Intel on AI

Kieran Flanagan, SVP of Marketing at HubSpot and former CMO at Zapier, unpacks how AI is reshaping go-to-market strategies. He shares real examples of companies transforming customer acquisition and retention with AI, and explains where the biggest enterprise-ready impacts are emerging—lead scoring, predictive forecasting, and hyper-personalization. Kieran also dives into how leaders can introduce AI into GTM structures without chaos, why AI agents may become co-pilots for product launches, and how to strike the right balance between efficiency and innovation. Along the way, he offers a glimpse into the AI-driven marketing playbook he would build today, and the GTM innovations from startups that excite him most. #IntelAI #HubSpot #Go-to-Market #AI-Support-Agents #AI-adoption #Future-proof-AI-marketing

In this episode, we sit down with Anna Farberov, General Manager at PepsiCo Labs, for a wide-ranging conversation on how AI is reshaping one of the world's largest food and beverage companies. Anna shares how PepsiCo Labs scouts and integrates emerging technologies to drive innovation across supply chains, production, and retail, and why the lab plays such a critical role in scaling transformation inside a global enterprise. We explore how AI is helping leaders manage the complexity of fast-moving production lines, optimize materials and storage, and unlock efficiency gains in operations that often go unseen by consumers. Anna also shares real-world examples of AI predicting demand, improving decision-making in retail, and supporting employees in ways that boost productivity without adding friction. Looking ahead, she reflects on what executives should prioritize as they begin their AI journey, the pitfalls to avoid, and the breakthroughs she sees coming to the food industry over the next five years. Whether you're an innovator, a business leader, or simply curious about how AI is powering the future of FMCG, this episode offers a practical and inspiring look at the road ahead.

Tomi Virkki, a leader in PMI's technology transformation team, joins the conversation to share how the company is industrializing AI at scale. As one of the architects behind PMI's AI Factory, Tomi has been driving the shift from scattered pilots to enterprise-wide, value-driven solutions. He explains how PMI governs the full lifecycle of GenAI use cases—from ideation to impact—while balancing governance with innovation. The discussion explores the biggest blockers to scaling AI, how to measure business value, and why change management and employee enablement are critical to success. Listeners will gain a behind-the-scenes view of how large enterprises can build confidence in AI, align cross-functional teams, and unlock both top- and bottom-line growth through GenAI. #AIIndustrialization #ResponsibleAI #GenAIIndustrialization #PMIAIFactory #ScalingAI #PhilipMorrisInternational

Miami is emerging as a global hub for artificial intelligence, and at the forefront of this movement is Burhan Sebin, Chief AI Officer at eMerge Americas. In this episode, Burhan takes us inside the origins of the Miami AI Hub, the unique opportunities and challenges of building an AI ecosystem in Florida, and how strategic partnerships with organizations like Hugging Face are fueling open innovation. He also shares how the Miami AI School is preparing the next generation of talent, what to expect at the upcoming Miami AI Summit, and why agentic AI could be the next big leap for the industry. From developer potential to ecosystem "layers," Burhan breaks down the vision driving Miami's AI future. #OpenSourceAI #IntelAI #MiamiAI #AgenticAI

As AI models grow more powerful, the question of where they run is becoming just as important as what they do. In this episode, Brandon Weng, Co-Founder and CEO of Fluid Inference, unpacks what it takes to move AI from massive data centers to everyday devices—and why that shift matters. Brandon shares the story behind Fluid Inference, a company focused on making it easier for developers to deploy large AI models like transformers on consumer hardware. From pivoting away from his previous project, Slipbox, to the technical and philosophical choices that shaped Fluid's direction, he walks us through the thinking behind local-first AI. We explore the tradeoffs between cloud-based and on-device inference—touching on privacy, cost, control, and performance—and the hardware breakthroughs that are making edge AI more viable, including integrated NPUs in devices like Intel's AI PCs. #EdgeAI #OnDeviceInference #AIOptimization #PrivacyFirst #OpenSourceAI #LocalAI

Explore how Agentic AI is reimagining enterprise workflows, industry processes, and leadership priorities with Baris Sarer, Global AI Leader for the Technology, Media, and Telecommunications (TMT) Industry at Deloitte. Baris shares Deloitte's perspective on the "Age of With" and what it means for enterprises adopting autonomous agents at scale—from unlocking measurable business value to ensuring trust, governance, and accountability. He also offers insights into real-world use cases, surprising regional trends in AI adoption, and how C-suite leaders can start experimenting with Agentic AI—whether they're early movers or feel late to the game. Tune in for a practical, forward-looking discussion on turning Agentic AI from a futuristic concept into a strategic advantage. #AgenticAI, #Deloitte, #AITransformation, #EnterpriseAI, #AIGovernance, #ProcessRedesign, #AILeadership, #IntelAI

AI adoption is moving fast—but making it simple, scalable, and power-efficient is where Falcons.AI stands out. In this episode, Bobbi Stattelman, Chief Operating Officer at Falcons.AI, shares how the company has delivered over 500 million model downloads while keeping its focus on practical, lightweight AI that works across devices and industries. From leading the world's top-performing NSFW detection model to helping enterprises run AI on the edge with minimal power draw, Falcons.AI is showing what accessible innovation looks like. Bobbi explains how the team thinks about AI that's fast, secure, and easy to use, and why simplifying deployment is key to enterprise readiness. She also talks through the growing role of open source in AI adoption, and how Falcons.AI bridges the gap between cutting-edge research and operational efficiency. You'll hear how leaders can think differently about performance vs. sustainability, and what their Intel partnership reveals about building real-world, power-aware AI solutions. Whether you're running edge devices, building AI tools, or leading innovation strategy, this conversation offers a clear look into how AI is evolving—and how to adopt it without adding unnecessary complexity. #FalconsAI #OnDeviceAI #AISafety #SustainableAI #EdgeAI #AIForGood #Intel

Discover how Agentic AI is reshaping industries that touch lives every day with Stacey Shulman, Vice President and GM of Health, Education, and Consumer Industries at Intel. In this episode, Stacey shares how Intel is helping healthcare providers improve patient outcomes without losing the human touch, and how AI can move beyond efficiency to true transformation in diagnosis, treatment, and patient experience. She also explores the future of personalized learning, what's next for AI tutors and adaptive platforms, and how Agentic AI is redefining consumer engagement. Along the way, Stacey outlines the biggest barriers leaders face in adopting advanced AI systems—and the strategies to overcome them. You'll also hear how Intel's integrated approach—combining hardware, software, and ecosystem partnerships—is accelerating real-world impact today, and which AI breakthroughs could most profoundly improve everyday life in the decade ahead. Tune in for a forward-looking conversation on building AI that serves people first, at scale.

