MUMBAI, India, June 26 -- Intellectual Property India has published a patent application (202617066139 A) filed by Gdm Holding LLC on May 26, 2026, for Distributed Training Of Large Neural Networks.
Inventors include Douillard, Arthur; Feng, Qixuan; Rusu, Andrei-Alexandru; Ranzato, Marc'Aurelio; Szlam, Arthur David; and Shen, Jiajun.
The application for the patent was published on June 19, 2026, under issue no. 25/2026.
Abstract: Systems and methods for using a distributed computing system to train a large neural network to perform a machine learning task. A shared set of trainable parameters is maintained in a shared data store, and each of a geographically distributed set of workers updates their trainable parameters using a shard training dataset. There are two optimization processes: an outer optimization process, and an inner optimization loop that is executed by each worker independently and in parallel tens, hundreds, or thousands of times. The workers can have different computing capabilities and can be geographically distant from one another, and the communications bandwidth used by the system can be two or three orders of magnitude less than that of other systems.
Disclaimer: Curated by HT Syndication.
