Cerebri Ai Inc.

David Alexander Curry

Alain Charles Briancon

Gabriel M Silberman

Jean Joseph Belanger

Thejas Narayana Prasad

Lee David Harper

Michael Thomas Wegan

Luke Philip Reding

Michael Henry Engeling

Eyal Ben Zion

Sara Amini

Dmitrii Aleksandrovich Boldyrev

Sathish Kumar Lakshmipathy

Provided is a process including: obtaining, for a plurality of entities, entity logs, wherein: the entity logs comprise events involving the entities, a first subset of the events are actions by the entities, at least some of the actions by the entities are targeted actions, and the events are labeled according to an ontology of events having a plurality of event types; training, with one or more processors, based on the entity logs, a predictive machine learning model to predict whether an entity characterized by a set of inputs to the model will engage in a targeted action in a given duration of time in the future; and storing the trained predictive machine learning model in memory.

Predictive, machine-learning, event-series computer models with encoded representation

Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.

Privacy and proprietary-information preserving collaborative multi-party machine learning

Predictive, machine-learning, time-series computer models suitable for sparse training sets

Collaborative multi-parties/multi-sources machine learning for affinity assessment, performance scoring, and recommendation making

Growing community of inventors

Austin, TX, United States of America

David Alexander Curry