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.

 

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(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