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!

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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

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!

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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!

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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

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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!

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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

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/

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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

This episode is sponsored by Oracle.

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In this episode of the Eye on AI podcast, Tariq Shaukat, CEO of Sonar, joins Craig Smith to explore the future of code quality, security, and AI’s role in software development.

Tariq shares his journey from leading roles at Google Cloud and Bumble to helming Sonar, a company disrupting code assurance for developers worldwide. With over 7 million users and support for 30+ programming languages, Sonar has become a critical tool in ensuring clean, maintainable, and secure code.

We dive into Sonar’s innovative AI Code Assurance Workflow, which integrates seamlessly with generative AI tools like Copilot and Codium. Tariq discusses how Sonar addresses the challenges of AI-generated code, tackling issues like security vulnerabilities, maintainability problems, and the accountability crisis in today’s coding landscape.

Tariq also unpacks the importance of hybrid deterministic and AI-driven approaches, the role of design and architecture in modern software development, and how Sonar is helping companies manage tech debt across billions of lines of code.

With Sonar’s recent enterprise-grade SaaS launch and commitment to reducing developer toil, this episode offers valuable insights for developers, tech leaders, and anyone interested in the evolving intersection of AI and software engineering.

Don’t forget to like, subscribe, and hit the notification bell for more discussions on AI, technology, and innovation!

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Craig Smith Twitter: https://twitter.com/craigss

Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

(00:00) Introduction to Tariq Shaukat and Sonar

(01:23) Overview of SonarQube

(03:03) Deterministic Systems and AI Integration

(07:36) Challenges of AI-Generated Code

(10:12) Early Issue Detection in Development

(12:33) Accountability in AI Code Generation

(16:20) Importance of Rigorous Code Reviews

(19:34) Managing Tech Debt with Continuous Improvement

(22:16) Why Sonar Focuses on Integration

(25:08) Reviewing Billion-Line Code Bases with Sonar

(29:37) Tailoring Sonar for Specific Codebases and Workflows

(32:40) Avoiding Overwhelming Developers with Noise

(37:49) Governance and Managing Complex Codebases

(40:50) Addressing Tech Debt in Legacy Systems

(45:07) Sonar’s Open-Source Model and Philosophy

(48:11) What’s Next for Sonar

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, Matt Panousis, Co-Founder & COO @ LipDub AI, shares the journey behind the platforms a cutting-edge AI-powered lip-syncing tool revolutionizing the dubbing industry.

Matt joins Craig to explore the future of content localization, the evolution of LipDub, and how generative AI is transforming how audiences experience video content worldwide.

As a leader in AI and visual effects, Matt discusses how LipDub integrates advanced AI to enable real-time lip-syncing for dubbed audio, making Hollywood-quality dubbing affordable and accessible. From processing hours of video footage to handling complex, dynamic scenes, LipDub is empowering content creators to reach global audiences like never before.

We explore the challenges of creating realistic lip movements, the importance of mouth internals, textures, and fidelity, and how tools like LipDub stand apart from competitors like Rasque AI. Matt also introduces Vanity AI, LipDub’s sister technology for automated digital makeup and de-aging, used by MARZ for high-end visual effects work.

Learn how LipDub is redefining the possibilities of content localization with AI and what the future holds as this technology evolves.

Don’t miss this deep dive into AI-powered innovation with Matt Panousis. Like, subscribe, and hit the notification bell for more episodes exploring cutting-edge advancements in AI!

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Craig Smith Twitter: https://twitter.com/craigss

Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

(00:00) Introduction & Matt Panousis Background
(02:45) Origins of MARZ and LipDub
(04:20) LipDub vs. Competitors
(06:15) Integration with Dubbing Solutions
(08:00) LipDub Technical Process
(10:20) Competition
(12:20) Time and Cost
(14:00) Target Markets and Use Cases
(19:00) Future Developments
(22:00) Translation and Timing Challenges
(28:00) Ethical Concerns and Misuse
(30:30) Digital Watermarking
(32:25) Real-World Examples and Future Products
(34:00) Team Building and Research
(37:00) Building the Advisory Board
(38:10) Securing Research Talent
(40:00) Funding and the Board
(40:35) Future Products

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, Matt Panousis, Co-Founder & COO @ LipDub AI, shares the journey behind the platforms a cutting-edge AI-powered lip-syncing tool revolutionizing the dubbing industry.

Matt joins Craig to explore the future of content localization, the evolution of LipDub, and how generative AI is transforming how audiences experience video content worldwide.

As a leader in AI and visual effects, Matt discusses how LipDub integrates advanced AI to enable real-time lip-syncing for dubbed audio, making Hollywood-quality dubbing affordable and accessible. From processing hours of video footage to handling complex, dynamic scenes, LipDub is empowering content creators to reach global audiences like never before.

We explore the challenges of creating realistic lip movements, the importance of mouth internals, textures, and fidelity, and how tools like LipDub stand apart from competitors like Rasque AI. Matt also introduces Vanity AI, LipDub’s sister technology for automated digital makeup and de-aging, used by MARZ for high-end visual effects work.

Learn how LipDub is redefining the possibilities of content localization with AI and what the future holds as this technology evolves.

Don’t miss this deep dive into AI-powered innovation with Matt Panousis. Like, subscribe, and hit the notification bell for more episodes exploring cutting-edge advancements in AI!

Stay Updated:

Craig Smith Twitter: https://twitter.com/craigss

Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

(00:00) Introduction & Matt Panousis Background
(02:45) Origins of MARZ and LipDub
(04:20) LipDub vs. Competitors
(06:15) Integration with Dubbing Solutions
(08:00) LipDub Technical Process
(10:20) Competition
(12:20) Time and Cost
(14:00) Target Markets and Use Cases
(19:00) Future Developments
(22:00) Translation and Timing Challenges
(28:00) Ethical Concerns and Misuse
(30:30) Digital Watermarking
(32:25) Real-World Examples and Future Products
(34:00) Team Building and Research
(37:00) Building the Advisory Board
(38:10) Securing Research Talent
(40:00) Funding and the Board
(40:35) Future Products