- Foster City CA, US Marin Kobilarov - Mountain View CA, US Andres Guillermo Morales Morales - San Francisco CA, US Kai Zhenyu Wang - San Francisco CA, US
Techniques for determining predictions on a top-down representation of an environment based on vehicle action(s) are discussed herein. Sensors of a first vehicle (such as an autonomous vehicle) can capture sensor data of an environment, which may include object(s) separate from the first vehicle (e.g., a vehicle or a pedestrian). A multi-channel image representing a top-down view of the object(s) and the environment can be generated based on the sensor data, map data, and/or action data. Environmental data (object extents, velocities, lane positions, crosswalks, etc.) can be encoded in the image. Action data can represent a target lane, trajectory, etc. of the first vehicle. Multiple images can be generated representing the environment over time and input into a prediction system configured to output prediction probabilities associated with possible locations of the object(s) in the future, which may be based on the actions of the autonomous vehicle.
Prediction On Top-Down Scenes Based On Action Data
- Foster City CA, US Marin Kobilarov - Mountain View CA, US Andres Guillermo Morales Morales - San Francisco CA, US Kai Zhenyu Wang - Foster City CA, US
Techniques for determining predictions on a top-down representation of an environment based on vehicle action(s) are discussed herein. Sensors of a first vehicle (such as an autonomous vehicle) can capture sensor data of an environment, which may include object(s) separate from the first vehicle (e.g., a vehicle or a pedestrian). A multi-channel image representing a top-down view of the object(s) and the environment can be generated based on the sensor data, map data, and/or action data. Environmental data (object extents, velocities, lane positions, crosswalks, etc.) can be encoded in the image. Action data can represent a target lane, trajectory, etc. of the first vehicle. Multiple images can be generated representing the environment over time and input into a prediction system configured to output prediction probabilities associated with possible locations of the object(s) in the future, which may be based on the actions of the autonomous vehicle.
- Foster City CA, US Michael Haggblade - El Dorado Hills CA, US Hao Li - San Jose CA, US Andres Guillermo Morales Morales - San Francisco CA, US
International Classification:
G06F 11/14 G06F 9/30
Abstract:
Techniques are disclosed for re-executing a data processing pipeline following a failure of at least one of its components. The techniques may include a syntax for defining a compute graph associated with the data processing pipeline and receiving such a compute graph in association with a specific data processing pipeline. The technique may include executing the data processing pipeline, determining that a component of the data processing pipeline failed, and determining a portion of the data processing pipeline to execute/re-execute based at least in part on dependencies defined by the data processing pipeline in association with the failed component. Re-executing the one or more components may comprise retrieving an output saved in association with a component upon which the failed component depends.
- Mountain View CA, US Ray Xiaohang Wang - Millburn NJ, US Yakov Okshtein - Far Rockaway NY, US Farhan Shamsi - Rego Park NY, US David Singleton - London, GB Lixin Zhang - Mountain View CA, US Alan Newberger - San Francisco CA, US Chandrasekhar Thota - Saratoga CA, US Douglas Alexander Gresham - Kitchener, CA Nicholas Fey - Mountain View CA, US Marcus Alexander Foster - West Malling, GB Petra Cross - San Francisco CA, US Andres Morales - San Francisco CA, US
Receiving point of interest zones and alerts on user devices comprises communicating, by a user computing device to a remote computing device, a request for point of interest data corresponding to points of interest within a proximity of the user device; presenting the received point of interest data; identifying a particular point of interest; and outputting an alert regarding the particular point of interest. Receiving point of interest zones on user devices comprises communicating a request for point of interest data; receiving the point of interest data from the remote network device wherein a size of the point of interest zone is determined based on a density of points of interest in the proximity of the user, and wherein the shape of the point of interest zone is expanded in a direction of travel and contracted in the opposite direction; and presenting the received point of interest data.
