Microsoft Technology Licensing, LLC

Bonsai Ai, Inc.

Other

Megan Adams

Keen McEwan Browne

Mark Hammond

Marcos M Campos

Matthew James Brown

Ruofan Kong

Tod Frye

Mark Isaac Hammond

An AI engine having an architect module to create a number of nodes and how the nodes are connected in a graph of concept nodes that make up a resulting AI model. The architect module also creates a first concept node by wrapping an external entity of code into a software container with an interface configured to exchange information in a protocol of a software language used by the external entity of code. The architect module also creates a second concept node derived from its description in a scripted file coded in a pedagogical programming language, and connects the second concept node into the graph of nodes in the resulting AI model.

Artificial intelligence engine for mixing and enhancing features from one or more trained pre-existing machine-learning models

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.

Artificial intelligence engine hosted on an online platform

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.

Artificial intelligence engine having an architect module

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 configured to work with a pedagogical programming language to train one or more trained artificial intelligence models

A method and system for translating source code in one logically distinct object oriented language on one platform into another object oriented language on another platform. This includes the translation of the classes and statements in the original source. It also includes the creation of object oriented interfaces for all types and services used in the source code whose definitions are not provided. Once the source code classes are translated, a complete object oriented interface to the target platform is generated. Type inference analysis is performed on the input source code in order to infer types for undeclared services and to infer type hierarchies for undeclared types. Type inference analysis is utilized to generate object oriented interfaces for all types and services used in the source code whose definitions are not available. The method and system also have the capability of generating, on an as needed basis, specific bridge classes which support bridging the platform differences between the target and the source platform.

Growing community of inventors

San Francisco, CA, United States of America

Megan Adams