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By Robert Davis and Desiree Vogt-Lee

Quantum computing is notoriously counterintuitive; it challenges us to grapple with concepts that can be difficult to imagine. We often rely on our sense of sight to make those concepts a little easier to grasp, by representing quantum information with visualization models like the Q-sphere or the circuit diagram, and even creative visual arts projects like the recent Quantum Circuit Disks series. But what happens when we represent quantum using not only imagery, but also sound?

One team of Australian researchers is showing the world exactly what that looks like with a project that turns quantum circuits into music videos. That project, which the creators have named “qMuVi” (“quantum Music Video”), earned the titles of both 1st place winner and Community Choice winner at the recent Qiskit Hackathon Melbourne, a hybrid in-person and virtual event held in early July that marked the first ever Qiskit Hackathon in Australia. The event brought together 35 participants over four days to learn about quantum computing and Qiskit, and to use their new knowledge to hack together a diverse array of novel quantum computing projects. The event as a whole was a tremendous success. But before we talk about that, let’s take a closer look at that winning quantum music videos project.

Chip makers will be able to put a trillion transistors in a package by the end of the decade in a move that will shake up the industry, says Pat Gelsinger, CEO of Intel.

This is one of the key drivers for Intel’s move into offering foundry services, he told leading chip designers in a keynote for the HotChips 34 conference in California last night. This will lead to more sharing of IP and drive new EDA tools, he says.

“We see our way clear to getting to a trillion transistors by the end of the decade,” he said. “With Ribbon FETs, using topside signal and backside power distribution and EUV and high NA we have a good path to the end of the decade,” he said, “With 2.5 and 3D packaging, these four together give us a path to a trillion transistor by the end of the decade.”

A team of researchers in the US and China has designed and built a neuromorphic AI chip using resistive RAM, also known as memristors.

The 48 core NeuRRAM chip developed at the University of California San Diego is twice as energy efficient as other compute-in-memory chips and provides results that are just as accurate as conventional digital chips.

Computation with RRAM chips is not necessarily new, and many startups and research groups are working on the technology. However it generally leads to a decrease in the accuracy of the computations performed on the chip and a lack of flexibility in the chip’s architecture.

Memory boost

Using a non-invasive method of stimulating the brain known as transcranial alternating current stimulation (tACS), which delivers electrical currents through electrodes on the surface of the scalp, Reinhart’s team conducted a series of experiments on 150 people aged between 65 and 88. Participants carried out a memory task in which they were asked to recall lists of 20 words that were read aloud by an experimenter. The participants underwent tACS for the entire duration of the task, which took 20 minutes.

After four consecutive days of this protocol, participants who received high-frequency stimulation of the dorsolateral prefrontal cortex had an improved ability to remember words from the beginning of the lists, a task that depends on long-term memory. Low-frequency zaps to the inferior parietal lobe enhanced participants’ recall of items later in the lists, which involves working memory. Participants’ memory performance improved over the four days — and the gains persisted even a month later. Those who had the lowest levels of general cognitive function before the study experienced the largest memory improvements.