Australian startup, Cortisol Labs is building miniature disembodied brains, using real, biological neurons embedded on a specialized computer chip. Based in Melbourne, the firm is hoping to teach the hybrid mini-brains to carry out the same tasks that software-based artificial intelligence does, but at a fraction of their energy consumption. Presently, Cortisol Labs are working on getting its mini-brains to play the old Atari arcade game Pong.

Cortical Labs used two methods for creating the hardware, it either extracts mouse neurons from embryos, or it uses a technique in which human skin cells are transformed back into stem cells and then induced to grow into human neurons. After that, the neurons are embedded in a nourishing liquid medium on top of a specialized metal-oxide chip. This chip contains a grid of 22,000 tiny electrodes that enable programmers to provide electrical inputs to the neurons and also sense their outputs.

 ‘What we are trying to do is show we can shape the behavior of these neurons,’ Hon Weng Chong, the company’s co-founder, and the chief executive officer said. Although it is starting with Pong, Cortical Labs will be able to master by the end of the year. Chong added that the company’s hybrid chips could eventually be the key to delivering the kinds of complex reasoning and conceptual understanding that today’s A.I. can’t produce. The company’s method, if it proves scalable, also offers a potential solution to one of the most vexing problems facing deep learning: It is incredibly energy-intensive.

 A neuroscientist at University College London, Karl Friston, famous for his work on brain imaging and theoretical underpinnings of how biological systems, saw a demonstration of Cortical Labs’ technology earlier this year and was impressed with the company’s work. Aspects of Cortical Labs’ system are based on Friston’s work, but the neuroscientist has no affiliation with the Australian startup. The idea of trying to integrate biological neurons with semiconductors is not, Friston said, an idea he’d anticipated. “But to my surprise and delight, they have gone straight for the real thing,” he said of Cortical Labs’ use of real biological neurons. “What this group is capable of, to my mind, is the right way to implement ideas to practice.”

 Using real neurons leads to avoidance of several other difficulties that software-based neural networks bring. For instance, to set artificial neural networks to learning, their programmers have to go through a complicated process of manually adjusting the initial coefficients, or weights, that will be applied to each type of data point the network processes. Another challenge that they face is to get the software to balance how much it should be trying to explore new solutions to a problem versus relying on solutions the network has already discovered that work well.

Chong, a former medical doctor, began researching ways to create hybrid biologic-computer intelligence systems about two years ago, along with his co-founder and chief technology officer, Andy Kitchen. Chong said the pair were interested in the idea of A.I. that has the flexibility to perform almost any kind of task as well or better than humans. “Everyone is racing to build AGI, but the only true AGI we know of is biological intelligence, human intelligence,” Chong said. He noted the pair figured the only way to get human-level intelligence was to use human neurons.

Cortisol Labs have been working with mouse neurons and have long been used as proxies for human neurons by neuroscientists because there were long-established methods for extracting and culturing them. Recently scientists at the Allen Institute for Brain Science in Seattle found differences in the proteins that coat mouse and human neurons. this means they have different electrical properties, and those mouse neurons may not be good stand-ins for human ones.