Abstract: Systems and methods are provided for receiving a request for lookalike data, the request for lookalike data comprising seed data and generating sample data from the seed data and from user data for a plurality of users, to use in a lookalike model training. The systems and methods further provide for capturing a snapshot of social graph data for a plurality of users and computing social graph features based on the seed data and the user data for the plurality of users, training a lookalike model based on the sample data and the computed social graph features to generate a trained lookalike model, generating a lookalike score for each user of the plurality of users in the user data using the trained lookalike model, and generating a list comprising a unique identifier for each user of the plurality of users and an associated lookalike score for each unique identifier.

Abstract: In an aspect, in general, a lighting fixture includes a plurality of light sources, each light source including an array of light emitting diodes and a reflective surface. The reflective surface of each of the light sources is configured to reflect at least a portion of near field light produced by the other light sources into the far field.

Abstract: New firmware versions may be tested more efficiently and more quickly by making an analysis of how a change in the firmware affects components, protocols, and drivers. Based on a determination of the dependencies between the changed components, drivers, and protocols, a list of tests that need to be undertaken can be derived. This list of tests may be much less extensive than all the tests that would normally be run to validate a new version of the firmware. As a result, the test time may be reduced in some embodiments.