AI isn't just transforming the software stack — it's reshaping the very machines powering modern business. Jennifer Larson, General Manager of Commercial Client Segments at Intel, breaks down why the distinction between workstations and high-end desktops matters more than ever, and how Intel is engineering platforms designed for creators, engineers, and enterprise users navigating increasingly complex workloads. The conversation explores the rise of small language models, on-device inference, and local AI — technologies that promise new levels of performance, privacy, and productivity right at the edge. Larson also sheds light on how Intel defines performance in an AI-driven world, how evolving security demands are influencing hardware strategy, and the priorities CIOs and CTOs should keep top of mind as 2025 approaches. Packed with insight and foresight, this discussion offers a grounded look at where commercial computing is headed next. #AIPC #AIWorkstation #CommercialPCs #On-DeviceAI #EdgeComputing #IntelAI #LocalAI #AIProductivity

Deepfakes are no longer science fiction—they're a fast-growing threat to consumers, businesses, and the trust we place in digital content. In this episode with Leena Elias, Chief Product Officer at Gen Digital, we explore how Norton and Intel are joining forces to fight back with AI-powered protection built directly into the next generation of AI PCs. We break down what deepfakes are, why they matter, and how running detection locally on the device creates stronger, faster security than cloud-only solutions. Our conversation also dives into the broader impact of AI on cybersecurity—both the risks and the opportunities—as well as how Norton is evolving its strategy to meet this new era of threats. From simplifying highly technical solutions for everyday users to anticipating what comes next, you'll hear how Norton and Intel are shaping a safer digital future.

Turning AI from promising experiments into billion-dollar business value requires more than powerful hardware—it takes strategy, scalability, and responsibility. In this episode, David Ellison, Chief Data Scientist & Director of AI Engineering at Lenovo, shares how the company's AI Discover Center of Excellence has generated more than $1 billion in revenue by moving beyond proofs of concept to enterprise-scale deployments. David breaks down why CPU-based inferencing is becoming a cost-efficient alternative to GPUs, how innovations like Intel's AMX, AVX, and OpenVINO toolkit are reshaping performance, and what enterprises can learn from real-world applications—from NASCAR's Smart Pit Box to logistics at USPS. The conversation also explores responsible AI practices, offering guidance for C-suite leaders balancing performance, cost, and trust. Looking ahread, David shares where CPU-based AI inferencing is poised to make the biggest impact in the next few years.

AI at the Edge is more than a technical shift—it's where intelligence meets the physical world. In this episode, Matthew Formica, Senior Director and Head of Edge Product Marketing & AI PC/Edge AI Software Developer Relations at Intel, unpacks how the company is shaping the future of AI at the Edge and why this space is becoming a critical frontier for innovation. Matthew shares the untold story of Intel's Edge business, the real-world value of Edge AI for industries from retail to logistics, and how robotics is emerging as a powerful proving ground for AI in action. He discusses the role of OpenVINO and the new Model Hub in accelerating AI deployment, the momentum of AI PCs, and what it takes to support developers building solutions that demand performance, power efficiency, and real-time decision-making. Drawing on his diverse background in developer relations, product marketing, and corporate strategy, Matthew offers practical guidance for business leaders curious about AI but unsure where to start. He also looks ahead to the next 12–18 months, sharing the trends and breakthroughs he believes will redefine the Edge AI landscape.

AI is transforming communication—but for the Deaf and hard-of-hearing community, the stakes are even higher. In this episode, Mariam Rahmani, Senior Director of AI at Sorenson, shares how her team approaches AI innovation with accessibility at its core. From developing computer vision models for sign language translation to navigating the real-world constraints of ethical deployment, she explains what it takes to build AI that serves people—not just use cases. Mariam discusses how Sorenson prioritizes projects that drive tangible impact, the challenges of measuring success in accessibility, and the unique hurdles AI teams face when designing for underserved communities. She also reflects on her journey through academia, corporate innovation at Intel, and now mission-driven work at Sorenson—and how those experiences have shaped her thinking around scalable, responsible AI. Whether you're building AI products, leading technical teams, or exploring how technology can drive inclusion, this conversation sheds light on the practical and human-centered realities of AI for accessibility.

Connected data is becoming a core competitive advantage in AI, and Neo4j is helping organizations harness it to deliver intelligent experiences at scale. In this episode, Neha Bajwa, Vice President of Product Marketing at Neo4j, explains how graph technology transforms the way companies manage data, derive insights, and operationalize AI by contextualizing information through relationships. Unlike traditional databases, graph databases reveal hidden patterns in highly connected data, making them ideal for modern AI systems that demand rapid, relevant, and explainable access to organizational knowledge. You'll hear how cities like London use graph-powered digital twins to reduce traffic congestion, and how companies are cutting cybersecurity response times with graph-based detection. Neha also breaks down the rise of GraphRAG—combining Retrieval-Augmented Generation with graph databases to ground generative AI models in structured, connected knowledge for higher accuracy and fewer hallucinations. This approach enables organizations to unify data across disconnected systems without heavy migrations, creating explainable AI critical for regulated industries. She shares how Klarna consolidated 1,200 applications into a single platform using Neo4j's knowledge graph and agentic AI, building a scalable foundation for continuous innovation. As industries push for AI with real returns, the focus has shifted from asking what AI can do to how quickly it can drive business outcomes with a data infrastructure that supports it. Tune in for a practical, clear look at how Neo4j is helping organizations build connected, AI-ready data strategies to accelerate adoption and deliver real impact.

