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Keen M Browne

from Seattle, WA
Age ~44
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Also known as:
Keen Mcewan Browne, Kevin Browne, Browne Keen
Phone and address:
2714 37Th Ave SW, Seattle, WA 98126
Related to:
Jessica Chatten Brown, 48Kennedy W Browne, 88Daniel D Woock, 72Lisa M BrowneTex Mandell, 98Charlotte T Dawkins, 35Seymour Mandell, 98Ronnie C Browne, 36Lisa B Mandell, 68Baldwin W Browne, 41Jane B Mandell, 99William S Dawkins, 33Kw BrownePeter A Gaylord, 56William Browne, 43
Connected to:
Adam T Browne, 38Alison S Browne, 50Althea A Browne, 60Amelia C Browne, 38Amy Browne, 53Andrae D Browne, 34Ann Browne, 58Anthony J Browne, 65Ari F Browne, 42Audel A Browne, 59

Keen Browne Phones & Addresses

  • 2714 37Th Ave SW, Seattle, WA 98126
  • 525 Belmont Ave E, Seattle, WA 98102
  • Berkeley, CA
  • Orlando, FL
  • Cambridge, WI
  • San Francisco, CA
  • 5214 38Th Ave NE, Seattle, WA 98105

Resumes

Resumes

Keen Browne Photo 1

Co-Founder, Head Of Product

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Location:
2714 37Th St, Seattle, WA 98103
Industry:
Computer Software
Work:
Microsoft
Group Program Manager, Business Ai
Bonsai
Co-Founder, Head of Product
Jobcompass Feb 2011 - Nov 2013
First Employee--Product Manager, Software Engineer, Chief Executive Officer
Ecitysky Jul 2007 - Dec 2010
Co-Founder
Microsoft May 2005 - Jul 2007
Program Manager - Developer Division
Education:
University of Virginia 1998 - 2003
Bachelors, Bachelor of Science, Computer Science Eastside High School
Skills:
Software Engineering
Product Management
Software Development
Agile Methodologies
Python
Scalability
C#
Software Design
Languages:
English
Mandarin
Keen Browne Photo 2

Keen Browne

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Publications

Us Patents

Methods And Apparatus For Evaluating A Candidate's Psychological Fit For A Role

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US Patent:
20130065208, Mar 14, 2013
Filed:
Sep 9, 2011
Appl. No.:
13/229035
Inventors:
Sean Peter Glass - Key West FL, US
Mark Isaac Hammond - Berkley CA, US
Adam Christopher Falla - London, GB
Keen McEwan Browne - Seattle WA, US
Adoree Fausta Durayappah - Houston TX, US
Assignee:
Employ Insight, LLC - Key West FL
International Classification:
G09B 19/00
US Classification:
434236
Abstract:
In some embodiments, a non-transitory processor-readable medium stores code representing instructions to cause a processor to receive a first psychological profile identifying one or more psychological facets associated with a candidate for a role and a set of second psychological profiles identifying one or more psychological facets associated with the role. Each second psychological profile is associated with an assessment of the role by an evaluator from a set of evaluators. The code represents instructions to cause the processor to receive a set of post-interview assessments, each of which is from an interviewer from a set of interviewers and includes a degree of confidence that the candidate possesses the one or more psychological facets associated with the candidate. The code further represents instructions to cause the processor to compute an indicator associated with the first psychological profile, the set of second psychological profiles and the set of post-interview assessments.

