Hardware Podcasts

19. Injectable Microchips, 2D Transistors, AI For Spacecraft Diagnosis

The Next Byte Podcast · 25 May 2021 · 25m

AI in practice: one real use of AI described

What this episode covers

Hosts Daniel and Forbode discuss research from Columbia University led by Professor Ken Shepard and Chen Xi on injecting a grain-of-salt-sized microchip powered by ultrasound for medical monitoring. They then cover an international effort involving MIT, UC Berkeley, and TSMC to develop 2D transistors using bismuth contacts to overcome Moore's Law bottlenecks. Finally, they highlight NASA intern Evanna Gizzi's RAISR project, which uses machine learning and classical AI to autonomously diagnose spacecraft failures.

AI in practice

Where this conversation describes AI being used to build or deliver a product. Part of the AI in practice tracker.

Engineering & simulation

The system uses machine learning to analyze historical failure data and classical AI to model engineer thought processes, enabling spacecraft to autonomously diagnose root causes of failures and determine corrective actions without human intervention.

“She used machine learning to learn off the 1000s of data points of what the previous symptoms were when a spacecraft failed and what the cause of that symptom was. … she's using classical AI to predict future failures and transfer into a computer language, how the engineers that design the system might diagnose and fix those failures.”

Speaker 1 · Hear it at 19:23

Most relevant to

early-stage companies

Topics

Mentioned

Companies
Columbia University, MIT, UC Berkeley, Taiwan Semiconductor Manufacturing Company, NASA
Products
RAISR
Also
Ken Shepard, Chen Xi, Evanna Gizzi

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