Policies For Secrets In Trusted Execution Environments
- Mountain View CA, US Andrew Abramson - Sunnyvale CA, US Neel Rao - San Francisco CA, US Shawn Willden - Morgan UT, US Andres Guillermo Morales - San Francisco CA, US James Brooks Miller - Sunnyvale CA, US
A computing device executes one or more trusted execution environment (TEE) processes in a TEE of a processor. The one or more TEE processes cryptographically protect a secret and a policy. The policy specifies a plurality of conditions on usage of the secret. A particular non-TEE process generates a request whose fulfillment involves an action requiring use of the secret. Responsive to the request, one or more non-TEE processes determine whether a first subset of the plurality of conditions is satisfied. Responsive to the first subset of the plurality of conditions being satisfied, the one or more TEE processes determine that a second, different subset of the plurality of conditions is satisfied. Responsive to determining the second subset of the plurality of conditions is satisfied, the one or more TEE processes use the secret to perform the action.
Policies For Secrets In Trusted Execution Environments
- Mountain View CA, US Andrew Abramson - Sunnyvale CA, US Neel Rao - San Francisco CA, US Shawn Edward Willden - Morgan UT, US Andres Guillermo Morales - San Francisco CA, US James Brooks Miller - Sunnyvale CA, US
International Classification:
G06F 21/72 H04L 9/32 H04L 9/08 G06F 21/53
Abstract:
A computing device executes one or more trusted execution environment (TEE) processes in a TEE of a processor. The one or more TEE processes cryptographically protect a secret and a policy. The policy specifies a plurality of conditions on usage of the secret. A particular non-TEE process generates a request whose fulfillment involves an action requiring use of the secret. Responsive to the request, one or more non-TEE processes determine whether a first subset of the plurality of conditions is satisfied. Responsive to the first subset of the plurality of conditions being satisfied, the one or more TEE processes determine that a second, different subset of the plurality of conditions is satisfied. Responsive to determining the second subset of the plurality of conditions is satisfied, the one or more TEE processes use the secret to perform the action.
- Mountain View CA, US Ray Xiaohang Wang - Millburn NJ, US Yakov Okshtein - Far Rockaway NY, US Farhan Shamsi - Rego Park NY, US David Singleton - London, GB Lixin Zhang - Mountain View CA, US Alan Newberger - San Francisco CA, US Chandrasekhar Thota - Saratoga CA, US Douglas Alexander Gresham - Kitchener, CA Nicholas Fey - Mountain View CA, US Marcus Alexander Foster - West Malling, GB Petra Cross - San Francisco CA, US Andres Morales - San Francisco CA, US
International Classification:
H04W 4/02 H04W 4/20 H04L 29/08
Abstract:
Receiving point of interest zones and alerts on user devices comprises communicating, by a user computing device to a remote computing device, a request for point of interest data corresponding to points of interest within a proximity of the user device; presenting the received point of interest data; identifying a particular point of interest; and outputting an alert regarding the particular point of interest. Receiving point of interest zones on user devices comprises communicating a request for point of interest data; receiving the point of interest data from the remote network device wherein a size of the point of interest zone is determined based on a density of points of interest in the proximity of the user, and wherein the shape of the point of interest zone is expanded in a direction of travel and contracted in the opposite direction; and presenting the received point of interest data.