AI adoption is shifting from proof-of-concept to enterprise execution, and Google Cloud is helping organizations turn ambition into measurable outcomes through clarity, customization, and speed to value. In this episode, Riyaz Habibbhai, Director of Product Marketing at Google Cloud, outlines why simplicity, security, and strategic alignment are essential for scalable AI, and how platforms like AgentSpace enable companies to deploy and manage intelligent agents across workflows in one place. He explains how Google's vertically integrated stack—from TPUs and GPUs to Vertex AI—gives customers the flexibility to combine proprietary and open-source tools, fitting AI into unique workflows rather than forcing a one-size-fits-all approach. You'll hear how industries are seeing clear ROI in customer service and software development and why the real opportunity lies in customizing AI for specific business contexts, whether in logistics, manufacturing, or financial operations. Riyaz also shares why product marketers and business leaders need to actively use AI to communicate its value effectively, turning great products into clear, compelling stories that drive adoption. Tune in for a thoughtful, pragmatic look at how Google Cloud is helping companies move from AI experimentation to orchestration at scale, making AI a core business capability that delivers real impact. #AIProductMarketing #GoogleCloud #AgentOrchestration #EnterpriseAI #AIInnovation #AgentSpace #AIatScale #CustomAI #AIIntegration #TechLeadership #AIinBusiness #AIAdoption #GenerativeAI #CustomerEngagement #AIWorkflow #AIandCreativity

Learn how companies are turning AI ambition into real business outcomes with Ramtin Davanlou, CTO of Accenture's partnership with Intel. In this episode, Ramtin outlines the key ingredients for scaling generative AI across the enterprise—from building a strong data foundation and aligning use cases with ROI, to choosing the right models and forming powerful partnerships. He explains why treating AI like a core business capability—not a science experiment—is critical, and how Accenture is helping clients move from pilot projects to full-scale transformation. You'll also hear his take on the future of human-AI collaboration, the rise of intelligent automation in physical environments, and why every team—not just data scientists—must be part of the AI conversation. Tune in for a thoughtful, pragmatic look at what it really takes to operationalize GenAI at speed and scale.

Discover how emotionally intelligent AI is changing the way enterprises interact, decide, and operate in this conversation with Ted Shelton, Chief Operating Officer at Inflection AI. The episode unpacks the rise of empathetic systems—from redefining customer support to enabling more human-like collaboration across teams. Ted shares practical use cases around Pi, an AI assistant designed with emotional intelligence and explains how businesses can move beyond transactional AI to create more meaningful engagement. The discussion also covers strategies for overcoming legacy data issues, the value of private AI in regulated industries, and the leadership mindset required to embrace these shifts. Tune in for a grounded, real-world look at designing AI that understands not just what users ask—but how they feel.

Explore how GenAI is reshaping enterprise infrastructure, marketing, and customer impact with Varun Chhabra, Senior Vice President of Product Marketing at Dell Technologies. Varun shares Dell's perspective on deploying AI at scale—from the launch of Intel's Xeon 6 and Gaudi 3 accelerators to transforming how product messaging is created and delivered. He also offers a candid look at Dell's own GenAI adoption journey, what it takes to lead change across a large organization, and how AI can be a powerful force for productivity, personalization, and even educational equity. Tune in for a thoughtful, real-world discussion on making AI work—beyond the buzzwords.

Discover Building Scalable, Sustainable AI Infrastructure with Ray Pang, Senior Vice President of Technology and Business Enablement at Supermicro. Ray unpacks how Supermicro is tackling the challenges of AI infrastructure at scale—combining high-performance computing with a deep commitment to sustainability. Learn how Supermicro approaches green computing, from energy-efficient server design to innovations in liquid cooling, and why partnerships are key to accelerating AI innovation. Ray also discusses the rise of billion-dollar AI deployments, the critical role of ecosystem collaboration, and what organizations must consider to future-proof their data centers in a rapidly evolving AI landscape.

Discover AI at the Edge with Dan Rodriguez, Corporate Vice President and General Manager of the Network and Edge Solutions Group at Intel. Dan shares how Intel is driving innovation at the intersection of AI, 5G, and edge computing—powering intelligent solutions across industries. Explore the opportunities and challenges companies face when deploying AI at the edge, how Intel is collaborating with partners like Siemens Healthineers, and what makes recent announcements from Intel so significant. Dan also breaks down key trends shaping the future of edge AI and offers practical advice for organizations looking to scale their efforts.

Explore how AI is transforming work and productivity with Sandra Andrews, Global GM, Surface Go-To-Market at Microsoft. Sandra joined us to unpack what an AI-first device strategy really means for today's enterprises. From the rising importance of on-device intelligence and NPUs to how Microsoft's Surface and Copilot are being used to solve real business challenges, Sandra shares compelling insights from the field—including takeaways from her recent visits to Japan and Mobile World Congress. We also explore how always-connected computing is shaping AI's next chapter, what's ahead for Surface + Copilot PCs, and why the right hardware matters more than ever for decision-makers navigating the future of work.

Explore how AI is tranforming healthcare with Peter Shen, Head of Digital and Automation at Siemens Healthineers. From improving diagnostics and treatment planning to enhancing patient outcomes with precision medicine, Peter shares insights on multimodal AI, the power of edge computing in imaging and diagnostics, and the growing role of AI-enabled medical devices. He also reflects on his CES presentation, the challenges of achieving data interoperability, and his testimony before Congress on AI's impact. Tune in for an in-depth look at how AI is reshaping the future of medicine and optimizing healthcare workflows.

In this episode of the Intel on AI podcast, we welcome Ryan Asdourian, EVP & Chief Marketing Officer at Lumen Technologies, to explore how AI is reshaping industries through cutting-edge infrastructure. Ryan discusses how Lumen is enabling businesses to build AI-ready environments with advanced connectivity, edge computing, and secure data movement. We dive into the role of high-speed, low-latency networks in optimizing AI applications and highlight real-world use cases where AI and network infrastructure create economic value. Ryan also shares insights on Lumen's collaboration with enterprises and what it means for businesses looking to accelerate innovation. Beyond technology, we examine AI's impact on workforce transformation, digital inclusion, and sustainability, as well as the evolving intersection of AI and telecom. Whether you're a business leader integrating AI or an industry professional exploring new opportunities, this episode is packed with valuable insights.

