A group of researchers from Stanford have developed a way to combine processors and memory on multiple hybrid chips to allow AI to run on battery-powered devices such as smartphones and tablets. The team believes that all manner of battery-power electronics would be smarter if they could run AI algorithms. The problem is efforts to build AI-capable chips for mobile devices have run up against something known as the "memory wall." The memory wall is the name for the separation of data processing and memory chips that have to work together to meet the computational demands of AI. Computer scientist Subhasish Mitra says the transactions between processors and memory can consume 95 percent of the energy needed to perform machine learning and AI, severely limiting battery life.

There aren't many computer chips that you have to build a life support system for. You actually need to supply everything they would normally get in a fully biological body. As Hon Weng Chong, the CEO of Australia's Cortical Labs explains, it's all about creating computer systems that learn -- and that learn faster with less training data. That requires a different approach than standard Intel, Nvidia, or AMD chips, he says. "What we've actually built is a hybrid chip that is comprised of a CMOS sensor, so it's a silicon chip with a very fine mesh of electrodes. They're about 17 microns in pitch and there are about 22,000 of them," Chong told me on The AI Show recently.

A.I. has already gotten to almost sci-fi levels of emulating brain activity, so much so that amputees can experience mind-controlled robotic arms, and neural networks might soon be a thing. Cortical Labs sounds like it could have been pulled from the future. Co-founder and CEO Hong Wen Chong and his team are merging biology and technology by embedding real neurons onto a specialized computer chip. Instead of being programmed to act like a human brain, it will use those neurons to think and learn and function on its own. The hybrid chips will save tremendous amounts of energy with an actual neuron doing the processing for them.