- Mountain View CA, US Ray Xiaohang Wang - Jersey City NJ, US Yakov Okshtein - Far Rockaway NY, US Farhan Shamsi - Rego Park NY, US David Singleton - London, GB Lixin Zhang - Mountain View CA, US Alan Newberger - San Francisco CA, US Chandrasekhar Thota - Saratoga CA, US Douglas Alexander Gresham - Kitchener, CA Nicholas Fey - Mountain View CA, US Marcus Alexander Folster - West Malling, UK Petra Cross - San Francisco CA, US Andres Morales - San Francisco CA, US
Assignee:
GOOGLE INC. - Mountain View CA
International Classification:
G01C 21/00
US Classification:
702150
Abstract:
Receiving point of interest zones and alerts on user devices comprises communicating, by a user computing device to a remote computing device, a request for point of interest data corresponding to points of interest within a proximity of the user device; presenting the received point of interest data; identifying a particular point of interest; and outputting an alert regarding the particular point of interest. Receiving point of interest zones on user devices comprises communicating a request for point of interest data; receiving the point of interest data from the remote network device wherein a size of the point of interest zone is determined based on a density of points of interest in the proximity of the user, and wherein the shape of the point of interest zone is expanded in a direction of travel and contracted in the opposite direction; and presenting the received point of interest data.
Sep 2010 to 2000 Marketing Manager - BlackBerry (RIM)SONY MOBILE (Latin America) Miami, FL Apr 2008 to Sep 2010 Marketing Business ManagerWARNER CHANNEL LATIN AMERICA / Warner Bros International Television Miami, FL Dec 2003 to Apr 2008 Marketing Executive/ Project ManagerVIGA CORP Miami, FL Jan 2002 to Jul 2003 Executive Account & Sales and Hispanic Media DirectorMEDIA PLANNING GROUP
Dec 1999 to Nov 2001 Executive Media Planner / Account ServicesBUENA VISTA INTERNATIONAL / Walt Disney Company
Sep 1998 to Dec 1999 Assistant Marketing Manager
Education:
Miller Heiman Miami, FL 2011 to 2011 Sales Excellence in Large Account Management Process in Business ManagementMiller Heiman Miami, FL 2011 to 2011 Sales Excellence in Conceptual Selling in Business ManagementFundacin Universidad Central Jan 1996 to Dec 2001 B.S. in Advertising
Skills:
Team player with a Results Guaranteed attitude. Excellent interpersonal skills and outstanding communication with cross functional and multicultural environments. Bicultural & bilingual, in Spanish and English, with conversational Portuguese.
Dr. Morales graduated from the University of North Texas College of Osteopathic Medicine in 1992. He works in Durant, OK and 2 other locations and specializes in Neurology. Dr. Morales is affiliated with Alliance Health Durant, Medical Center Of Mckinney, Texoma Medical Center and Wilson N Jones Regional Medical Center.
Youtube
andres morales - clemente y javier.wmv
Una rola compuesta e interpretada por el seor Andres Morales acompaado...
Category:
Music
Uploaded:
12 Dec, 2009
Duration:
3m 5s
Activation Andres Morales
Category:
Music
Uploaded:
15 Jun, 2009
Duration:
6m 17s
Andres Morales - los tesoros de michoacan.wmv
Con saludos a mi compita Andres Morales de Humberto Sanchez Y puro Hue...
Category:
Music
Uploaded:
13 Apr, 2010
Duration:
2m 26s
ANDRES MORALES - BASS JAM
Andres Morales Bass Jam / Ken Smith 5 Bass
Category:
Music
Uploaded:
26 Jan, 2010
Duration:
1m 27s
Andrs Morales 1931 publicacin de Altazor
Category:
Entertainment
Uploaded:
30 Jan, 2011
Duration:
4m
Entrevista de Andrs Morales Carbo en ETV Tele...
Andrs Morales Carbo, Candidato a la Presidencia de la Cmara de Comerci...
Instituto De Seguridad Del Trabajo - Paramedico (19)
Tagline:
Paramedico 21 años (aun), fumador empedernido, bebedor social, amante de su familia y amigos :D
Andres Morales
Work:
Universidad Anáhuac México Norte - Coordinador Académico
Education:
Universidad Anáhuac - Humanidades
Andres Morales
Work:
YouTube - The Boss (2005)
About:
Paula the koala She moved to Guatemala Cuz she heard the trees there were a little taller Turned out they were smaller So she moved to lake eufuala Then to Walla Walla WashingtonSo if you live in Wall...