Benefits of Breaking Down AI Problems into Smaller Pieces
We use a modular building block approach to break down the problem set into smaller manageable subsets and build different AI models/systems to address these subsets.
We then use proprietary AI model integration techniques to solve the overall problem by combining the AI modules into an AI solution.
By breaking a large AI problem into smaller AI components and then solving the smaller AI components individually, we significantly increase the success of our AI solutions, increase the speed of AI development, increases the opportunities to repurpose the modules in other AI solutions, and reduce the overall cost of the AI solution(s). It also provides us a means to adapt the AI modular technologies in different ways and it provides us tangential benefits, such as interoperability to other AI technologies, improved AI monitoring, fast AI prototyping and better integration into larger systems.
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Our AI solutions are considered strong AI from a capabilities point of view and crossing into the theory of mind from a functionalities point of view. Our solutions can adjust to their environments and alter their behavior based on the human operator's environment. Our suite of solutions enables our customers to do more with AI and machine learning.
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We have a substantial suite of innovative solutions that enable multiple products and services.