Eric D Hullander

US Patent:

20230017644, Jan 19, 2023

Filed:

Jul 14, 2022

Appl. No.:

17/864885

Inventors:

- Santa Clara CA, US
Miller Tracy - Seattle WA, US
Eric Hullander - Edmonds WA, US

International Classification:

G10L 15/01
G10L 21/10

Abstract:

A system and method for characterizing the data used to train a model for machine learning inference. Training data and production data may both be fingerprinted, and the fingerprints may be compared to detect undesirable variances between training and production data. This may allow performance issues relating to differences in the training data set versus the production data set to be more easily identified. Parameters used for characterization can be determined based on the type of training data such as numerical data, image data, or audio data.

US Patent:

20210240953, Aug 5, 2021

Filed:

Aug 12, 2020

Appl. No.:

16/992093

Inventors:

- Bellevue WA, US
Eric Hullander - Edmonds WA, US

International Classification:

G06K 7/14
G06K 7/10
G06T 19/20

Abstract:

A system and method for managing large numbers of computing devices in a data center are disclosed. The computing devices are configured to flash their indicator lights in a pattern that encodes a device ID, and an image capture device such as a mobile phone or tablet captures the flashes in a series of images/video of the data center. The images/video are processed to create a three-dimensional (3D) model of the data center with computing device IDs positioned therein. The 3D model, including correctly positioned device ID indicators, can be rendered for the user of the mobile device to enable the user to more easily identify computing device locations.

US Patent:

20210026729, Jan 28, 2021

Filed:

May 20, 2020

Appl. No.:

16/879157

Inventors:

- Bellevue WA, US
Ganesh Balakrishnan - Sammamish WA, US
Evan Adams - Bainbridge Island WA, US
Carla Cortez - Playa Del Rey CA, US
Eric Hullander - Edmonds WA, US

International Classification:

G06F 11/07

Abstract:

A management device for managing a plurality of computing devices in a data center may comprise a network interface, a first module that periodically sends health status queries to the computing devices via the network interface, a second module configured to receive responses to the health status queries and collect and store health status data for the computing devices, a third module configured to create support tickets, and/or a fourth module configured to (i) create and periodically update a Cox proportional hazards (CPH) model based on the health status data; (ii) apply a deep neural network (DNN) to the input of the CPH model; (iii) determine a probability of failure for each computing device; (iv) compare each probability of failure with a threshold; and (v) cause the third module to generate a pre-failure support ticket for each computing device having determined probabilities of failure above the threshold.