Note. Voracity athlete who qualified at the Boston Marathon.

Our brain network contains 100 trillion synapses and 100 billion neurons, consuming only 20 watts of energy. To scale to this level of computing power under high physical fitness loads, the total power consumption of the body needs to be highly efficient. The measure of power (P) is watts of energy (e) measured in volts multiplied by the current (i) in Ohm's law (P=ie). In this case of physical fitness, one of many indicators (i.e., metrics) related to performance is VO2 max or maximal oxygen consumption. Another indicator is Efficiency, measured in sprint power output and cycling efficiency. The relationship between brain power consumption and physical performance and efficiency can be characterized by athletes as being in the Zone.

• Zone-Inspired Algorithms - Accelerate next generation of AI research by exploring under-explored mathematical algorithms from “brain-inspired” massively-scalable approaches.

• Heart rate monitoring - Develop greater abstracting and reasoning capabilities such as applying knowledge from one domain to another domain along with perceiving and learning.

• Better Performance - This model must validate for potential of some human improvement (e.g., 2xU) in energy efficiency and data rate handling capability.

Note. Voracity athlete on Pelton bike in a 45-minute HIIT hill ride.

Performers will be expected to provide at a minimum the following deliverables: negotiated deliverables specific to the proposed effort. These may include reports; experimental and simulated data sets; proposed architectures; protocols; software codes; publications; model data; metrics; validation data; and other associated documentation and results.

1. Report on novel training and related zone-inspired algorithms.

2. Report on updated expectations for energy efficiency improvements and data used of the proposed approach and preliminary discussion of potential hardware implementation (e.g., power meters, heart-rate monitors).

3. Report on initial training and test data sets (simulated or modeled), evaluation metrics, and initial analysis results.