16) Ankur's Path to cheqd (05:39) Delegating Tasks to AI Agents (11:26) Identity Lessons from Governments (17:25) Trusting AI with Digital Credentials (23:42) The Problem with Biometrics (30:49) Web Standards for Agent Identity (36:46) MCP and Agent Interoperability (48:47) Bridging Web2 and Web3 Identity (55:18) Why Companies Should Care About Decentralized ID

Can Generative AI Be Secured? Amazon's Chief Security Officer Weighs In   In this episode of Eye on AI, Amazon's Chief Security Officer Stephen Schmidt pulls back the curtain on how Amazon is using AI-powered cybersecurity to defend against real-world threats. From global honeypots to intelligent alarm systems and secure AI agent networks, Steve shares never-before-heard details on how Amazon is protecting both its infrastructure and your data in the age of generative AI.   We dive deep into: Amazon's MadPot honeypot network and how it tracks adversaries in 90 seconds The role of AI in threat detection, alarm triage, and code validation Why open-source vs. closed-source models are a real security debate The critical need for data privacy, secure LLM usage, and agent oversight Amazon's $5M+ Nova Trusted AI Challenge to battle adversarial code generation Whether you're building AI tools, deploying models at scale, or just want to understand how the future of cybersecurity is evolving—this episode is a must-listen.   Don't forget to like, subscribe, and turn on notifications to stay updated on the latest in AI, security, and innovation.     Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Preview (00:52) Stephen Schmidt's Role and Background at Amazon (02:11) Inside Amazon's Global Honeypot Network (MadPot) (05:26) How Amazon Shares Threat Intel Through GuardDuty (08:06) Are Cybercriminals Using AI? (10:28) Open Source vs Closed Source AI Security Debate (13:09) What Is Amazon GuardDuty (17:44) How Amazon Protects Customer Data at Scale (20:18) Can Autonomous AI Agents Handle Security? (25:14) How Amazon Empowers SMBs with Agent-Driven Security (26:18) What Tools Power Amazon's Security Agents? (29:25) AI Security Basics (35:34) Securing AI-Generated Code (37:26) Are Models Learning from Our Queries? (39:44) Risks of Agent-to-Agent Data Sharing (42:08) Inside the $5M Nova Trusted AI Security Challenge (47:01) Supply Chain Attacks and State Actor Tactics (51:32) How Many True Adversaries Are Out There? (53:04) What Everyone Needs to Know About AI Security