Eye On A.I.

Craig S. Smith
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Eye On A.I.

Eye on A.I. is a biweekly podcast, hosted by longtime New York Times correspondent Craig S. Smith. In each episode, Craig will talk to people making a difference in artificial intelligence. The podcast aims to put incremental advances into a broader context and consider the global implications of the developing technology. AI is about to change your world, so pay attention.

  1. -1 ДН.

    #236 Vall Herard: The Future of AI-Driven Compliance (Saifr.ai)

    This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more. NetSuite is offering a one-of-a-kind flexible financing program. Head to  https://netsuite.com/EYEONAI to know more.     In this episode of Eye on AI, Vall Herard, CEO of Saifr.ai, joins Craig Smith to explore how AI is transforming compliance in financial services.   Saifr.ai acts as a "grammar check" for regulatory compliance, ensuring AI-generated content meets SEC, FINRA, and global financial regulations. Vall explains how Saifr integrates into Microsoft Word, Outlook, and Adobe, reducing compliance risks in marketing, emails, and AI chatbots.   We also discuss Saifr.ai’s partnership with Microsoft, AI’s role in regulated industries, and how businesses can safely adopt generative AI without violating compliance laws. - How does AI reduce compliance friction? - Why is regulatory oversight a barrier to AI adoption? - What does AI safety really mean for financial services? Find out in this deep dive into AI, compliance, and the future of regulation. Like, subscribe, and hit the notification bell for more AI insights!   Strengthen your compliance controls with AI: https://saifr.ai/   Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI (00:00) Introduction to Generative AI and Compliance   (02:47) Meet Vall Herard, CEO of Saifr.ai   (05:28) What Saifr.ai Does and Its Mission   (08:25) How Saifr.ai Ensures Regulatory Compliance   (12:13) Overcoming AI Adoption Barriers in Finance   (19:58) Saifr.ai’s Partnership with Microsoft   (24:11) How SaferAI Integrates with Microsoft Office   (29:33) AI in Podcast and Audio Compliance Review   (33:54) Saifr.ai’s Business Model and Pricing   (38:09) How Saifr.ai Works with Generative AI Chatbots   (42:36) Supporting Multiple Languages for Compliance   (50:08) Future Outlook

    52 мин.

  2. -6 ДН.

    #235 Tyler Xuan Saltsman: How AI is Shaping the Future of Combat & Warfare

    In this episode of the Eye on AI podcast, Tyler Xuan Saltsman, CEO of Edgerunner, joins Craig Smith to explore how AI is reshaping military strategy, logistics, and defense technology—pushing the boundaries of what’s possible in modern warfare.   Tyler shares the vision behind Edgerunner, a company at the cutting edge of generative AI for military applications. From logistics and mission planning to autonomous drones and battlefield intelligence, Edgerunner is building domain-specific AI that enhances decision-making, ensuring national security while keeping humans in control.   We dive into how AI-powered military agents work, including the LoRA (Low-Rank Adaptation) model, which fine-tunes AI to think and act like military specialists—whether in logistics, aircraft maintenance, or real-time combat scenarios. Tyler explains how retrieval-augmented generation (RAG) and small language models allow warfighters to access mission-critical intelligence without relying on the internet, bringing real-time AI support directly to the battlefield.   Tyler also discusses the future of drone warfare—how AI-driven, vision-enabled drones can neutralize threats autonomously, reducing reliance on human pilots while increasing battlefield efficiency. With autonomous swarms, AI-powered kamikaze drones, and real-time situational awareness, the landscape of modern warfare is evolving fast.   Beyond combat, we explore AI’s role in security, including advanced weapons detection systems that can safeguard military bases, schools, and public spaces. Tyler highlights the urgent need for transparency in AI, contrasting Edgerunner’s open and auditable AI models with the black-box approaches of major tech companies.   Discover how AI is transforming military operations, from logistics to combat strategy, and what this means for the future of defense technology.   Don’t forget to like, subscribe, and hit the notification bell for more deep dives into AI, defense, and cutting-edge technology!   Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI 00:00) Introduction – AI for the Warfighter (01:34) How AI is Transforming Military Logistics( 04:44) Running AI on the Edge – No Internet Required (06:49) AI-Powered Mission Planning & Risk Mitigation (14:32) The Future of AI in Drone Warfare (22:17) AI’s Role in Strategic Defense & Economic Warfare (26:34) The U.S.-China AI Race – Are We Falling Behind? (35:17) The Future of AI in Warfare

    39 мин.

  3. 26 ЯНВ.

