Plausible Neural Networks (PNN) Technologies

Plausible Neural Networks (PNN) is designed for the next generation of intelligent computing machines. PNN has several innovative breakthrough technologies, which are under US and PCT patents. PNN employs parallel distributed processing, currently implemented using cluster computing on cloud platforms. In the future, PNN can be implemented using neuromorphic circuits and other physical computing systems.

Currently, artificial intelligence is at the forefront of new technologies. PNN is designed to mimic higher-order human cognitive capabilities, including understanding, knowledge acquisition, forecasting, decision-making, reasoning, logic, belief, and inference. We welcome collaboration in Research & Development in all of these areas.

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Features

  • Self-organization

    PNN learning is entirely unsupervised, based on competitive neuronal signals for entropy reduction.

  • Fast learning algorithms

    PNN has the fastest learning algorithm among the current neural network and machine learning methods.

  • Universal data analysis

     PNN performs clustering, classification, function estimation, associative memory and statistical inference.

  • Parallel distributed processing

    PNN employs parallel and distributed computing for large scale data analysis.

  • Cloud computing

    PNN employs learning and data analysis on cloud platforms.

  • Multi-resolution cluster analysis

     PNN organizes coarse and detail pattern profiles by different network levels.

  • High dimensional model

    PNN builds large scale high dimensional models from data.

  • Knowledge extraction and inference rules

    PNN extracts knowledge and rules for the relationships between variables through network queries.