AI energy demands
Advances in AI have come at the cost of massive energy to operate circuits that perform calculations in Neural Networks. Further advances that will lead to profitable applications and widespread adaptation are threatened by the tremendous electricity demands to both train and deploy AI. The burden AI will put on the power grid, environmental damage and climate concerns will likely cause governments to regulate the electricity AI can be permitted to utilize. Many battery power AI applications are not feasible due to the AI circuits' power requirements.
Energy efficiency in the brain
Nature solves the signal processing energy problem with non-linear, high dynamic range compression of sensory signals that feed into the neural networks of the brain. Neuron signaling values are processed as a logarithmic type response to stimuli. This non-linear signal processing enables the brain to operate with power usage many orders of magnitude less than currently available electronics hardware. This signal processing method enables the brain to process the wide range of sensory input intensities and types.
Energy efficient solutions
NeuralBrew is currently developing innovative chip design, programmable logic, circuit board and software to solve the AI energy problem. We plan to deliver innovative products to the market that will be exponentially more energy efficient than currently available hardware. Our solutions will make possible intensive Machine Learning that will produce profitable and wide spread adaptation of AI.