Welcome to the first episode in our 2025 season of Intel on AI. We sit down with Luke Norris, founder and CEO of Kamiwaza AI to explore how enterprises can unlock trillions of AI inferences per day with hardware-agnostic, scalable AI infrastructure. We discuss the Fifth Industrial Revolution and the rise of AI-native enterprises, why AI inference—not training—is the real bottleneck, and how the new AI supply chain is evolving with custom silicon, cloud interoperability, and multi-vendor strategies. Plus, we dive into the AI Leverage Index (ALI) as a key metric for enterprise intelligence, the rise of autonomous AI agents, and the shift toward inference-based AI monetization. Don't miss this conversation on the future of AI-driven business. Subscribe for more AI insights!

Learn about building cutting-edge AI tools, tailored for internal use with Intel experts Boaz Efroni Rotman and Barbara Roos. They dive into the creation of IGPT and VITA, Intel's innovative solutions for secure information sharing and productivity, and share insights on balancing generalized versus specialized AI tools. Whether you're curious about AI adoption strategies, tackling data challenges, or the future of CRM, this episode is packed with actionable advice for businesses navigating the AI revolution. RESOURCES: · Vita white paper: https://www.intel.com/content/www/us/en/content-details/834569/content-details.html · Sales assists white paper: https://www.intel.com/content/dam/www/central-libraries/us/en/documents/improving-sales-account-coverage-with-ai-paper.pdf

Explore real-world applications driving sustainability, productivity, and accessibility, from disaster prediction to personalized banking and interactive kiosks. Join Scott Tease, VP and GM of Lenovo's Infrastructure Solutions Group as we discuss cutting-edge innovations like liquid cooling systems, which enhance energy efficiency in data centers and learn how AI is shifting from the cloud to the edge, making advanced technology accessible and sustainable for businesses and consumers alike. Scott also highlights Lenovo's commitment to sustainability, discussing innovative approaches to recycling and reducing environmental impact while delivering business value.

Dive into the transformative potential of Retrieval Augmented Generation (RAG) with Intel's Bill Pearson and Deloitte's Baris Sarer. In this episode, they discuss how RAG combines enterprise data with large language models to unlock new efficiencies and insights. From tackling data governance and security challenges to exploring cutting-edge solutions at the edge and in the cloud, this conversation unpacks the real-world applications, benefits, and future of AI-driven data management in the enterprise. Learn more about Intel AI for Enterprise RAG.

Learn about the development of low-resource language models with Ian Gilmour, founder of Euler Digital and creator of Bezoku. Ian shares how Bezoku evolved from AI Forum, addressing the challenge of creating AI models for languages with limited data. He emphasizes the need for low-resource language models and their potential use cases, like polling and surveying, through techniques like reinforcement learning. Gilmour also delves into technical strategies, such as homomorphic encryption and synthetic data, for building secure and efficient AI solutions.

Tune in to learn about the future of AI deployments, from cost-effective CPU instances to the seamless integration of multiple models for robust AI systems with Jeff Boudier from Hugging Face and Sudeep Sharma from Amazon EC2. Jeff shares Hugging Face's mission to democratize machine learning, highlighting the ease and affordability of using diverse models on their platform. Sudeep dives into how AWS is tackling evolving customer demands by delivering next-gen Intel-powered instances, including the Gen7 Intel Sapphire Rapids processors, which optimize AI and machine learning tasks. Together, they discuss the challenges and innovations in serving customers with scalable, efficient solutions and how Hugging Face and AWS are partnering to offer more choices for AI builders.

Learn about the origins of Oracle's Roving Edge Device, and how the next-gen iteration with updated Intel processors is leading to breakthrough advancements in defense, agriculture, and healthcare. Recorded live at Oracle CloudWorld 2024 in Las Vegas with Matt Leonard, VP of OCI Edge and Cloud Infrastructure, Peter Guerra, Global VP of Data and AI, and guest host, Andy Morris from Intel Enterprise AI. The conversation also highlights Oracle and Intel's 31-year partnership and innovations in AI deployment at the edge. Guests include: Matt Leonard is Vice President of OCI Edge Cloud product management at Oracle, leading product strategy and vision for bringing the power of cloud computing to the edge. Matt's goal is to enable customers to deploy and manage applications anywhere. With over 20 years of experience in product management, integration, and IT advisory, Matt has a proven track record of delivering successful products and solutions for leading tech companies such as Google, Microsoft, and Amazon. Peter Guerra, Global Vice President, Data & AI at Oracle, is a proven Data & AI executive with over 20 years of experience with commercial and public sector customers. Prior to Oracle, he led AI teams at Microsoft, AWS, Accenture and Booz Allen Hamilton. His career has been to focus on data & AI solutions for customers in defense, public sector, health, energy, and retail. He is a technical expert in AI and data platforms, having led numerous deployments and algorithm development solutions, including contributing to the Apache Accumulo and Apache Nifi projects. He has written thought pieces for O'Reilly, published papers in IEEE, and has spoken at industry events such as NVIDIA's GTC, Oracle CloudWorld, Blackhat, and more. Peter holds a Bachelor of Science in Computer Science, a Bachelor of Art in English from University of Maryland, and an MBA with Information Systems concentration from Loyola University.

In this episode, Sean Phan from Pixel ML explores the transformative power of agentic workflows in automating complex processes and enhancing operational efficiency across industries. He shares insights on how AI-driven automation is being used to scale event engagement and streamline workflows in large enterprises. Sean also discusses the future potential of these workflows to revolutionize various industries.

