US 11,728,825 B2
Cluster-based data compression for AI training on the cloud for an edge network
Ofir Ezrielev, Be'er Sheba (IL); Nadav Azaria, Meitar (IL); Avitan Gefen, Lehavim (IL); and Amihai Savir, Sansana (IL)
Assigned to Dell Products L.P., Round Rock, TX (US)
Filed by Dell Products L.P., Round Rock, TX (US)
Filed on Oct. 25, 2021, as Appl. No. 17/509,759.
Prior Publication US 2023/0127149 A1, Apr. 27, 2023
Int. Cl. H03M 7/00 (2006.01); H03M 7/30 (2006.01); H04L 67/10 (2022.01); G06N 3/02 (2006.01); G06F 18/23213 (2023.01)
CPC H03M 7/3059 (2013.01) [G06F 18/23213 (2023.01); G06N 3/02 (2013.01); H03M 7/6005 (2013.01); H03M 7/6011 (2013.01); H04L 67/10 (2013.01)] 18 Claims
OG exemplary drawing
 
1. An information handling system, comprising:
an edge device, communicatively coupled to a cloud computing resource, wherein the edge device is configured to perform edge operations including:
responsive to receiving, from an internet of things (IoT) unit, a numeric value for a parameter of interest, determining a compressed encoding for the numeric value in accordance with a lossy compression algorithm;
transmitting the compressed encoding of the numeric value to the cloud computing resource; and
a decoder, communicatively coupled to the encoder, configured to perform cloud operations including:
responsive to receiving the compressed encoding, generating a surrogate for the numeric value in accordance with a probability distribution applicable to the parameter of interest; and
providing the estimate of the numeric value as training date for an artificial intelligence engine of the cloud computing resource.