Eye On A.I. podcast

Player FM - Internet Radio Done Right

215 subscribers

Artificial Intelligence

تمت الإضافة منذ قبل six عام

المحتوى المقدم من Craig S. Smith. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Craig S. Smith أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.

The Vanished

1
Lost on Route 66: The Disappearance of Diana Hayes 6:47

منذ 4 weeks6:47

التشغيل لاحقا

قوائم

إعجاب

احب

6:47

Was she the victim of foul play, an accident, or did she choose to disappear? In this episode of The Vanished, we retrace Diana’s last known movements, strange witness accounts, and the lingering mystery that has never been solved or.. was never meant to be solved.

Eye On A.I.

منزل السلاسل•Feed

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.

241 حلقات

#Artificial Intelligence #Artificialintelligence #Machinelearning #Newyorktimes #Programming #Research #Technology #Tech #Craig S Smith #OpenAI

Eye On A.I.

215 subscribers

updated منذ 3 أيام

منزل السلاسل•Feed

241 حلقات

#Artificial Intelligence #Artificialintelligence #Machinelearning #Newyorktimes #Programming #Research #Technology #Tech #Craig S Smith #OpenAI

كل الحلقات

1
#241 Tuhin Srivatsa: How Baseten is Disrupting AI Deployment & Scaling in 2025 46:17

منذ 3 أيام46:17

46:17

This episode is sponsored by Thuma. Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details. To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai ————————————————————————————————————————— AI deployment is broken—can it be fixed? In this episode, Tuhin Srivatsa, CEO & Co-Founder of Baseten, reveals how his company is DISRUPTING AI infrastructure, making it easier, faster, and more cost-effective to deploy and scale AI models in production. As enterprises increasingly turn to open-source AI models and grapple with the high costs and complexity of scaling, Baseten offers a game-changing solution that eliminates bottlenecks and simplifies the process. Discover how Baseten is taking on AWS SageMaker, OpenAI, and cloud-based AI deployment platforms to reshape the future of AI model deployment. What You’ll Learn in This Episode: Why AI deployment & scaling is one of the biggest challenges in 2025 How Baseten enables enterprises to run AI models faster & more efficiently The shift from closed-source to open-source AI models—and why it matters The hidden costs of AI inference & how to optimize for performance Why most AI models fail in production and how to prevent it The future of AI infrastructure: What comes next for scalable AI Whether you’re a machine learning engineer, AI researcher, startup founder, or enterprise leader, this episode is packed with actionable insights to help you scale AI models without the headaches. Don’t miss this conversation on the next era of AI deployment! #AI #ArtificialIntelligence #MachineLearning #Baseten #AIDeployment #AIScaling #Inference #MLInfrastructure #TechPodcast Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI ————————————————————————————————————————— (00:00) Tuhin Srivatsa’s Journey in AI & Baseten (01:50) What is AI Infrastructure & Why It Matters (03:30) How Baseten Optimizes AI Model Deployment (05:19) Why Most AI Deployments Fail (And How to Fix It) (09:17) The Future of Open-Source AI Models in Enterprise (11:01) How Baseten Automates AI Scaling & Inference (14:12) Why AI Developers Struggle with Cloud-Based AI Tools (18:47) The Real Cost of AI Inference (And How to Reduce It) (20:44) Why AI Scaling is the Biggest Challenge in 2025 (26:55) Can AI Run on Non-NVIDIA Chips? (The Hardware Debate) (31:23) The Future of AI Model Deployment & Inference (37:05) How AI Agents & Reasoning Models Are Changing the Game (40:39) The Truth About AI Hype vs. Reality (45:04) How to Get Started with Baseten (45:48) The Future of AI Infrastructure…

1
#238 Dominic Williams Reveals His Vision for the Internet Computer (ICP) 1:14:52

