Water-based chips could be the future of neural networks
Researchers are working on water-based microprocessors that could one day be used as a more diverse alternative to the current wafer architecture of today, with applications ranging from AI to DNA synthesis and likely beyond.
The chips in question are still in the prototype stage, so don't expect processors with built in water cooling just yet, but the way they work is really exciting. They use a technique called ionics, which involves manipulating different ion species in liquid, as opposed to the standard electrons shooting through our semiconductors today.
It's more akin to how the human brain handles data processing, and although the technique may be slower than current semiconductor architectures, scientists believe «the diversity of ionic species with different physical and chemical properties could be harnessed for richer and more diverse information processing.»
That's according to a post(opens in new tab) from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS). Collaborating with startup DNA Script(opens in new tab), researchers from SEAS recently published findings describing how they combined ionic diodes and transistors—something no research team had done before—to develop an ionic circuit.
Although the simple 16 x 16 array is a long way from matching the power of the 100 billion transistors found in Intel's 12th Gen wafers, or the Apple M1 Ultra's 114 billion transistors, the researchers did manage to perform a neural net computing core process.
They used said array to «expand the analog arithmetic multiplication of individual transistors into an analog matrix multiplication.» Yeah I'm pretty lost here, too. Thankfully SEAS postdoctoral fellow Woo-Bin Jung explains that «Matrix
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