Join me for an exclusive, behind-the-scenes tour of Cisco's purpose-built $20 million AI data center lab in San Jose. AI is revolutionizing the tech industry, but running massive 10,000 GPU clusters can cost up to $175 million a year—and a mere 5% network bottleneck can flush $8 million down the drain. In this video, we break down the hardware, software, and networking topologies required to build, secure, and scale massive AI data centers.

I sit down with Cisco engineers to explore scale-up domains with NVIDIA H200 and AMD MI350X servers, scale-out rail-optimized topologies, and the massive Cisco Silicon One G300 ASIC delivering 102.4 Terabits per second with innovative liquid cooling. We also dive into the Ethernet vs. InfiniBand debate for scaling to 100,000 GPUs, the power of Linear Pluggable Optics (LPO) to reduce power draw, and how Cisco used AI to safely refactor 500,000 lines of legacy code. Whether you are building

an AI network today or upgrading your engineering skills for the future, this is video can help you learn.

Big thanks to Cisco for sponsoring my trip to Cisco Data Center and Operational Control Center in San Jose.

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// YouTube video REFERENCE //

• The 100Tbps AI Switch: Inside the Beast

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// MENU //

0:00 - The power of AI data centers

0:51 - Cost and challenges of AI data centers

02:35 - How to connect GPUs in an AI cluster

05:23 - The future of data centers

08:45 - NeoCloud infrastructure in Australia

10:28 - The right components matter

16:32 - Testing to avoid failures

21:43 - Ethernet vs InfiniBand

23:27 - Cisco security services

26:14 - Future of speeds in the data center

27:23 - Conclusion

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Disclaimer: This video is for educational purposes only.

#ai #network #datacenter