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AI Builder 2 Overview

The TinMan AI Builder is a platform and development kit for creating autonomous artificial intelligence and real-time decision making systems. It includes an integrated development environment application (IDE) and the runtime engine (sold separately).

Most AI tools and AI middleware applications today are impractical for development of an AI system that can function autonomously in a dynamic environment. Many applications require significant familiarity and/or programming skills to be utilized properly, require a heavy mathematics or statistical background to be productive or deal with a single problem domain.

TinMan provides a development environment and underlying technology for the rapid production of complex multi-module decision making systems ready for deployment in a dynamic environment, abstracting and shielding the user from the unnecessary mathematical tedium associated with these technologies.

The TinMan IDE allows the construction, testing and simulation of an AI system, along with the packaging and export of that system for use in the runtime environment. The runtime environment provides a dynamic link library which loads, reconstructs and then executes all AI systems and coordinates the communication between and among the AI entities and their human controllers, if any.

AI systems developed in TinMan do not have to be autonomous, nor function in a continuous mode. An AI system can be designed to receive an input data set and compute one or more answers – from a single manual user selection event in the host application. However, TinMan AI systems are extremely well-suited for continuous processing of input data in a dynamic environment, allowing for the continuous potentially perfect execution of all desired outputs.

The process of constructing an AI system involves the declaration of a set of variables, a set of outputs and the selection and connection of a set of components. Over 85 types of component templates are available for drag and drop addition to the AI system, in familiar logic flow model. States of decision making can either be made simultaneous or exclusive, as well as the end actions from the system.

As variables and actions are defined and then connected to the components, and as components are connected to each other, appropriate structural modifications are automatically and transparently made by the TinMan IDE. Although an AI system can be viewed at the component level for a module or the entire system, the composition and connectivity of the components is completely abstracted.

With the logical design of a system complete and connections and appropriate interpretations of data set, thorough testing and simulation is performed. The resulting trained system is then packaged and made ready for integration into the host application.

At runtime, the host application loads the packaged AI system via the TinMan runtime engine, feeds the AI system the set of input variable values, the system processes the data via its configured module(s) and updates all system outputs with updated values.

The Build and Deploy Process

The TinMan approach to building and deploying an AI system is designed to be efficient and straight-forward. TinMan AI Builder provides the environment, technology and tools to create and package for runtime, an artificial intelligence core (AI core). The TinMan AI Runtime Library is integrated with a host application to load and utilize that AI core to make runtime decisions in the host system.


Runtime Execution Process

At runtime, the host application utilizes the AI Core through the use of 3 simple steps (each with a single API call). At each instance of time on a continuous basis, (or in response to a single manual event in the host application):

1)      Update the values of variables.

·  This is the information the AI System needs to compute its response. This information may in some cases come from physical sensors on-board the host system, or any other source.

2)      Execute the AI System

·  This function feeds all variables to the AI System, executes the system, and returns the multi-action response pointer filled with all actions (by integer ID) resulting from this cycle of logic.

3)      Act on the returned action identifiers.

·  The host application simply reads and acts on each system output updated following each system execution request.


Middleware Integration

Because of the simplicity and openness of this approach, TinMan AI systems can easily and conveniently integrate with other software systems, databases or specialized AI middleware to best support the operation of the host system. For instance a returned value from the execute API call above may be asking for the calculation of a new 3-D path (from a path-finding application), or to deliver a message wirelessly to a recipient system, or to pull another record from a database for processing.


Integration of Middleware Technologies

(hypothetical examples)

 The simplicity of the TinMan integration approach centers on the fact that a single TinMan function call passes all data to the AI system and the AI system provides  the host application all updated system output values each cycle of execution.

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