منذ 9 أيام1:14:52

1:14:52

This episode is sponsored by Indeed. Stop struggling to get your job post seen on other job sites. Indeed's Sponsored Jobs help you stand out and hire fast. With Sponsored Jobs your post jumps to the top of the page for your relevant candidates, so you can reach the people you want faster. Get a $75 Sponsored Job Credit to boost your job’s visibility! Claim your offer now: https://www.indeed.com/EYEONAI Dominic Williams’ Bold Vision for The Internet Computer (ICP) | The Future of Decentralized Computing The internet is broken—can blockchain fix it? In this episode, Dominic Williams, the visionary behind The Internet Computer (ICP) and founder of DFINITY, reveals his plan to build a decentralized alternative to cloud computing. Discover how ICP is challenging Big Tech, replacing traditional IT infrastructure, and creating a tamper-proof, autonomous internet powered by smart contracts. What You'll Learn in This Episode: Why Dominic Williams believes the current internet is flawed How ICP aims to replace centralized cloud providers like AWS & Google Cloud The role of smart contracts in making the internet more secure and censorship-resistant The mission of DFINITY and how it started in 2016 The future of Web3, decentralized applications (dApps), and blockchain governance Don't miss this deep dive into the future of the internet! If you're interested in blockchain, decentralization, and the next evolution of the web, this episode is for you. Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI (00:00) The Origins of The Internet Computer (02:57) Dominic Williams’ Background in Tech (04:28) Early Innovations in Distributed Computing (07:08) The Birth of a 'World Computer' Concept (11:22) Reimagining IT: A Decentralized Alternative (13:45) The Creation of DFINITY and ICP (16:29) How ICP Differs from Traditional Blockchains (22:05) The Problem with Cloud-Based Blockchains (25:35) How ICP Ensures True Decentralization (29:25) AI & The Self-Writing Internet (35:24) How ICP Hosts AI & Smart Contracts (40:23) Understanding Reverse Gas and ICP’s Economy (45:03) The Vision: A Truly Decentralized Internet (49:09) How To Use The Internet Computer (52:01) The Role of Nodes & Incentives in ICP (56:53) The Future of Web3 & Decentralized Applications (01:05:49) The Misconception of ‘On-Chain’ & Blockchain Hype…

1
#237 Pedro Domingos Breaks Down The Symbolist Approach to AI 48:12

منذ 12 يومًا48:12

48:12

This episode is sponsored by Thuma. Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details. To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai In this episode of the Eye on AI podcast, Pedro Domingos—renowned AI researcher and author of The Master Algorithm—joins Craig Smith to break down the Symbolist approach to artificial intelligence, one of the Five Tribes of Machine Learning. Pedro explains how Symbolic AI dominated the field for decades, from the 1950s to the early 2000s, and why it’s still playing a crucial role in modern AI. He dives into the Physical Symbol System Hypothesis, the idea that intelligence can emerge purely from symbol manipulation, and how AI pioneers like Marvin Minsky and John McCarthy built the foundation for rule-based AI systems. The conversation unpacks inverse deduction—the Symbolists' "Master Algorithm"—and how it allows AI to infer general rules from specific examples. Pedro also explores how decision trees, random forests, and boosting methods remain some of the most powerful AI techniques today, often outperforming deep learning in real-world applications. We also discuss why expert systems failed, the knowledge acquisition bottleneck, and how machine learning helped solve Symbolic AI’s biggest challenges. Pedro shares insights on the heated debate between Symbolists and Connectionists, the ongoing battle between logic-based reasoning and neural networks, and why the future of AI lies in combining these paradigms. From AlphaGo’s hybrid approach to modern AI models integrating logic and reasoning, this episode is a deep dive into the past, present, and future of Symbolic AI—and why it might be making a comeback. Don't forget to like, subscribe, and hit the notification bell for more expert discussions on AI, technology, and the future of intelligence! Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI (00:00) Pedro Domingos onThe Five Tribes of Machine Learning (02:23) What is Symbolic AI? (04:46) The Physical Symbol System Hypothesis Explained (07:05) Understanding Symbols in AI (11:51) What is Inverse Deduction? (15:10) Symbolic AI in Medical Diagnosis (17:35) The Knowledge Acquisition Bottleneck (19:05) Why Symbolic AI Struggled with Uncertainty (20:40) Machine Learning in Symbolic AI – More Than Just Connectionism (24:08) Decision Trees & Their Role in Symbolic Learning (26:55) The Myth of Feature Engineering in Deep Learning (30:18) How Symbolic AI Invents Its Own Rules (31:54) The Rise and Fall of Expert Systems – The CYCL Project (38:53) Symbolic AI vs. Connectionism (41:53) Is Symbolic AI Still Relevant Today? (43:29) How AlphaGo Combined Symbolic AI & Neural Networks (45:07) What Symbolic AI is Best At – System 2 Thinking (47:18) Is GPT-4o Using Symbolic AI?…

