Heterogeneous integration of imprecise memory devices to enable learning from a very small volume of noisy data

Introduction

The artificial intelligence community, inspired by the tremendous progress made in neuroscience, has recently proposed powerful algorithms to enable effective real-time decision making based on a limited volume of noisy sensory data.

Challenges in Implementation

However, implementing such algorithms in low-power devices remains a challenge due to the energy inefficiency that comes from separating logic and memory in current electronic systems.

Research Developments

For the past 10 years, research groups have been developing alternative electronic components and systems, such as:

1. Brain-inspired computing architectures
2. Novel resistive memory technologies

These developments aim to address the design bottleneck associated with energy inefficiency.

Ideal Memory Characteristics

The critical feature for these new technologies to perform at their best is:

• A very high-density, reliable, non-volatile memory with infinite endurance.

This ideal memory does not exist today, and it is unlikely it will ever exist.

Project Inspiration

This project takes inspiration from the insect’s nervous system. The general aim of DIVERSE is to enable learning from a very limited volume of noisy data based on imperfect, limited density, low endurance, resistive memories.

Insect Decision-Making

Unlike digital systems, insects are not very good at performing precise calculations, but they excel at making extremely energy-efficient real-time decisions by combining sensory data recorded in noisy environments.

Proposed Solution

I thus propose to take inspiration from the well-studied cricket’s nervous system and to use my experience and skills in resistive memories to develop a new technology that expresses robust cognitive behavior while interacting with the environment.

Expected Outcomes

This cross-disciplinary work will lead to the fabrication of an innovative hardware/software platform with:

• Extremely high power efficiency
• Robust cognitive computing capabilities

This new technology will open new perspectives in dynamically developing areas including:

• Service and consumer robotics
• Implantable medical diagnostic microchips
• Wearable electronics