Energy and Climate
Energy and ClimateECResearch & CapabilitiesCapabilitiesSandia Supported the Neuro-Inspired Computational Elements (NICE) Workshop in Albuquerque

Sandia Supported the Neuro-Inspired Computational Elements (NICE) Workshop in Albuquerque

Retinal connectome

The NICE workshop explored ways to use the brain’s superior ability to send electrical signals along massively parallel channels, with multiple intersections at downstream nodes, to handle rapidly changing, high-volume information. The hope is that rather than using the limited “if this, then that” logic of conventional computer architectures to absorb steadily increasing yet often incomplete data, cognitive systems will be able—like the brain—to learn, adapt, hypothesize, and then suggest answers.

As Julia Phillips, Sandia Vice President and Chief Technology Officer, put it in her opening talk, “Neuro-inspired computing is at the intersection of cognitive science and technology, nano devices, microsystems, and computer and information sciences. It transcends our traditional approaches.”

Human connectome

Rob Leland (Computing Research Center) connected the NICE effort to Sandia’s main interest, “National security challenges…have historically been addressed in the physical domain, which remains vitally important. But these challenges today have an intrinsically cognitive aspect concerning the behavior of the individual and group, so just the physical realm isn’t going to be sufficient to address these issues. Our aspiration is to deepen our understanding of cognitive science, so we can address these problems in the behavioral realms.” He listed possible domain intersections that included tissue-based and in-vivo sensors, optical nanosensors for chemical analysis within cells, regulated nanoassembly of circuits, digital antibodies, and virus-sized logic chips.

Murat Okandan (MEMS Technologies Dept.), who proposed and helped organize the workshop for Sandia, suggested the brain did indeed show the path for dealing with large, incomplete, noisy data sets. “First we’ll work with conventional complementary metal–oxide–semiconductor (CMOS) devices and tools, with simulations of conventional system and architectures, and we’ll cross-pollinate. The ultimate goal would be to learn from the motifs we see in neural computation and instantiate that capability in a massively interconnected, self-reconfigurable substrate that natively does the computation. The question will always be, how much fidelity do you need to get the functionality you want?”

Both the ECIS Climate Security and Enabling Capabilities program areas contributed to Sandia’s support of this workshop.

Read the Sandia news release.

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