US 12,452,217 B2
Private artificial intelligence and data exchange
Christopher Sharp, Broomfield, CO (US); Travis Duane Ewert, Highlands Ranch, CO (US); Daniel Brian Letort, Gulfport, MS (US); and Scott William Mills, Highlands Ranch, CO (US)
Assigned to DIGITAL PORPOISE, LLC, Austin, TX (US)
Filed by DIGITAL PORPOISE, LLC, Austin, TX (US)
Filed on Nov. 8, 2024, as Appl. No. 18/941,636.
Claims priority of provisional application 63/571,918, filed on Mar. 29, 2024.
Prior Publication US 2025/0310301 A1, Oct. 2, 2025
Int. Cl. H04L 9/40 (2022.01); H04L 67/10 (2022.01)
CPC H04L 63/0272 (2013.01) [H04L 67/10 (2013.01)] 28 Claims
OG exemplary drawing
 
1. A method for providing an environment of a plurality of data centers for privately exchanging and processing data, comprising:
receiving, at a computing device, an identification of (i) a machine learning model to train and (ii) a characteristic describing data needed to train the machine learning model, wherein the plurality of data centers provide physical computer server space and network connectivity services for a plurality of customers of the plurality of data centers;
locating, by the computing device, a data provider within the environment such that the located data provider has access to a data set according to the characteristic,
wherein the data provider is provided by a first customer of the plurality of customers within the environment, and
wherein the data provider is located at a first data center of the plurality of data centers;
locating, by the computing device, a task provider within the environment such that the located task provider is configured to train the machine learning model,
wherein the task provider is provided by a second customer of the plurality of customers,
wherein the task provider is located at a second data center of the plurality of data centers, and
wherein the second customer is different from the first customer;
establishing, by the computing device, a real-time, private, and secure network connection between the data provider and the task provider such that the data provider and the task provider are able to communicate with one another via the network connection without using publicly accessible network addresses, wherein each of the plurality of data centers is connected to the established network connection;
orchestrating, by the computing device, the data set to be transferred from the data provider to the task provider via the established network connection; and
in response to the transfer, orchestrating, by the computing device, the task provider to:
train the machine learning model using the data set; and
deploy the trained machine learning model at a location accessible on the established network connection.