Abstract: A system includes one or more processors and a statically reconfigurable dataflow processor (SRDAP) coupled to the processors which are programmed to receive a first request to generate an instantiation of a computation graph to generate a probability distribution for N classes and retrieve a compiled graph of the computation graph. The computation graph includes a bias node and a probability distribution node for M classes. The bias node provides a biased tensor of size M to the probability distribution node by adding a bias tensor. The processors generate a bias tensor having N entries equal to zero and M?N entries having negative values and then load the compiled graph with the first bias tensor into a first set coarse-grained reconfigurable units of the SRDAP. Execution of the computation graph is initiated on the SRDAP to generate the probability distribution and a first inference is provided.

Abstract: Systems and methods for neuromodulation therapy with repetitive magnetic stimulation of paraspinal regions have been developed for the treatment and prevention of gastroparesis. The methods identify a minimal electromagnetic intensity threshold required to elicit a motor response of 10 ?V at a preferred location within the mid-thoracic region of a subject, and then deliver repetitive magnetic stimulation to the subject at a maximum 150% of the threshold value. Typically, the methods administer about 1,200 stimulations in groups of about 300 pulses having a frequency of about 1 Hz, with a rest period of about 5 minutes between pulses. Typically, the methods repeat the stimuli about twice a day for a period of around 5 days.

Abstract: According to examples, a system for using artificial intelligence (AI) and machine learning (ML) techniques to generate and implement a configurable measurement platform is described. The system may include a processor and a memory storing instructions. The processor, when executing the instructions, may cause the system to access information associated with one or more events occurring on a platform with event activity, log and analyze the one or more events to generate measurement data associated with the event activity, and generate a metric associated with the measurement data. The processor, when executing the instructions, may then generate a computed metric value associated with the metric utilizing the measurement data, implement a platform computation utilizing the computed metric value, and facilitate a decision associated with the platform based on the platform computation.