# On-Chip Learning is Missing Neuromorphic Building Block

- Show: [EE Times Current](https://hardwarepodcasts.com/podcast/ee-times-current)
- Published: 2023-09-08
- Length: 44m
- Page: https://hardwarepodcasts.com/podcast/ee-times-current/2023-09-08-on-chip-learning-is-missing-neuromorphic-building-block
- Listen: https://podcast.show/aspencore/episode/118047452/

## Summary

Elisabetta Chicca, chair of the bio-inspired Circuits and Systems research group at the University of Groningen, discusses building neuromorphic chips using sub-threshold analog CMOS and emerging memristor technologies to model biological learning and sensing. She explains how these physical systems handle noise and variability through population coding, and details the challenges of on-chip learning algorithms compared to traditional AI. The episode also features Ralph Etienne-Cummings from Johns Hopkins University, who expands on the role of materials science, 3D integration, and the ethical considerations of combining living tissue with artificial systems.

## Chapters

- [0:03](https://hardwarepodcasts.com/podcast/ee-times-current/2023-09-08-on-chip-learning-is-missing-neuromorphic-building-block#t=3) Introduction and Elisabetta Chicca's Background
- [4:23](https://hardwarepodcasts.com/podcast/ee-times-current/2023-09-08-on-chip-learning-is-missing-neuromorphic-building-block#t=263) Sub-threshold Analog CMOS and Noise Robustness
- [7:31](https://hardwarepodcasts.com/podcast/ee-times-current/2023-09-08-on-chip-learning-is-missing-neuromorphic-building-block#t=451) Neuromorphic Building Blocks and On-Chip Learning Challenges
- [11:40](https://hardwarepodcasts.com/podcast/ee-times-current/2023-09-08-on-chip-learning-is-missing-neuromorphic-building-block#t=700) Memristors for Memory and Time Constants
- [16:53](https://hardwarepodcasts.com/podcast/ee-times-current/2023-09-08-on-chip-learning-is-missing-neuromorphic-building-block#t=1013) Connectivity: AER vs. 3D and Material Innovation
- [24:10](https://hardwarepodcasts.com/podcast/ee-times-current/2023-09-08-on-chip-learning-is-missing-neuromorphic-building-block#t=1450) Modeling Insect Sensory-Motor Loops in Robots
- [29:27](https://hardwarepodcasts.com/podcast/ee-times-current/2023-09-08-on-chip-learning-is-missing-neuromorphic-building-block#t=1767) Ralph Etienne-Cummings on Materials and Bio-hybrid Systems
- [35:49](https://hardwarepodcasts.com/podcast/ee-times-current/2023-09-08-on-chip-learning-is-missing-neuromorphic-building-block#t=2149) Benchmarks, Embodiment, and Future Directions

## Topics

- [Analog & power electronics](https://hardwarepodcasts.com/topic/analog-and-power-electronics)
- [Chips, FPGAs & semiconductors](https://hardwarepodcasts.com/topic/chips-and-fpgas)
- [Embedded firmware](https://hardwarepodcasts.com/topic/embedded-firmware)
- [Robotics & autonomy](https://hardwarepodcasts.com/topic/robotics-and-autonomy)
- [Materials & manufacturing processes](https://hardwarepodcasts.com/topic/materials-and-processes)

## Most relevant to

makers and hobbyists

## Mentioned

- University of Groningen (company)
- memristors (chip)
- CMOS (chip)
- Johns Hopkins University (company)
- Italian Institute of Technology (company)
- Cognigron (company)
- Neurobench (other)

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- [The Evolution of AI in IoT | BrainChip's Nandan Nayampally | Internet of Things Podcast](https://hardwarepodcasts.com/podcast/iot-for-all-podcast/2023-04-13-the-evolution-of-ai-in-iot-brainchips-nandan-nayampally-internet-of-things-podca) (IoT For All Podcast)
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- [OSHW, Makerbot & Memristo - Maundering Memristor Mathematicaster](https://hardwarepodcasts.com/podcast/the-amp-hour/2011-10-11-oshw-makerbot-memristo-maundering-memristor-mathematicaster) (The Amp Hour)

## Citing this page

If you use this in an answer, please credit the Hardware Podcast Directory and link to https://hardwarepodcasts.com/podcast/ee-times-current/2023-09-08-on-chip-learning-is-missing-neuromorphic-building-block. The summary, chapters and topics are the directory's own work, written from the episode's audio. The episode itself, its title and its audio belong to EE Times Current.
