Neural networks are the status quo of ML today, but relying on abstractions
of the original data doesn't allow for full explainability and increases the risk of bias, hallucinations, and model drift.
Howso runs alongside AI models and allows for model monitoring and debugging of AI and their data. Howso leverages the data itself, rather than an abstraction of the data, allowing for the elimination risks like bias, drift, and lack of transparency and therefore the full realization of enterprise AI/ML investments.
Howso leverages instance-based learning (IBL). IBL is not a new AI concept, but it failed to scale over the last few decades due to performance issues. Howso uncovered advancements in probability and information theory, as well as accelerated universal search algorithms, which solved IBLs performance issues. This research and development has enabled Howso Enterprise to allow organizations to realize their full AI ROI by truly understanding and taking action against any issues in their AI deployments.