In 2022, a research team in Australia got US$400,000 from Australia’s National Intelligence and Security Discovery Research Grants program for DishBrain. They received this money in defense funding for developing a biological programmable computer.
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How was “DishBrain” developed?
A research team in Australia merged lab-grown human brain cells with silicon chips to try and develop a computing system that can work like traditional hardware. These programmable chips are fusing biological computing with artificial intelligence.
The project lead, Associate Professor Adeel Razi said; “in the future may eventually surpass the performance of existing, purely silicon-based hardware,”
He added; “The outcomes of such research would have significant implications across multiple fields such as, but not limited to, planning, robotics, advanced automation, brain-machine interfaces, and drug discovery, giving Australia a significant strategic advantage,”
How does the “DishBrain” work?
The micro-electrode array available in the middle of “DishBrain” was able to read activity in the brain cells, and stimulate the e;ectric signals. Hence, the research team set up a special version of Pong, where brain cells receive information from the brain cells by moving electric stimuli. Followed by this, represents which side of the “screen” the ball was on, and how far away from the paddle it was. Researchers set the brain cells to act on the paddle that allows it to move left and right.
It was trained on a basic reward system as the small clusters of brain cells tend to try to minimize unpredictability in their environment. They rewarded it when the paddle hit the ball with a nice and predictable stimulus. However, when the ball misses, they punish it by giving a four-second unpredictable stimulation.
DishBrain- a lifelong learning:
Even though the research is still in the early stages, the research team noticed a potential for using the same approach to control more complex AI systems. They claimed it as “lifelong learning” in comparison with traditional AI programs at that moment having strong memory limits.
In this context, the project lead Mr, Razi said; “We will be using this grant to develop better AI machines that replicate the learning capacity of these biological neural networks,” He added; “This will help us scale up the hardware and methods capacity to the point where they become a viable replacement for in silico computing.”
Funding:
The research started from the partnership between a startup Cortical Labs and Monash University. They developed around 8,00,000 brain cells on a silicon chip by a combination of rat and human stem cells. Consequently, Cortical Labs explained about this silicon chip; “which has a set of pins that send electrical impulses into the neural structure, and also receive impulses back in return,”
Use case:
This tiny computer chip can stimulate the brain cells and read activity from those brain cells as a biological CPU. The development team also claimed that this technology can also be programmed for elementary tasks such as playing Pong games.
Razi said in the funding announcement; “This new technology capability in the future may eventually surpass the performance of existing, purely silicon-based hardware,”.
Capabilities:
The advanced capabilities of DishBrain can unlock a new generation of machine learning by embodying it in autonomous vehicles, drones, and robots. Hence, it will be a new type of machine intelligence that can learn throughout its lifetime as said by Razi.
This technology also promises machines to continuously learn new abilities without compromising old knowledge. These machines will adapt well to changes and use existing knowledge creatively in new situations. However, they can continue self-optimizing their computing power, memory, and energy.
Razi cleared that; “We will be using this grant, to develop better AI machines that replicate the learning capacity of these biological neural networks. This will help us scale up the hardware and methods capacity to the point where they become a viable replacement for silicon computing.”