Graphical User Interface To An Artificial Intelligence Engine Utilized To Generate One Or More Trained Artificial Intelligence Models

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US Patent:
20200250583, Aug 6, 2020
Filed:
Apr 21, 2020
Appl. No.:
16/854687
Inventors:
- Berkeley CA, US
Keen McEwan Browne - Berkeley CA, US
Mike Estee - Oakland CA, US
Assignee:
Bonsai AI, Inc. - Berkeley CA
International Classification:
G06N 20/00
G06F 16/951
G06F 16/22
G06F 8/38
G06Q 10/00
G06N 3/10
G06F 30/20
G06F 8/30
G06N 3/08
G06N 3/04
H04L 29/06
G06F 9/451
G06F 3/0482
G06N 3/00
G06N 5/04
G06F 9/48
G06F 15/80
G06K 9/62
Abstract:
A computing system includes a processor, and a storage device holding instructions executable by the processor. The instructions are executable to receive a source code through an application programming interface (“API”) exposed to a graphical user interface (“GUI”). The GUI is configured to enable an author to define a proposed model with a pedagogical programming language, the proposed model including an input, one or more concept nodes, and an output. The GUI is further configured to enable the author to provide a program annotation indicating an execution behavior for the source code, to generate an assembly code from the source code with a compiler of an artificial intelligence (“AI”) engine configured to work with the GUI; and to build an executable, trained AI model including a neural-network layout having one or more layers derived from the assembly code.

Artificial Intelligence Engine Configured To Work With A Pedagogical Programming Language To Train One Or More Trained Artificial Intelligence Models

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US Patent:
20170213126, Jul 27, 2017
Filed:
Jan 26, 2017
Appl. No.:
15/417056
Inventors:
- Berkeley CA, US
Keen McEwan Browne - Berkeley CA, US
Megan Adams - San Francisco CA, US
International Classification:
G06N 3/04
G06N 3/08
H04L 29/06
Abstract:
Provided in some embodiments is an artificial intelligence (“AI”) engine configured to work with a pedagogical programming language configured to enable an author to 1) define a mental model to be learned by an AI model, the mental model including an input, one or more concept nodes, one or more stream nodes, and an output, as well as 2) define one or more curriculums for training the AI model respectively on the one or more concept nodes. A compiler can be configured to generate an assembly code from a source code authored in the pedagogical programming language. An architect module can be configured to propose a neural-network layout from the assembly code. A learner module can be configured to build the AI model the neural-network layout. An instructor module can be configured to train the AI model on the one or more concept nodes respectively with the one or more curriculums.

Artificial Intelligence Engine Hosted On An Online Platform

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US Patent:
20170213128, Jul 27, 2017
Filed:
Jan 26, 2017
Appl. No.:
15/416970
Inventors:
- Berkeley CA, US
Keen McEwan Browne - Berkeley CA, US
Marcos Campos - Carlsbad CA, US
Matthew James Brown - San Francisco CA, US
Ruofan Kong - Berkeley CA, US
Megan Adams - San Francisco CA, US
International Classification:
G06N 3/04
G06N 3/08
H04L 29/06
Abstract:
Provided herein in some embodiments is an artificial intelligence (“AI”) engine hosted on one or more remote servers configured to cooperate with one or more databases including one or more AI-engine modules and one or more server-side client-server interfaces. The one or more AI-engine modules include an instructor module and a learner module configured to train an AI model. An assembly code can be generated from a source code written in a pedagogical programming language describing a mental model of one or more concept modules to be learned by the AI model and curricula of one or more lessons for training the AI model. The one or more server-side client-server interfaces can be configured to enable client interactions from a local client such as submitting the source code for training the AI model and using the trained AI model for one or more predictions.

Graphical User Interface To An Artificial Intelligence Engine Utilized To Generate One Or More Trained Artificial Intelligence Models

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US Patent:
20170213131, Jul 27, 2017
Filed:
Jan 26, 2017
Appl. No.:
15/416988
Inventors:
- Berkeley CA, US
Keen McEwan Browne - Berkeley CA, US
Mike Estee - Oakland CA, US
International Classification:
G06N 3/08
G06F 3/0482
G06N 3/04
G06F 9/44
G06F 17/50
G06N 3/00
Abstract:
Provided herein in some embodiments is an artificial intelligence (“AI”) engine configured to work with a graphical user interface (“GUI”). The AI engine can include an architect module, instructor module, and learner module AI-engine modules. The GUI can be configured with a text editor and a mental-model editor to enable an author to define a mental model to be learned by an AI model, the mental model including an input, one or more concept nodes, and an output. The architect module can be configured to propose a neural-network layout from an assembly code compiled from a source code in a pedagogical programming language, the learner module can be configured to build the AI model from the neural-network layout, and the instructor module can be configured to train the AI model on the one or more concept nodes.

