Aaron Hofstadter, creative lead of the team behind ANNIE, the AI that automates security and routine human resource tasks at the corporate headquarters of Xia-Hifa Biologics (creators of the life-saving Junin 2 treatment Arenovir), has published “ANNIE Genesis: Reengineering The Autonomous Neural Network”, the first applied AI descriptive case study in a series of five to be featured over the next few months in the International Journal of Applied New Intelligence (IJANI) as part of their extensive look at practical AI handover:

ANNIE is fundamentally a distributed implementation of the theory first put forth by Aya Ishikawa in this journal on the theoretical framework for neuromorphic cognition in robotics. Building on the feature selection algorithm provided by her, our researchers developed a m-KT classification (Perry and Rajagopal, 2017) and prediction algorithm (Okeke et al., 1997) to evolve a deep neural network to extract reuse opportunities from our training runs. This method has the distinct advantages of high levels of data compression, high accuracy from partial matches (smoothing outliers), rapid multi-pass training and the scalability to be applied within a small or large population with expected efficiency.

To read more please visit the IJANI archives here.