Explore the transformative potential of AI in the enterprise, guided by insights from Anil Nanduri, Vice President and Head of Intel AI Accelerator Office. Learn why integrating AI is crucial for staying competitive and uncover the benefits of scalable solutions. This episode delves into a flexible, secure approach to AI, ensuring seamless integration with existing enterprise systems and maximizing ROI. Tune in to discover how enterprises can leverage AI to drive innovation and efficiency. #IntelAI @IntelAI

Join us in this episode as we dive into the transformative impact of responsible AI with David Ellison, Chief Data Scientist at Lenovo. Discover how Lenovo's Responsible AI Committee and its six guiding principles are setting new standards for privacy, security, and diversity in AI. David shares practical techniques such as data minimization and differential privacy, highlighting their roles in promoting transparency, accountability, and sustainable innovation in AI. Learn how these practices are not only shaping Lenovo's AI strategy but also paving the way for a more ethical and inclusive future in technology. #IntelAI @IntelAI

Whether you're an AI enthusiast or a business looking to integrate AI into your operations, this episode offers valuable insights into the rapidly evolving AI landscape. Join Seamus Jones, Director of Technical Marketing/Engineering at Dell, as he explains how Dell is creating comprehensive AI solutions. These solutions encompass everything from AI infrastructure and hardware to software stacks, making AI deployment easier for businesses. Explore exciting AI use cases such as computer vision in retail and multimodal applications in logistics. Learn how enterprises can leverage AI accelerators like the new Intel Gaudi 3 to enhance performance and reduce costs. Discover how AI is transforming industries and what it means for the future of enterprise computing. Tune in to find out how Dell, in partnership with Intel, is making significant strides in AI deployment and infrastructure. Don't miss this episode packed with expert insights and practical advice on harnessing the power of AI in your business. See: https://dell.com/AI https://infohub.delltechnologies.com

Learn about the importance of flexibility and governance in AI model management as Robert Daigle, Director of Global AI Business at Lenovo, discusses the future of AI deployment across various computing environments. He highlights the collaborative efforts of Lenovo and partners in addressing specific vertical use cases such as retail, healthcare, and smart cities, demonstrating how AI can drive real-time analytics and deliver significant business value. Daigle also touches on the ethical considerations and localized strategies Lenovo employs to ensure responsible AI implementation globally.

Explore the transformative power of AI in business leadership in this engaging episode of Intel on AI. Join hosts Ryan Carson and Tony Mongkolsmai as they interview Nathaniel Whittemore, renowned AI thought leader, founder and CEO of Super Intelligent, and host of the AI Daily Brief. Learn how executives can implement artificial intelligence solutions in their daily operations to drive significant improvements and strategic outcomes. Nathaniel provides actionable advice on starting with non-controversial AI deployments that optimize productivity and mitigate the challenges of rapid AI innovation. Tune in for invaluable insights on leveraging Intel's AI technology in leadership roles. Subscribe and stay updated with the latest in AI applications and technology advancements. #IntelAI @IntelAI

Discover the cutting-edge advancements in artificial intelligence with Vasudev Lal, Principal AI Research Scientist at Intel. This episode delves into the benefits of multimodal AI and the enhanced validity achieved through self-supervised learning. Vasudev also explores the applications of counterfactual reasoning in AI and the efficiency gains from using AI agents. Additionally, learn how leveraging multiple Gaudi 2 accelerators can significantly reduce LLM training times. Stay updated with the latest in AI technology and innovations by following #IntelAI and @IntelAI for more information.

Learn about real-world applications of AI in manufacturing as Rao Desineni shares how Intel incorporates visual AI in their defect detection processes along with autonomous machine learning for improving product yields & quality. #IntelAI @IntelAI

Learn the latest on open ecosystems, AI data foundations and Meta's new Llama 3 with Dr. Wei Li, VP/GM of AI Software Engineering at Intel.

Dive deep into the ever-evolving landscape of AI with Intel's VP of AI Marketing, Nuri Cankaya, as he navigates the intricacies of cutting-edge AI models and their impact on businesses.

In this episode of Intel on AI host Amir Khosrowshahi talks with Jeff Lichtman about the evolution of technology and mammalian brains. Jeff Lichtman is the Jeremy R. Knowles Professor of Molecular and Cellular Biology at Harvard. He received an AB from Bowdoin and an M.D. and Ph.D. from Washington University, where he worked for thirty years before moving to Cambridge. He is now a member of Harvard's Center for Brain Science and director of the Lichtman Lab, which focuses on connectomics— mapping neural connections and understanding their development. In the podcast episode Jeff talks about why researching the physical structure of brain is so important to advancing science. He goes into detail about Brainbrow—a method he and Joshua Sanes developed to illuminate and trace the "wires" (axons and dendrites) connecting neurons to each other. Amir and Jeff discuss how the academic rivalry between Santiago Ramón y Cajal and Camillo Golgi pioneered neuroscience research. Jeff describes his remarkable research taking nanometer slices of brain tissue, creating high-resolution images, and then digitally reconstructing the cells and synapses to get a more complete picture of the brain. The episode closes with Jeff and Amir discussing theories about how the human brain learns and what technologists might discover from the grand challenge of mapping the entire nervous system. Academic research discussed in the podcast episode: Principles of Neural Development The reorganization of synaptic connexions in the rat submandibular ganglion during post-natal development Development of the neuromuscular junction: Genetic analysis in mice A technicolour approach to the connectome The big data challenges of connectomics Imaging Intracellular Fluorescent Proteins at Nanometer Resolution Stimulated emission depletion (STED) nanoscopy of a fluorescent protein-labeled organelle inside a living cell High-resolution, high-throughput imaging with a multibeam scanning electron microscope Saturated Reconstruction of a Volume of Neocortex A connectomic study of a petascale fragment of human cerebral cortex A Canonical Microcircuit for Neocortex