1
#236 Pedro Domingo’s on Bayesians and Analogical Learning in AI 56:43

منذ 20 يومًا56:43

56:43

This episode is sponsored by Thuma. Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details. To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai In this episode of the Eye on AI podcast, Pedro Domingos, renowned AI researcher and author of The Master Algorithm, joins Craig Smith to explore the evolution of machine learning, the resurgence of Bayesian AI, and the future of artificial intelligence. Pedro unpacks the ongoing battle between Bayesian and Frequentist approaches, explaining why probability is one of the most misunderstood concepts in AI. He delves into Bayesian networks, their role in AI decision-making, and how they powered Google’s ad system before deep learning. We also discuss how Bayesian learning is still outperforming humans in medical diagnosis, search & rescue, and predictive modeling, despite its computational challenges. The conversation shifts to deep learning’s limitations, with Pedro revealing how neural networks might be just a disguised form of nearest-neighbor learning. He challenges conventional wisdom on AGI, AI regulation, and the scalability of deep learning, offering insights into why Bayesian reasoning and analogical learning might be the future of AI. We also dive into analogical learning—a field championed by Douglas Hofstadter—exploring its impact on pattern recognition, case-based reasoning, and support vector machines (SVMs). Pedro highlights how AI has cycled through different paradigms, from symbolic AI in the '80s to SVMs in the 2000s, and why the next big breakthrough may not come from neural networks at all. From theoretical AI debates to real-world applications, this episode offers a deep dive into the science behind AI learning methods, their limitations, and what’s next for machine intelligence. Don’t forget to like, subscribe, and hit the notification bell for more expert discussions on AI, technology, and the future of innovation! Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI (00:00) Introduction (02:55) The Five Tribes of Machine Learning Explained (06:34) Bayesian vs. Frequentist: The Probability Debate (08:27) What is Bayes' Theorem & How AI Uses It (12:46) The Power & Limitations of Bayesian Networks (16:43) How Bayesian Inference Works in AI (18:56) The Rise & Fall of Bayesian Machine Learning (20:31) Bayesian AI in Medical Diagnosis & Search and Rescue (25:07) How Google Used Bayesian Networks for Ads (28:56) The Role of Uncertainty in AI Decision-Making (30:34) Why Bayesian Learning is Computationally Hard (34:18) Analogical Learning – The Overlooked AI Paradigm (38:09) Support Vector Machines vs. Neural Networks (41:29) How SVMs Once Dominated Machine Learning (45:30) The Future of AI – Bayesian, Neural, or Hybrid? (50:38) Where AI is Heading Next…

1
#235 Vall Herard: The Future of AI-Driven Compliance (Saifr.ai) 51:55

منذ 26 يومًا51:55

51:55

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…

1
#234 Tyler Xuan Saltsman: How AI is Shaping the Future of Combat & Warfare 38:48

منذ 4 weeks38:48

38:48

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…

1
#233 Matt Price: How Crescendo is Disrupting Customer Service with Gen AI 44:53

منذ 5 weeks44:53

44:53

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…

1
#232 Sepp Hochreiter: How LSTMs Power Modern AI System’s 51:08

منذ 5 weeks51:08

51:08

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…

1
#231 Paras Jain: The Future of AI Video Generation with Genmo 47:49

منذ 6 weeks47:49

47:49

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…

1
#230 Jamie Lerner: How Quantum Solves AI’s Need for Unstructured Data Solutions 53:23

منذ 7 weeks53:23

53:23

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…

1
#229 Mitesh Agrawal: Why Lambda Labs’ AI Cloud Is a Game-Changer for Developers 56:07

منذ 7 weeks56:07

56:07

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…

1
#228 Rodrigo Liang: How SambaNova Systems Is Disrupting AI Inference 23:54

منذ 8 weeks23:54

23:54

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…

1
#227 Sedarius Tekara Perrotta: The Importance of Data Quality in AI Systems 45:00

منذ 9 weeks45:00

45:00

In this episode of the Eye on AI podcast, we dive into the critical issue of data quality for AI systems with Sedarius Perrotta, co-founder of Shelf. Sedarius takes us on a journey through his experience in knowledge management and how Shelf was built to solve one of AI’s most pressing challenges—unstructured data chaos. He shares how Shelf’s innovative solutions enhance retrieval-augmented generation (RAG) and ensure tools like Microsoft Copilot can perform at their best by tackling inaccuracies, duplications, and outdated information in real-time. Throughout the episode, we explore how unstructured data acts as the "fuel" for AI systems and why its quality determines success. Sedarius explains Shelf's approach to data observability, transparency, and proactive monitoring to help organizations fix "garbage in, garbage out" issues, ensuring scalable and trusted AI initiatives. We also discuss the accelerating adoption of generative AI, the future of data management, and why building a strategy for clean and trusted data is vital for 2025 and beyond. Learn how Shelf enables businesses to unlock the full potential of their unstructured data for AI-driven productivity and innovation. Don’t forget to like, subscribe, and hit the notification bell to stay updated on the latest advancements in AI, data management, and next-gen automation! Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI (00:00) Introduction and Shelf's Mission (03:01) Understanding SharePoint and Data Challenges (05:29) Tackling Data Entropy in AI Systems (08:13) Using AI to Solve Data Quality Issues (12:30) Fixing AI Hallucinations with Trusted Data (21:01) Gen AI Adoption Insights and Trends (28:44) Benefits of Curated Data for AI Training (37:38) Future of Unstructured Data Management…

