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

A non-transitory computer-readable medium including executable instructions that, when executed on a computer system with one or more processors, cause the computer system to perform the following steps, comprising:

• instantiating an Artificial Intelligence (“AI”) engine having multiple independent modules on one or more computing platforms, where the multiple independent modules are configured to have their instructions executed by one or more processors in the one or more computing platforms, and the multiple independent modules, including an architect module, are configured to be loaded into one or more memories of the one or more computing platforms,
• wherein, upon execution instructions for the architect module by the one or more processors, the architect module is configured 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, where the graph of concept nodes is derived from a description in one or more scripted files, where the architect module is configured to create 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, where one or more external entities of code are selected from a group consisting of i) an external AI model coded in different software language natively used by a resulting AI model, ii) an external function having some defined input and output that is coded in different software language natively used by a resulting AI model, iii) a block of code using a ReST API, iv) an already trained AI model coded in the software language natively used by the resulting AI model, and v) any combination of these;
• wherein, upon execution of the architect module by the one or more processors, the architect module is configured to create a second concept node in the graph of nodes that is derived from its description in a first scripted file, and where the second concept node is also connected into the graph of nodes in the resulting AI model;
• where a re-use of the external entity of code as the first concept node in the graph making up the resulting AI model allows a creation and training of the resulting AI model with less computing cycles in the AI engine than creating and training all of the concept nodes in the resulting AI model from scratch;
• and
• where the second concept node, coded by the architect module and that needs to be trained, allows deployment of the first concept node embodied in the external entity of code with i) new functionality, ii) extended functionality or iii) a combination of both when combined in the resulting AI model.