Multiple User Interfaces Of An Artificial Intelligence System To Accommodate Different Types Of Users Solving Different Types Of Problems With Artificial Intelligence

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US Patent:
20170213132, Jul 27, 2017
Filed:
Jan 26, 2017
Appl. No.:
15/417033
Inventors:
- Berkeley CA, US
Keen McEwan Browne - Berkeley CA, US
Mike Estee - Oakland CA, US
International Classification:
G06N 3/08
G06N 3/04
G06F 17/50
Abstract:
Provided herein in some embodiments is an artificial intelligence (“AI”) engine configured to operate with multiple user interfaces to accommodate different types of users solving different types of problems with AI. The AI engine can include AI-engine modules including an architect module, an instructor module, and a learner module. An assembly code can be generated from a source code written in a pedagogical programming language. The architect module can be configured to propose a neural-network layout from the assembly code; the learner module can be configured to build the AI model from the neural-network layout; and the instructor module can be configured to train the AI model built by the learner module. The multiple user interfaces can include an integrated development environment, a web-browser interface, or a command-line interface configured to enable an author to define a mental model for the AI model to learn.

Artificial Intelligence Engine Having An Architect Module

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US Patent:
20170213154, Jul 27, 2017
Filed:
Jan 26, 2017
Appl. No.:
15/416904
Inventors:
- Berkeley CA, US
Keen McEwan Browne - Berkeley CA, US
Marcos Campos - Carlsbad CA, US
Matthew James Brown - San Francisco CA, US
Ruofan Kong - Berkeley CA, US
Megan Adams - San Francisco CA, US
International Classification:
G06N 99/00
G06N 3/08
G06F 9/44
Abstract:
Provided herein in some embodiments is an artificial intelligence (“AI”) engine hosted on one or more servers configured to cooperate with one or more databases including one or more AI-engine modules. The one or more AI-engine modules include an architect module configured to propose an AI model from an assembly code. The assembly code can be generated from a source code written in a pedagogical programming language describing a mental model of one or more concept modules to be learned by the AI model and curricula of one or more lessons for training the AI model on the one or more concept modules in one or more training cycles. The AI engine can be configured to instantiate a trained AI model based on the one or more concept modules learned by the AI model in the one or more training cycles.

Searchable Database Of Trained Artificial Intelligence Objects That Can Be Reused, Reconfigured, And Recomposed, Into One Or More Subsequent Artificial Intelligence Models

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US Patent:
20170213155, Jul 27, 2017
Filed:
Jan 26, 2017
Appl. No.:
15/417075
Inventors:
- Berkeley CA, US
Keen McEwan Browne - Berkeley CA, US
Marcos Campos - Carlsbad CA, US
Matthew James Brown - San Francisco CA, US
Ruofan Kong - Berkeley CA, US
William Guss - Berkeley CA, US
Ross Story - Berkeley CA, US
International Classification:
G06N 99/00
G06F 17/30
Abstract:
An AI database hosted on cloud platform is configured to cooperate with a search engine and an AI engine. The AI database stores and indexes trained AI objects and its class of AI objects have searchable criteria. The AI database cooperates with the search engine to utilize search criteria supplied from a user, from either or both 1) via scripted software code and 2) via data put into defined fields of a user interface. The search engine utilizes the search criteria in order for the search engine to retrieve one or more AI data objects that have already been trained as query results. The AI database is coupled to an AI engine to allow any of reuse, reconfigure ability, and recomposition of the one or more trained AI data objects from the AI database into a new trained AI model.
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Keen M Browne from Seattle, WA, age ~44 Get Report