In this episode of Intel on AI host Amir Khosrowshahi and co-host Mariano Phielipp talk with Chelsea Finn about machine learning research focused on giving robots the capability to develop intelligent behavior. Chelsea is Assistant Professor in Computer Science and Electrical Engineering at Stanford University, whose Stanford IRIS (Intelligence through Robotic Interaction at Scale) lab is closely associated with the Stanford Artificial Intelligence Laboratory (SAIL). She received her Bachelor's degree in Electrical Engineering and Computer Science at MIT and her PhD in Computer Science at UC Berkeley, where she worked with Pieter Abbeel and Sergey Levine. In the podcast episode Chelsea explains the difference between supervised learning and reinforcement learning. She goes into detail about the different kinds of new reinforcement algorithms that can aid robots to learn more autonomously. Chelsea talks extensively about meta-learning—the concept of helping robots learn to learn­—and her efforts to advance model-agnostic meta-learning (MAML). The episode closes with Chelsea and Mariano discussing the intersection of natural language processing and reinforcement learning. The three also talk about the future of robotics and artificial intelligence, including the complexity of setting up robotic reward functions for seemingly simple tasks. Academic research discussed in the podcast episode: Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Meta-Learning with Memory-Augmented Neural Networks Matching Networks for One Shot Learning Learning to Learn with Gradients Bayesian Model-Agnostic Meta-Learning Meta-Learning with Implicit Gradients Meta-Learning Without Memorization Efficiently Identifying Task Groupings for Multi-Task Learning Three scenarios for continual learning Dota 2 with Large Scale Deep Reinforcement Learning ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback

In this episode of Intel on AI host Amir Khosrowshahi talks with Joshua Tucker about using artificial intelligence to study the influence social media has on politics. Joshua is professor of politics at New York University with affiliated appointments in the department of Russian and Slavic Studies and the Center for Data Science. He is also the director of the Jordan Center for the Advanced Study of Russia and co-director of the Center for Social Media and Politics. He was a co-author and editor of an award-winning policy blog at The Washington Post and has published several books, including his latest, where he is co-editor, titled Social Media and Democracy: The State of the Field, Prospects for Reform from Cambridge University Press. In the podcast episode, Joshua discusses his background in researching mass political behavior, including Colored Revolutions in Eastern Europe. He talks about how his field of study changed after working with his then PhD student Pablo Barberá (now a professor at the University of Southern California), who proposed a method whereby researchers could estimate people's partisanship based on the social networks in which they had enmeshed themselves. Joshua describes the limitations researchers often have when trying to study data on various platforms, the challenges of big data, utilizing NYU's Greene HPC Cluster, and the impact that the leak of the Facebook Papers had on the field. He also describes findings regarding people who are more prone to share material from fraudulent media organizations masquerading as news outlets and how researchers like Rebekah Tromble (Director of the Institute for Data, Democracy and Politics at George Washington University) are working with government entities like the European Union on balancing public research with data privacy. The episode closes with Amir and Joshua discussing disinformation campaigns in the context of the Russo-Ukrainian War. Academic research discussed in the podcast episode: Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data. Tweeting From Left to Right: Is Online Political Communication More Than an Echo Chamber?

In this episode of Intel on AI host Amir Khosrowshahi talks with Ron Dror about breakthroughs in computational biology and molecular simulation. Ron is an Associate Professor of Computer Science in the Stanford Artificial Intelligence Lab, leading a research group that uses machine learning and molecular simulation to elucidate biomolecular structure, dynamics, and function, and to guide the development of more effective medicines. Previously, Ron worked on the Anton supercomputer at D.E. Shaw Research after earning degrees in the fields of electrical engineering, computer science, biological sciences, and mathematics from MIT, Cambridge, and Rice. His groundbreaking research has been published in journals such as Science and Nature, presented at conferences like Neural Information Processing Systems (NeurIPS), and won awards from the Association of Computing Machinery (ACM) and other organizations. In the podcast episode, Ron talks about his work with several important collaborators, his interdisciplinary approach to research, and how molecular modeling has improved over the years. He goes into detail about the gen-over-gen advancements made in the Anton supercomputer, including its software, and his recent work at Stanford with molecular dynamics simulations and machine learning. The podcast closes with Amir asking detailed questions about Ron and his team's recent paper concerning RNA structure prediction that was featured on the cover of Science. Academic research discussed in the podcast episode: Statistics of real-world illumination The Role of Natural Image Statistics in Biological Motion Estimation Surface reflectance recognition and real-world illumination statistics Accuracy of velocity estimation by Reichardt correlators Principles of Neural Design Levinthal's paradox Potassium channels Structural and Thermodynamic Properties of Selective Ion Binding in a K+ Channel Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters Long-timescale molecular dynamics simulations of protein structure and function Parallel random numbers: as easy as 1, 2, 3 Biomolecular Simulation: A Computational Microscope for Molecular Biology Anton 2: Raising the Bar for Performance and Programmability in a Special-Purpose Molecular Dynamics Supercomputer Molecular Dynamics Simulation for All Structural basis for nucleotide exchange in heterotrimeric G proteins How GPCR Phosphorylation Patterns Orchestrate Arrestin-Mediated Signaling Highly accurate protein structure prediction with AlphaFold ATOM3D: Tasks on Molecules in Three Dimensions Geometric deep learning of RNA structure

In this episode of Intel on AI host Amir Khosrowshahi, assisted by Dmitri Nikonov, talks with Jean Anne Incorvia about the use of new physics in nanocomputing, specifically with spintronic logic and 2D materials. Jean is an Assistant Professor and holds the Fellow of Advanced Micro Devices Chair in Computer Engineering in the Department of Electrical and Computer Engineering at The University of Texas at Austin, where she directs the Integrated Nano Computing Lab. Dimitri is a Principal Engineer in the Components Research at Intel. He holds a Master of Science in Aeromechanical Engineering from the Moscow Institute of Physics and Technology and a Ph.D. from Texas A&M. Dimitri works in the discovery and simulation of nanoscale logic devices and manages joint research projects with multiple universities. He has authored dozens of research papers in the areas of quantum nanoelectronics, spintronics, and non-Boolean architectures. In the episode Jean talks about her background with condensed matter physics and solid-state electronics. She explains how magnetic properties and atomically thin materials, like graphene, can be leveraged at nanoscale for beyond-CMOS computing. Jean goes into detail about domain wall magnetic tunnel junctions and why such devices might have a lower energy cost than the modern process of encoding information in charge. She sees these new types of devices to be compatible with CMOS computing and part of a larger journey toward beyond-von Neumann architecture that will advance the evolution of artificial intelligence, neural networks, deep learning, machine learning, and neuromorphic computing. The episode closes with Jean, Amir, and Dimitri talking about the broadening definition of quantum computing, existential philosophy, and AI ethics. Academic research discussed in the podcast episode: Being and Time Cosmic microwave background radiation anisotropies: Their discovery and utilization Nanotube Molecular Wires as Chemical Sensors Visualization of exciton transport in ordered and disordered molecular solids Nanoscale Magnetic Materials for Energy-Efficient Spin Based Transistors Lateral Inhibition Pyramidal Neural Network for Image Classification Magnetic domain wall neuron with lateral inhibition Maximized Lateral Inhibition in Paired Magnetic Domain Wall Racetracks for Neuromorphic Computing Domain wall-magnetic tunnel junction spin–orbit torque devices and circuits for in-memory computing High-Speed CMOS-Free Purely Spintronic Asynchronous Recurrent Neural Network