    #234 Matt Price: How Crescendo is Disrupting Customer Service with Gen AI

    In this episode of the Eye on AI podcast, Matt Price, CEO of Crescendo, joins Craig Smith to discuss how generative AI is reshaping customer service and blending seamlessly with human expertise to create next-level customer experiences.   Matt shares the story behind Crescendo, a company at the forefront of revolutionizing customer service by integrating advanced AI technology with human-driven solutions. With a focus on outcome-based service delivery and quality assurance, Crescendo is setting a new standard for customer engagement.   We dive into Crescendo’s innovative approach, including its use of large language models (LLMs) combined with proprietary IP to deliver consistent, high-quality support across 56 languages. Matt explains how Crescendo’s AI tools are designed to handle routine tasks while enabling human agents to focus on complex, empathy-driven interactions—resulting in higher job satisfaction and better customer outcomes.   Matt highlights how Crescendo is redefining the BPO industry, combining AI and human capabilities to reduce costs while improving the quality of customer interactions. From enhancing agent retention to enabling scalable, multilingual support, Crescendo’s impact is transformative.   Discover how Matt and his team are designing a future where AI and humans work together to deliver exceptional customer experiences—reimagining what’s possible in the world of customer service.   Don’t forget to like, subscribe, and hit the notification bell for more insights into AI, technology, and innovation! Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI (00:00) Introduction to Matt Price and Crescendo   (01:49) The rise of AI in customer service   (05:34) Using AI and human expertise for better customer experiences   (07:47) How Gen AI reduces costs and improves engagement   (09:37) Challenges in customer service design and innovation   (11:32) Moving from hidden chatbots to front-and-center customer interaction   (14:08) Training human agents to work seamlessly with AI   (17:02) Using AI to analyze and improve service interactions   (19:15) Outcome-based pricing vs traditional headcount models   (21:53) Improving contact center roles with AI integration   (25:08) The importance of curating accurate knowledge bases for AI   (28:05) Crescendo’s acquisition of PartnerHero and its impact   (30:39) Scaling customer service with AI-human collaboration   (32:06) Multilingual support: AI in 56 languages   (33:49) The vast market potential of AI-driven customer service   (36:28) How Crescendo is reshaping customer service with AI innovation   (42:42) Building customer profiles for personalized support

    45 мин.

  4. 22 ЯНВ.

    #232 Sepp Hochreiter: How LSTMs Power Modern AI System’s

    In this special episode of the Eye on AI podcast, Sepp Hochreiter, the inventor of Long Short-Term Memory (LSTM) networks, joins Craig Smith to discuss the profound impact of LSTMs on artificial intelligence, from language models to real-time robotics. Sepp reflects on the early days of LSTM development, sharing insights into his collaboration with Jürgen Schmidhuber and the challenges they faced in gaining recognition for their groundbreaking work. He explains how LSTMs became the foundation for technologies used by giants like Amazon, Apple, and Google, and how they paved the way for modern advancements like transformers. Topics include: - The origin story of LSTMs and their unique architecture. - Why LSTMs were crucial for sequence data like speech and text. - The rise of transformers and how they compare to LSTMs. - Real-time robotics: using LSTMs to build energy-efficient, autonomous systems. The next big challenges for AI and robotics in the era of generative AI. Sepp also shares his optimistic vision for the future of AI, emphasizing the importance of efficient, scalable models and their potential to revolutionize industries from healthcare to autonomous vehicles. Don’t miss this deep dive into the history and future of AI, featuring one of its most influential pioneers. (00:00) Introduction: Meet Sepp Hochreiter (01:10) The Origins of LSTMs (02:26) Understanding the Vanishing Gradient Problem (05:12) Memory Cells and LSTM Architecture (06:35) Early Applications of LSTMs in Technology (09:38) How Transformers Differ from LSTMs (13:38) Exploring XLSTM for Industrial Applications (15:17) AI for Robotics and Real-Time Systems (18:55) Expanding LSTM Memory with Hopfield Networks (21:18) The Road to XLSTM Development (23:17) Industrial Use Cases of XLSTM (27:49) AI in Simulation: A New Frontier (32:26) The Future of LSTMs and Scalability (35:48) Inference Efficiency and Potential Applications (39:53) Continuous Learning and Adaptability in AI (42:59) Training Robots with XLSTM Technology (44:47) NXAI: Advancing AI in Industry

    51 мин.

  5. 16 ЯНВ.