1
#226 Nathan Michael: The Future of AI-Powered Drones and Autonomous Warfare (with Shield AI) 58:17

منذ 10 weeks58:17

58:17

Launch, run, and protect your business to make it official TODAY at https://www.legalzoom.com/ and use promo code EYEONAI to get 10% off any LegalZoom business formation product excluding subscriptions and renewals. In this episode of the Eye on AI podcast, we explore the cutting-edge world of AI-powered autonomy with Nathan Michael, CTO of Shield AI. Nathan shares his journey from academia to leading one of the most innovative companies in defense technology, revealing how Shield AI is transforming autonomous systems to operate in the most challenging environments. Throughout the episode, Nathan dives into Shield AI's groundbreaking technologies, including the revolutionary Hivemind platform, which enables drones and uncrewed jets to think, adapt, and act independently—even in GPS-denied and communication-jammed conditions. He explains how these systems are deployed across defense and commercial applications, reshaping intelligence, surveillance, and reconnaissance missions with unprecedented precision and resilience. We also discuss the future of warfare and technology, from the commoditization of AI-driven autonomy to the ethical and strategic considerations of deploying these systems at scale. Nathan offers insights into how rapid iteration cycles and resilient intelligence will define the next era of defense innovation, ensuring mission success in increasingly complex scenarios. Don’t forget to like, subscribe, and hit the notification bell to stay updated on the latest advancements in AI, robotics, and the future of autonomous systems! Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI (00:00) Introduction to Shield AI and Hivemind (03:02) Nathan Michael's journey to Shield AI (06:07) Shield AI's mission and technology overview (10:18) VBAT: A versatile tail-sitter aircraft (12:44) Hivemind's swarm capabilities and applications (14:32) Ethics and societal guardrails for autonomous systems (17:24) Combat applications of quadcopters (19:12) Navigating and mapping unknown environments (20:38) Use of VBAT in Ukraine operations (22:10) Intelligence gathering and mission versatility (24:42) Transforming warfare with AI-driven autonomy (28:47) Teaming and communication in autonomous swarms (32:29) Communication networks in jammed conditions (35:34) Coordinated exploration with autonomous systems (38:13) Exploring buildings with quadcopter teams (40:57) Crewed-uncrewed teaming in modern combat (43:28) Global competition in AI and autonomy (46:03) Use of autonomous drones in Ukraine (50:28) Shield AI's vision: Proliferation of resilient intelligence (55:26) Expanding AI autonomy to commercial applications…

1
#225 Christian Marek: How AI is Shaping the Future of Product Management 50:14

منذ 10 weeks50:14

50:14

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 delve into the role of AI in product management with Christian Marek, VP of Product at Productboard. Christian shares his journey in shaping the future of product management, exploring how AI is changing the way we ideate, build, and deliver customer-centric products. Throughout the episode, Christian unveils Productboard's innovative AI-driven solutions, including the groundbreaking Productboard Pulse, which accelerates ideation and discovery by aggregating and analyzing customer feedback. He explains how AI enables product managers to prioritize features, write detailed specifications, and align product roadmaps with organizational goals—all while driving ROI and delivering exceptional customer experiences. We also discuss the evolution of product management, from its origins to its rise as a mainstream discipline in organizations of all sizes. Christian offers insights into how AI tools are reshaping the product management landscape, making it more efficient, collaborative, and impactful than ever before. Don’t forget to like, subscribe, and hit the notification bell to stay updated on the latest breakthroughs in AI, product innovation, and customer-centric technology! Checkout Productboard Pulse: https://www.productboard.com/product/voice-of-customer/ Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI (00:00) Introduction (03:18) What is Productboard? (05:04) Christian Marek’s Journey (07:20) Defining Product Management (08:45) How Productboard Was Born (10:05) Transforming Product Management (14:32) Exploring Use Cases: Existing and New Product Development (18:13) Scaling Productboard (20:33) Managing Complex Projects Without Productboard (24:59) Industries Using Productboard (26:29) Why Startups Benefit from Productboard (29:25) Closing the Feedback Loop on Product Management (33:16) Non-Digital Applications of Productboard (36:27) AI Model Selection (39:48) The Future of Product Management with AI (43:30) C-Suite Engagement and ROI with Productboard (45:15) How to Get Started with Productboard…

مرحبًا بك في مشغل أف ام!

يقوم برنامج مشغل أف أم بمسح الويب للحصول على بودكاست عالية الجودة لتستمتع بها الآن. إنه أفضل تطبيق بودكاست ويعمل على أجهزة اندرويد والأيفون والويب. قم بالتسجيل لمزامنة الاشتراكات عبر الأجهزة.