World Congress 2026 Europe Jul 10, 2026 Session details

Building the Nervous System of AI - Michael Kagan (NVIDIA)

Michael Kagan , Sead Ahmetović

Michael Kagan asserts that without robust networking, AI hardware is just expensive sand. Discover how distributed nervous systems transform scattered data centers into singular intelligence factories.

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#1 about 3 min

Evolution of computing to AI infrastructure

How AI transforms the unit of computing and makes programming accessible through natural language.

#2 about 4 min

Acquiring Mellanox to build cohesive AI factories

The strategic necessity of advanced networking to connect GPUs into a single unified AI computer.

#3 about 3 min

Transitioning from data centers to AI factories

Converting traditional storage warehouses into power plants that generate intelligence tokens from raw data.

#4 about 3 min

Optimizing infrastructure for agentic flows and inference

Managing exponential computing demands driven by reasoning models and autonomous agentic interactions within data centers.

#5 about 3 min

Scaling up and scaling out GPU clusters

Using NVLink and scale-out networking to connect millions of GPUs into massive unified supercomputers.

#6 about 2 min

Connecting distributed AI factories across distances

Overcoming power limits by networking separate data centers to operate as one synchronized computing machine.

#7 about 3 min

Architecting CUDA and the AI software stack

Building a flexible API platform that allows developers to innovate continuously on top of hardware layers.

#8 about 3 min

Navigating power limitations for AI infrastructure

Treating energy supply as a foundational layer and decoupling training locations from edge inference endpoints.

#9 about 3 min

Moving agentic intelligence to physical robotics

Enabling robots to operate independently in the physical world and sync learned data back to centralized clusters.

#10 about 2 min

Ensuring safety and security in AI systems

Implementing technical guardrails and cooperating with authorities to steer artificial intelligence toward benefiting humanity.

#11 about 2 min

Choosing foundational learning paths for engineers

Why mastering core physics, math, and emerging fields like digital biology remains critical amidst AI advancements.

#12 about 3 min

Simulating historical outcomes as an experimental science

Forecasting the long-term societal consequences of actions by using AI models to simulate complex historical trajectories.

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Hard science and infrastructure enabled by artificial intelligence

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Cost and latency pressures pushing AI to the edge

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