In this episode of Intel on AI hosts Amir Khosrowshahi and Santiago Miret talk with Alán Aspuru-Guzik about the chemistry of computing and the future of materials discovery. Alán is a professor of chemistry and computer science at the University of Toronto, a Canada 150 Research Chair in theoretical chemistry, a CIFAR AI Chair at the Vector Institute, and a CIFAR Lebovic Fellow in the biology-inspired Solar Energy Program. Alán also holds a Google Industrial Research Chair in quantum computing and is the co-founder of two startups, Zapata Computing and Kebotix. Santiago Miret is an AI researcher in Intel Labs, who has an active research collaboration Alán. Santiago studies at the intersection of AI and the sciences, as well as the algorithmic development of AI for real-world problems. In the first half of the episode, the three discuss accelerating molecular design and building next generation functional materials. Alán talks about his academic background with high performance computing (HPC) that led him into the field of molecular design. He goes into detail about building a "self-driving lab" for scientific experimentation, which, coupled with advanced automation and robotics, he believes will help propel society to move beyond the era of plastics and into the era of materials by demand. Alán and Santiago talk about their research collaboration with Intel to build sophisticated model-based molecular design platforms that can scale to real-world challenges. Alán talks about the Acceleration Consortium and the need for standardization research to drive greater academic and industry collaborations for self-driving laboratories. In the second half of the episode, the three talk about quantum computing, including developing algorithms for quantum dynamics, molecular electronic structure, molecular properties, and more. Alán talks about how a simple algorithm based on thinking of the quantum computer like a musical instrument is behind the concept of the variational quantum eigensolver, which could hold promising advancements alongside classical computers. Amir, and Santiago close the episode by talking about the future of research, including projects at DARPA, oscillatory computing, quantum machine learning, quantum autoencoders, and how young technologists entering the field can advance a more equitable society. Academic research discussed in the podcast episode: The Hot Topic: What We Can Do About Global Warming Energy, Transport, & the Environment Scalable Quantum Simulation of Molecular Energies The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning Neuroevolution-Enhanced Multi-Objective Optimization for Mixed-Precision Quantization Organic molecules with inverted gaps between first excited singlet and triplet states and appreciable fluorescence rates Simulated Quantum Computation of Molecular Energies Towards quantum chemistry on a quantum computer Gerald McLean and Marcum Jung and others with the concept of the variational quantum eigensolver Experimental investigation of performance differences between coherent Ising machines and a quantum annealer Quantum autoencoders for efficient compression of quantum data

In this episode of Intel on AI host Amir Khosrowshahi and Milena Marinova talk about using artificial intelligence for professional learning. Milena is currently the Vice President of Data and AI Solutions at Microsoft. At the time of recording this podcast (April 2021), Milena was the visionary and driving force behind the award-winning AI calculus tutoring application Aida and its capabilities platform in the AI Products & Solutions Group, which she founded and led at Pearson. Bringing over 15 years of experience and knowledge in machine learning, neural networks, computer vision, and the commercialization of new technologies, Milena's background includes an MBA from IMD in Lausanne, Switzerland and a B.Sc. with Honors in Computer Science from Caltech. She is a passionate advocate for innovation and has been a Venture Partner with Atlantic Bridge Capital, helping with AI investments and portfolio companies. Milena is also a co-founder and advisor to several startups in Europe and the US and has previously held management positions at the startup incubator Idealab, as well as executive roles at Intel. In the podcast episode Amir and Milena discuss some of the challenges of developing artificial intelligence products, going from academic research into commercial deployment, and the importance of data policy by design. Milena describes some of the lessons she's learned over the years. Academic research discussed in the podcast episode: Learning from Data The Multi-Armed Bandit Problem: Decomposition and Computation Programmable Neural Logic Bubble Blinders: The Untold Story of the Search Business Model Regulating Innovation (conference panel) Intel RealSense Stereoscopic Depth Cameras Smart Robots: From the Lab to the World (podcast) Artificial Intelligence: A Modern Approach Self-supervised learning: The dark matter of intelligence

