Neuromorphic Computing News and Discussions

Post Reply
User avatar
wjfox
Site Admin
Posts: 8732
Joined: Sat May 15, 2021 6:09 pm
Location: London, UK
Contact:

Neuromorphic Computing News and Discussions

Post by wjfox »

Intel launches 2nd generation neuromorphic chip

8th October 2021

Intel has introduced Loihi 2, its second-generation neuromorphic research chip, featuring eight times the computational neurons compared to the earlier Loihi 1.

Neuromorphic computing is the use of electronic analogue circuits to mimic neurological architectures present in the brain and nervous system. In contrast to digital electronics – where the signals are usually binary (fixed as either "0" or "1") – analogue circuits work with a continuously variable signal. This can provide a tool for scientists to understand the dynamic processes of learning, thinking, and development in the brain. It also enables much greater energy efficiency, speed, and robustness against local failures.

In essence, neuromorphic computers function more like biological brains than traditional computers – and with more and more transistors being packed together onto these chips, the potential for machine consciousness to emerge has been discussed among scholars.

Intel's latest neuromorphic chip, the second-generation Loihi 2, is based on feedback and insights from the Loihi 1, which debuted back in 2017. It contains a million artificial spiking neurons, about eight times that of its predecessor. For a nice visualisation of what a million active neurons look like, see our blog on the new "light beads" microscopy technique that we posted just yesterday.

Loihi 2 is also much more compact, achieving a nearly 50% size reduction. The die area is just 31 mm², compared with 60 mm² for Loihi 1. The neuron state allocation had been fixed at 24 bytes per neuron for the Loihi 1. This is now variable from 0 to 4,096 per neuron for the Loihi 2. The 14 nanometre (nm) process of Loihi 1 has been shrunk down to 7 nm for Loihi 2.

Read more: https://www.futuretimeline.net/blog/202 ... meline.htm


Image
User avatar
wjfox
Site Admin
Posts: 8732
Joined: Sat May 15, 2021 6:09 pm
Location: London, UK
Contact:

Re: Neuromorphic Computing News and Discussions

Post by wjfox »

Photonic computing processes information using light, whilst neuromorphic computing attempts to emulate the human brain. Bring the two together, and we may have the perfect platform for next generation AI, as this video explores:


User avatar
caltrek
Posts: 6509
Joined: Mon May 17, 2021 1:17 pm

Re: Neuromorphic Computing News and Discussions

Post by caltrek »

New Neuromorphic Chip Designed and Built by Researchers
August 17, 2022

Introduction:
(EurekAlert) An international team of researchers has designed and built a chip that runs computations directly in memory and can run a wide variety of AI applications–all at a fraction of the energy consumed by computing platforms for general-purpose AI computing.

The NeuRRAM neuromorphic chip brings AI a step closer to running on a broad range of edge devices, disconnected from the cloud, where they can perform sophisticated cognitive tasks anywhere and anytime without relying on a network connection to a centralized server. Applications abound in every corner of the world and every facet of our lives, and range from smart watches, to VR headsets, smart earbuds, smart sensors in factories and rovers for space exploration.

The NeuRRAM chip is not only twice as energy efficient as the state-of-the-art “compute-in-memory” chips, an innovative class of hybrid chips that runs computations in memory, it also delivers results that are just as accurate as conventional digital chips. Conventional AI platforms are a lot bulkier and typically are constrained to using large data servers operating in the cloud.

In addition, the NeuRRAM chip is highly versatile and supports many different neural network models and architectures. As a result, the chip can be used for many different applications, including image recognition and reconstruction as well as voice recognition.

“The conventional wisdom is that the higher efficiency of compute-in-memory is at the cost of versatility, but our NeuRRAM chip obtains efficiency while not sacrificing versatility,” said Weier Wan, the paper’s first corresponding author and a recent Ph.D. graduate of Stanford University who worked on the chip while at UC San Diego, where he was co-advised by Gert Cauwenberghs in the Department of Bioengineering.
Read more here: https://www.eurekalert.org/news-releases/962039

For a technical written presentation of the research results: https://www.nature.com/articles/s41586-022-04992-8
Don't mourn, organize.

-Joe Hill
Post Reply