    #231 Paras Jain: The Future of AI Video Generation with Genmo

    In this episode of the Eye on AI podcast, Paras Jain, CEO and Co-founder of Genmo, joins Craig Smith to explore the cutting-edge world of AI-driven video generation, the open-source revolution, and the future of creative storytelling. Paras shares the story behind Genmo, a company at the forefront of advancing video generation technologies, and their groundbreaking model, Mochi One. With a focus on motion quality and prompt adherence, Genmo is redefining what's possible in generative AI for video, offering unmatched precision and creative possibilities. We delve into the innovative approach behind Mochi One, including its state-of-the-art architecture, which enables fast, high-quality video generation. Paras explains how Genmo’s commitment to open source empowers developers and researchers worldwide, fostering rapid advancements, customization, and the creation of new tools, like video-to-video editing. The conversation touches on key themes such as scalability, synthetic data pipelines, and the transformative potential of AI in creating immersive virtual worlds. Paras also explores how Genmo is bridging the gap between cutting-edge AI and practical applications, from TikTok-ready videos to future possibilities like interactive environments and real-time video game-like experiences. Discover how Paras and his team are shaping the future of video creation, blending art, science, and open collaboration to push the boundaries of generative AI. Don’t forget to like, subscribe, and hit the notification bell for more insightful conversations on AI, technology, and innovation!   Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI (00:00) Introduction to Paras Jain and Genmo   (01:45) Video generation with Mochi One   (04:41) Open-source AI in video generation   (06:08) Building Mochi One (12:03) Simulating complex physics in video models   (14:35) Reducing latency: Fast video generation at scale   (20:34) Tackling cost challenges for longer videos   (23:14) Character consistency in AI-generated videos   (27:17) Why video models represent intelligence's next frontier   (30:18) How diffusion models create sharp, realistic videos   (34:02) Visualizing the denoising process in video generation   (39:36) Exploring user-generated video creations with Mochi One   (42:05) Monetizing open-source AI for video generation   (45:47) Video generation's potential in the metaverse   (47:19) Collaborating with universities to advance AI   (48:39) The future of generative AI

    48 мин.

  6. 13 ЯНВ.

    #230 Jamie Lerner: How Quantum Solves AI’s Need for Unstructured Data Solutions

    This episode is sponsored by Oracle.   Oracle Cloud Infrastructure, or OCI is a blazing fast and secure platform for your infrastructure, database, application development, plus all your AI and machine learning workloads. OCI costs 50% less for compute and 80% less for networking. So you’re saving a pile of money. Thousands of businesses have already upgraded to OCI, including MGM Resorts, Specialized Bikes, and Fireworks AI.   Cut your current cloud bill in HALF if you move to OCI now:  https://oracle.com/eyeonai In this episode of the Eye on AI podcast, Jamie Lerner, CEO of Quantum, joins Craig Smith to discuss the future of data storage, unstructured data management, and AI’s transformative role in modern workflows.   Jamie shares his journey leading Quantum, a company revolutionizing the storage and management of unstructured data for industries like healthcare, media, and AI research. With decades of expertise in creating innovative data solutions, Quantum is at the forefront of enabling efficient, secure, and scalable data workflows.   We dive into Quantum’s cutting-edge technologies, from high-speed flash storage systems like the Myriad file system to cost-effective, long-term archival solutions such as tape systems. Jamie unpacks how Quantum supports AI-powered workflows, enabling seamless data movement, metadata tagging, and policy-driven automation for unstructured data like medical imaging, genomics, and video archives.   Jamie also explores the critical role of data sovereignty in today’s global landscape, the growing importance of "forever archives," and how Quantum’s tools help organizations balance exponential data growth with flat budgets. He sheds light on innovations like synthetic DNA and compressed storage mediums, providing a glimpse into the future of data storage.   Don’t forget to like, subscribe, and hit the notification bell for more engaging discussions on AI, technology, and innovation! Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI (00:00) Introduction to Jamie Lerner and Quantum (02:21) Quantum’s Focus on Unstructured Data Storage (05:19) Structured vs. Unstructured Data: Key Differences (07:52) Managing Data Workflows with AI and Automation (10:55) Quantum’s Role in Long-Term Data Archives (13:32) Data Sovereignty and Security (16:18) How Data is Stored and Protected Across Mediums (19:54) Metadata in AI and Data Management (21:29) Quantum’s Role in Building Forever Archives (24:16) Tape Storage: Efficiency and Longevity (29:11) Innovations in Data Storage (34:39) Competing in the Evolving Data Storage Industry (37:56) Innovations in Flash Storage (40:55) Balancing Cost and Efficiency in Data Storage (44:28) The Future of Data Storage and AI Integration (50:07) Quantum’s Vision for the Future

    53 мин.

  7. 8 ЯНВ.

