Sandia National Labs Academic Alliance Collaboration Report 2020-2021


Bio-inspired computing is related to artificial intelligence (AI) and machine learning (ML) but is distinct from traditional AI in its approach to computer learning. In traditional AI, intelligence is often viewed as being created by a programmer who imparts “intelligence.” Bio-inspired computing begins with simple

organisms that adhere to a set of simple rules. Then over time, within simple constraints, these organisms evolve. Advances in DNA sequencing, various biotechnology manipulations, and the intersection of biology with engineering and mathematics continue to empower the influential field. Plus, bioengineering and bio-inspired research are useful to both society at large and to national security. Numerous applications benefit from brain-inspired (neuromorphic) computing because it responds more quickly to world circumstances than other techniques. Sandia PI Brad Aimone is focused on computational neuroscience modeling and research. Aimone said, “While AI is traditionally expensive, bio-inspired approaches (lower algorithms and hardware) are both more efficient and useful in more systems due to their low size, weight, and power requirements. It’s also quite robust.” He added, “National labs, generally speaking, don’t have this type of neuromorphic computing background or deep expertise. UT Austin has an excellent base for neural science research in its strong computer science program and novel devices


Sandia Academic Alliance Program

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