4 results about "Natural intelligence" patented technology

Backpropagation enabled neural network optimization, but is still expensive at scale. An efficient alternative for neural networks must reduce scaling costs and provide high-efficiency optimizations. The presented solution for feed-forward layers is extended compositionally, for transformers containing feed-forward and self-attention layers. These train complex models modularized by self-attentive feed-forward units (SAFFUs), defining efficient architectures that generalize over much less data. Results demonstrate outperformance of backpropagation (alone), compared to application of backpropagation after explicit solutions, which uncover better optima from less data. Ablations train a roadmap of 245 transformers to determine specifications for the SAFFU-transformer, showing several architectural variants appear quite performant. The most performant models appear to not be the most parameterized. Summarizing, well-generalized SAFFU models are efficiently reachable, their architectural explorability via explicit solutions is cheaper and more robust than by backpropagation, and their explicit solutions could be useful for low-resource hardware, where AI might be embodied.

What is disclosed is: a method for natural intelligence (NI) processing for a wireless communication system. The method comprises receiving perceptions comprising a plurality of transmitted symbols, and determining, based on the received plurality of transmitted symbols, whether a suitable posterior model is available. when a suitable posterior model is available, the model is retrieved. The retrieved posterior model is used to estimate a BER, and the estimated BER is communicated to an executive subsystem. when the estimated BER is below a threshold, a prospective action is selected. The selected prospective action is tested in a virtual environment to determine whether the prospective action is beneficial. when the selected prospective action is beneficial, it is communicated to a feedback subsystem. Signals comprising the selected prospective action are received. An adjustment to implement the selected prospective action is determined, and signals to perform the determined adjustment are transmitted.

What is disclosed is: A system for natural intelligence (NI) processing for an intelligent health transponder comprising: A perceptor subsystem coupled to an executive subsystem, wherein: the perceptor subsystem comprises a posterior storage and one or more posterior processing modules. The executive subsystem comprises an executive storage, one or more executive processing modules and a planning module. A feedback subsystem is coupled to the executive subsystem, a transmission subsystem, a reception subsystem and a training dataset. The feedback subsystem comprises a feedback processing module, a feedback subsystem database, and a feedback processing module with a feedback subsystem firmware running on a feedback subsystem processor. An adaptive feedback path control module is coupled to the executive subsystem and the perceptor subsystem.