OMG - xAI and Tesla Rewrote Ethernet Protocol into Hardware for Infinite AI Scaling

By Brian Wang

Tesla and xAI have been to scale coherent GPU AI clusters beyond the 33,000 GPU limit by NOT synchronize all nodes simultaneously. Synchronizing all nodes becomes increasingly challenging at scale - the system implements a partition-based architecture with coordinated timing offsets.

They communicate with an ethernet based network using a transport layer without software control mechanisms

They replaced the third and fourth out of seven layers of network into hardware instead of software.

This is an insane technical achievement that basically has won the battle for AI.

The systems do not wait for confirmation that packets were received and packets can be sent and received out of order.

Every node has timing and memory buffers to enable keep sending and resending packets.

This will enable to xAI and Tesla AI to scale AI data centers to millions of GPUs and even billions. IF AI intelligence continues to scale with compute this will become an insurmountable lead of hundreds of times more compute.

Tesla has patented differential timing in the data center. Tesla's patents describe a comprehensive set of technologies that address fundamental challenges in large-scale AI computing. By combining mesochronous computing, dynamic partitioning, and advanced synchronization mechanisms, these innovations enable the construction and operation of AI clusters at previously unattainable scales.

The clock distribution system described in Tesla's patents implements mesochronous computing, where clock signals are distributed with intentional timing offsets between nodes. This approach creates defined timing relationships between adjacent nodes while allowing controlled variations across the larger system.

The timing offset system provides several technical advantages:

Distribution of computational activities across time

Reduced simultaneous power demand

Support for system partitioning through natural timing boundaries