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ai-one™ provides application programming interfaces (APIs) that enable developers to build machine learning applications. Our tools enable any programmer to build intelligence into almost any software application.
Our technology transforms information into a generalized rule set and processing environment. ai-one™ is capable of multiple higher-order concept formation, i.e. it can learn new concepts by taking multiple layers of context information into account such as visual information structures in pictures or the whole range of lexical, syntactic, semantic and pragmatic context in text. These information structures are transformed into generalized rule sets, which can then be applied to further input facts.
Unlike other approaches, our API enables machines to learn with or without human supervision. Our technology automatically generates a lightweight ontology (LWO) that detects all relationships among data elements. Learning occurs at the time data is ingested — so it is very fast compared to other approaches.
When incorporated into products as software or embedded as a chip solution, ai-one™ enables solutions that feature new functions with large improvements in cost and performance.
The features and benefits of the holosemantic data space in combination with the mathematical ai-one™ approaches are:
- Self-optimized information processing
- Self-controlled content organization
- Multiple higher-order concept formation (multiple high order co-occurrence)
- Autonomic learning via multiple context recognition (unsupervised machine learning)
- Self-generalizing of learned concepts
Total control and understanding the behavior of the neural cells in the holosemantic data space leads to: Biologically inspired intelligence in computing