In this episode of Intel on AI host Amir Khosrowshahi and Luis Ceze talk about building better computer architectures, molecular biology, and synthetic DNA. Luis Ceze is the Lazowska Professor in the Paul G. Allen School of Computer Science and Engineering at the University of Washington, Co-founder and CEO at OctoML, and Venture Partner at Madrona Venture Group. His research focuses on the intersection between computer architecture, programming languages, machine learning and biology. His current research focus is on approximate computing for efficient machine learning and DNA-based data storage. He co-directs the Molecular Information Systems Lab (misl.bio) and the Systems and Architectures for Machine Learning lab (sampl.ai). He has co-authored over 100 papers in these areas, and had several papers selected as IEEE Micro Top Picks and CACM Research Highlights. His research has been featured prominently in the media including New York Times, Popular Science, MIT Technology Review, Wall Street Journal, among others. He is a recipient of an NSF CAREER Award, a Sloan Research Fellowship, a Microsoft Research Faculty Fellowship, the 2013 IEEE TCCA Young Computer Architect Award, the 2020 ACM SIGARCH Maurice Wilkes Award and UIUC Distinguished Alumni Award. In the episode, Amir and Luis talk about DNA storage, which has the potential to be a million times denser than solid state storage today. Luis goes into detail about the process he and fellow researchers at the University of Washington along with a team from Microsoft went through in order to store the high-definition music video "This Too Shall Pass" by the band OK Go onto DNA. Luis also discusses why enzymatic synthesis of DNA might potentially be environmentally sustainable, the advancements being made in similarity searches, and his role in creating the open source Apache TVM project that aims to use machine learning to find the most efficient hardware and software combination optimizations. Amir and Luis end the episode talking about why multi-technology systems with electronics, photonics, molecular systems, and even quantum components could be the future of compute. Academic research discussed in the podcast episode: The biologic synthesis of deoxyribonucleic acid Towards practical, high-capacity, low-maintenance information storage in synthesized DNA DNA Hybridization Catalysts and Catalyst Circuits A simple DNA gate motif for synthesizing large-scale circuits A DNA-Based Archival Storage System Random access in large-scale DNA data storage Landscape of Next-Generation Sequencing Technologies Clustering Billions of Reads for DNA Data Storage Demonstration of End-to-End Automation of DNA Data Storage High density DNA data storage library via dehydration with digital microfluidic retrieval Probing the physical limits of reliable DNA data retrieval Stabilizing synthetic DNA for long-term data storage with earth alkaline salts Molecular-level similarity search brings computing to DNA data storage DNA Data Storage and Near-Molecule Processing for the Yottabyte Era

In this episode of Intel on AI host Amir Khosrowshahi talks with Stephen Wolfram about the current state of artificial intelligence. Stephen is the founder and CEO of Wolfram Research, maker of the Wolfram Mathematica software system and WolframAlpha computational knowledge engine, author of A New Kind of Science, and most recently originator of the Wolfram Physics Project, which is a collaborative effort to find the fundamental theory of physics. In the podcast episode, Stephen talks about the computational universe and the idea that even simple programs possibly have sophisticated abilities under the Principle of Computational Equivalence, but that these abilities are perceived to be useless to humans and therefore underexplored. He discusses the need for shared computational languages that will allow people and machines to mine the wealth of available historic data so that it can be translated into useable knowledge. Amir and Stephen talk about a number of subjects during their two-hour conversation, including Emanuel Kant, Noam Chomsky, if aliens might view a completely different part of physical reality than humans, encoding values for AI content ranking, and why Stephen left academia to develop his own research institute. Stephen discusses his predictions about the limitations of quantum computing, the potential of computing at the molecular scale, and what comes after semiconductor processing. He also explains why Einstein's theory of relatively and spacetime is misunderstood. Amir asks Stephen to explain how multiway systems and the biology of neuroscience can be viewed in harmony. Academic research discussed in the podcast episode: Critique of Pure Reason A Review of B. F. Skinner's Verbal Behavior Perceptrons Workshop on Environments for Computational Mathematics A programming language Modern Cellular Automata: Theory and Applications Space and Time Gravitation My Time with Richard Feynman Some Relativistic and Gravitational Properties of the Wolfram Model The Wolfram Physics Project: A One-Year Update Multicomputation with Numbers: The Case of Simple Multiway Systems Algorithms for Inverse Reinforcement Learning Spiders are much smarter than you think Molecular Computation of Solutions to Combinatorial Problems A Learning Algorithm for Boltzmann Machines The Computational Brain

In this episode of Intel on AI host Amir Khosrowshahi, assisted by Dmitri Nikonov, talks with Ian Young about Intel's long-term research to develop more energy-efficient computing based on exploratory materials and devices as well as non-traditional architectures. Ian is Senior Fellow at Intel and the Director of the Exploratory Integrated Circuits in the Components Research. Ian was one of the key players in the advancement of dynamic and static random-access memory (DRAM, SRAM), and the integration of the bipolar junction transistor and complementary metal-oxide-semiconductor (CMOS) gate into a single integrated circuit (BiCMOS). He developed the original Phase Locked Loop (PLL) based clocking circuit in a microprocessor while working at Intel, contributing to massive improvements in computing power. Dimitri is a Principal Engineer in the Components Research at Intel. He works in the discovery and simulation of nanoscale logic devices and manages joint research projects with multiple universities. Both Ian and Dmitri have authored dozens of research papers, many together, in the areas of quantum nanoelectronics, spintronics, and non-Boolean architectures. In the podcast episode, the three talk about moving beyond CMOS architecture, which is limited by current density and heat. By exploring new materials, the hope is to make significant improvements in energy efficiency that could greatly expand the performance of deep neural networks and other types of computing. The three discuss the possible applications of ferroelectric materials, quantum tunneling, spintronics, non-volatile memory and computing, and silicon photonics. Ian talks about some of the current material challenges he and others are trying to solve, such as meeting operational performance targets and creating pristine interfaces, which mimic some of the same hurdles Intel executives Gordon Moore, Robert Noyce, and Andrew Grove faced in the past. He describes why he believes low-voltage, magneto-electric spin orbit (MESO) devices with quantum multiferroics (materials with coupled magnetic and ferroelectric order) have the most potential for improvement and wide-spread industry adoption. Academic research discussed in the podcast episode: A PLL clock generator with 5 to 110 MHz of lock range for microprocessors Clock generation and distribution for the first IA-64 microprocessor CMOS scaling trends and beyond Overview of beyond-CMOS devices and a uniform methodology for their benchmarking Benchmarking of beyond-CMOS exploratory devices for logic integrated circuits Tunnel field-effect transistors: Prospects and challenges Scalable energy-efficient magnetoelectric spin–orbit logic Beyond CMOS computing with spin and polarization Optical I/O technology for tera-scale computing Device scaling considerations for nanophotonic CMOS global interconnects Coupled-oscillator associative memory array operation for pattern recognition Convolution inference via synchronization of a coupled CMOS oscillator array Benchmarking delay and energy of neural inference circuits