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Physicists Simulate Artificial Brain Networks with New Quantum Materials

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Isaac Newton's groundbreaking scientific productivity while isolated from the spread of bubonic plague is legendary. University of California San Diego physicists can now claim a stake in the annals of pandemic-driven science. A team of UC San Diego researchers and colleagues at Purdue University have now simulated the foundation of new types of artificial intelligence computing devices that mimic brain functions, an achievement that resulted from the COVID-19 pandemic lockdown. By combining new supercomputing materials with specialized oxides, the researchers successfully demonstrated the backbone of networks of circuits and devices that mirror the connectivity of neurons and synapses in biologically based neural networks. Like biologically based systems (left), complex emergent behaviors--which arise when separate components are merged together in a coordinated system--also result from neuromorphic networks made up of quantum-materials-based devices (right).


Artificial intelligence is energy-hungry. New hardware could curb its appetite.

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WEST LAFAYETTE, Ind. -- Just to solve a puzzle or play a game, artificial intelligence can require software running on thousands of computers. That could be the energy that three nuclear plants produce in one hour. A team of engineers has created hardware that can learn skills using a type of AI that currently runs on software platforms. Sharing intelligence features between hardware and software would offset the energy needed for using AI in more advanced applications such as self-driving cars or discovering drugs. "Software is taking on most of the challenges in AI. If you could incorporate intelligence into the circuit components in addition to what is happening in software, you could do things that simply cannot be done today," said Shriram Ramanathan, a professor of materials engineering at Purdue University.


Spintronics research lays path for new type of memory

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With demands for ever more powerful computing devices, researchers are pushing at the limits of physics to explore alternatives to conventional computing, such as with photonics, quantum simulators, and spintronics. "Quantum materials hold great promise for improving the capacities of today's computers," said Professor Andrew Kent, a senior investigator. "The work draws upon their properties in establishing a new structure for computation." Kent worked alongside collaborators from the University of California-San Diego and the University of Paris-Saclay on the project. Professor Ivan Schuller, a San Diego physicist, explained: "Since conventional computing has reached its limits, new computational methods and devices are being developed. These have the potential of revolutionising computing and in ways that may one day rival the human brain."


Brain-inspired computing: We need a master plan

arXiv.org Artificial Intelligence

New computing technologies inspired by the brain promise fundamentally different ways to process information with extreme energy efficiency and the ability to handle the avalanche of unstructured and noisy data that we are generating at an ever-increasing rate. To realise this promise requires a brave and coordinated plan to bring together disparate research communities and to provide them with the funding, focus and support needed. We have done this in the past with digital technologies; we are in the process of doing it with quantum technologies; can we now do it for brain-inspired computing?


Taking lessons from a sea slug, study points to better hardware for artificial intelligence

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Researchers mimic the animal kingdom's most basic signs of intelligence in quantum material WEST LAFAYETTE, Ind. -- For artificial intelligence to get any smarter, it needs first to be as intelligent as one of the simplest creatures in the animal kingdom: the sea slug. A new study has found that a material can mimic the sea slug's most essential intelligence features. The discovery is a step toward building hardware that could help make AI more efficient and reliable for technology ranging from self-driving cars and surgical robots to social media algorithms. The study, publishing this week in the Proceedings of the National Academy of Sciences, was conducted by a team of researchers from Purdue University, Rutgers University, the University of Georgia and Argonne National Laboratory. "Through studying sea slugs, neuroscientists discovered the hallmarks of intelligence that are fundamental to any organism's survival," said Shriram Ramanathan, a Purdue professor of materials engineering.