    #229 Mitesh Agrawal: Why Lambda Labs’ AI Cloud Is a Game-Changer for Developers

    This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.   NetSuite is offering a one-of-a-kind flexible financing program. Head to  https://netsuite.com/EYEONAI to know more.  In this episode of the Eye on AI podcast, we dive into the transformative world of AI compute infrastructure with Mitesh Agrawal, Head of Cloud/COO at Lambda   Mitesh takes us on a journey from Lambda Labs' early days as a style transfer app to its rise as a leader in providing scalable, deep learning infrastructure. Learn how Lambda Labs is reshaping AI compute by delivering cutting-edge GPU solutions and accessible cloud platforms tailored for developers, researchers, and enterprises alike.   Throughout the episode, Mitesh unpacks Lambda Labs’ unique approach to optimizing AI infrastructure—from reducing costs with transparent pricing to tackling the global GPU shortage through innovative supply chain strategies. He explains how the company supports deep learning workloads, including training and inference, and why their AI cloud is a game-changer for scaling next-gen applications.   We also explore the broader landscape of AI, touching on the future of AI compute, the role of reasoning and video models, and the potential for localized data centers to meet the growing demand for low-latency solutions. Mitesh shares his vision for a world where AI applications, powered by Lambda Labs, drive innovation across industries.   Tune in to discover how Lambda Labs is democratizing access to deep learning compute and paving the way for the future of AI infrastructure.   Don’t forget to like, subscribe, and hit the notification bell to stay updated on the latest in AI, deep learning, and transformative tech! Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI (00:00) Introduction and Lambda Labs' Mission (01:37) Origins: From DreamScope to AI Compute Infrastructure (04:10) Pivoting to Deep Learning Infrastructure (06:23) Building Lambda Cloud: An AI-Focused Cloud Platform (09:16) Transparent Pricing vs. Hyperscalers (12:52) Managing GPU Supply and Demand (16:34) Evolution of AI Workloads: Training vs. Inference (20:02) Why Lambda Labs Sticks with NVIDIA GPUs (24:21) The Future of AI Compute: Localized Data Centers (28:30) Global Accessibility and Regulatory Challenges (32:13) China’s AI Development and GPU Restrictions (39:50) Scaling Lambda Labs: Data Centers and Growth (45:22) Advancing AI Models and Video Generation (50:24) Optimism for AI's Future (53:48) How to Access Lambda Cloud

    56 мин.

  8. 1 ЯНВ.

    #228 Rodrigo Liang: How SambaNova Systems Is Disrupting AI Inference

    This episode is sponsored by RapidSOS. Close the safety gap and transform your emergency response with RapidSOS.   Visit https://rapidsos.com/eyeonai/ today to learn how AI-powered safety can protect your people and boost your bottom line. In this episode of the Eye on AI podcast, we explore the world of AI inference technology with Rodrigo Liang, co-founder and CEO of SambaNova Systems.   Rodrigo shares his journey from high-performance chip design to building SambaNova, a company revolutionizing how enterprises leverage AI through scalable, power-efficient solutions. We dive into SambaNova’s groundbreaking achievements, including their record-breaking inference models, the Lama 405B and 70B, which deliver unparalleled speed and accuracy—all on a single rack consuming less than 10 kilowatts of power.   Throughout the conversation, Rodrigo highlights the seismic shift from AI training to inference, explaining why production AI is now about speed, efficiency, and real-time applications. He details SambaNova’s approach to open-source models, modular deployment, and multi-tenancy, enabling enterprises to scale AI without costly infrastructure overhauls.   We also discuss the competitive landscape of AI hardware, the challenges of NVIDIA’s dominance, and how SambaNova is paving the way for a new era of AI innovation. Rodrigo explains the critical importance of power efficiency and how SambaNova’s technology is unlocking opportunities for enterprises to deploy private, secure AI systems on-premises and in the cloud.   Discover how SambaNova is redefining AI for enterprise adoption, enabling real-time AI, and setting new standards in efficiency and scalability.    Don’t forget to like, subscribe, and hit the notification bell to stay updated on the latest breakthroughs in AI, technology, and enterprise innovation! Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

    24 мин.
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Eye on A.I. is a biweekly podcast, hosted by longtime New York Times correspondent Craig S. Smith. In each episode, Craig will talk to people making a difference in artificial intelligence. The podcast aims to put incremental advances into a broader context and consider the global implications of the developing technology. AI is about to change your world, so pay attention.

Информация

  • Автор
    Craig S. Smith
  • Годы выхода
    2018 - 2025
  • Выпуски
    234
  • Ограничения
    Без ненормативной лексики
  • Авторские права
    © Eye On A.I.
  • Сайт подкаста
    Eye On A.I.

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