industry news
Subscribe Now

Intel Labs Improves Interactive, Continual Learning for Robots with Neuromorphic Computing

Neuromorphic research chip Loihi demonstrates real-time learning with 175x lower energy.

Intel Labs, in collaboration with the Italian Institute of Technology and the Technical University of Munich, has introduced a new approach to neural network-based object learning. It specifically targets future applications like robotic assistants that interact with unconstrained environments, including in logistics, healthcare or elderly care. This research is a crucial step in improving the capabilities of future assistive or manufacturing robots. It uses neuromorphic computing through new interactive online object learning methods to enable robots to learn new objects after deployment.

Using these new models, Intel and its collaborators successfully demonstrated continual interactive learning on Intel’s neuromorphic research chip, Loihi, measuring up to 175x lower energy to learn a new object instance with similar or better speed and accuracy compared to conventional methods running on a central processing unit (CPU). To accomplish this, researchers implemented a spiking neural network architecture on Loihi that localized learning to a single layer of plastic synapses and accounted for different object views by recruiting new neurons on demand. This enabled the learning process to unfold autonomously while interacting with the user.

The research was published in the paper “Interactive continual learning for robots: a neuromorphic approach,” which was named “Best Paper” at this year’s International Conference on Neuromorphic Systems (ICONS) hosted by Oak Ridge National Laboratory.

“When a human learns a new object, they take a look, turn it around, ask what it is, and then they’re able to recognize it again in all kinds of settings and conditions instantaneously,” said Yulia Sandamirskaya, robotics research lead in Intel’s neuromorphic computing lab and senior author of the paper. “Our goal is to apply similar capabilities to future robots that work in interactive settings, enabling them to adapt to the unforeseen and work more naturally alongside humans. Our results with Loihi reinforce the value of neuromorphic computing for the future of robotics.”

For further exploration, read about Intel Labs’ research on Intel.com’s neuromorphic computing page.

 

Leave a Reply

featured blogs
Feb 1, 2023
See how Lightelligence used our Platform Architect SoC design tool to develop a multi-die system-in-package including digital, analog, and optical components. The post Customer Spotlight: Lightelligence Optimizes Optical SoC Design with Synopsys Platform Architect appeared f...
Feb 1, 2023
With climate challenges top of mind, the International Maritime Organization (IMO) is taking an ever more active role in establishing a more sustainable global fleet. The IMO2023 regulations have entered into force since November 2022. They are set for the shipping industry t...
Jan 30, 2023
By Hossam Sarhan Work smarter, not harder. Isn't that what everyone is always telling you? Of course, it's excellent advice,… ...
Jan 19, 2023
Are you having problems adjusting your watch strap or swapping out your watch battery? If so, I am the bearer of glad tidings....

featured video

Synopsys 224G & 112G Ethernet PHY IP OIF Interop at ECOC 2022

Sponsored by Synopsys

This Featured Video shows four demonstrations of the Synopsys 224G and 112G Ethernet PHY IP long and medium reach performance, interoperating with third-party channels and SerDes.

Learn More

featured chalk talk

Powering Servers and AI with Ultra-Efficient IPOL Voltage Regulators

Sponsored by Infineon

For today’s networking, telecom, server, and enterprise storage applications, power efficiency and power density are crucial components to the success of their power management. In this episode of Chalk Talk, Amelia Dalton and Dr. Davood Yazdani from Infineon chat about the details of Infineon’s ultra-efficient integrated point of load voltage regulators. Davood and Amelia take a closer look at the operation of these integrated point of load voltage regulators and why using the Infineon OptiMOS 5 FETs combined with the Infineon Fast Constant On Time controller engine make them a great solution for your next design.

Click here for more information about Integrated POL Voltage Regulators