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Thinking at the edge: How neuromorphic computing empowers edge devices
Nov 29, 2023 | Abhishek JadhavCATEGORIES Edge Computing News | Hardware
As experts in the industry believe that Moore’s Law and Dennard scaling is coming to an end, it becomes clear that the traditional approach to improving computer performance has reached its limits. To address these limitations, neuromorphic computing has emerged as a promising solution. Coined by Carver Mead in the late 1980s, the term “neuromorphic” refers to a computing approach inspired by the brain, combining analog and digital components.
Over recent years, the field of neuromorphic computing has expanded, particularly in its application to deep learning and machine learning. When we compare neuromorphic computers to von Neumann machines, which use separate CPUs and memory units, running programs based on explicit instructions, the difference is significant. Neuromorphic computers are inspired from neurons and synapses.
One key advantage of neuromorphic hardware lies in its integration of processing and memory, which helps mitigate the von Neumann bottleneck that can slow down the data processing speed. This integration also reduces the need for frequent data access from main memory, a common operation in conventional computing systems that consumes a substantial amount of energy.
In this article, we will explore the convergence of neuromorphic computing with edge devices and explore its potential benefits in distributed edge computing. Additionally, we will examine industry contributions to the field of neuromorphic computing within the specific context of edge infrastructure. Finally, we will discuss the market opportunities and the future prospects of this advanced computing technology.
Neuromorphic computing meets edge devices
One of the most interesting aspects of neuromorphic computing lies in its ability to operate with low power consumption. This capability can be attributed to two key factors – the event-driven nature of neuromorphic systems and their massive parallelism. Unlike traditional computing hardware, which continuously consumes power, neuromorphic computers only engage in computations when there are specific events or spikes to process. Its inherent parallelism allows many neurons and synapses to operate simultaneously, meaning that only a small portion of the system is active at any given time, while the rest remains idle.Both of these factors have significant implications for the efficiency and effectiveness of computing in edge environments. The event-driven characteristic is particularly advantageous when dealing with thousands of edge devices deployed in remote settings where data is generated sporadically or in response to specific events. For instance, in scenarios such as oil and gas plants, sensors may only produce data when certain parameters exceed normal values, or surveillance cameras may transmit data upon detecting motion. Event-driven processing aligns well with the need for efficient utilization of computational resources and the minimization of power consumption, which is the case of edge computing environments.
Similarly, the concept of massive parallelism holds promise for edge computing. Many edge devices now incorporate multi-core processors or specialized AI accelerators, enabling them to engage in parallel processing of tasks. Edge computing can leverage this feature to execute resource-intensive AI computations concurrently, thereby delivering high performance and quick responses for mission-critical applications. The massive parallelism enables edge devices to reduce latency, provide real-time feedback, and take data-driven actions to enhance operational efficiency within the ecosystem.
Industry contributes to embedded intelligence at the edge
Initially, a significant portion of research and industrial efforts in the field of neuromorphic hardware primarily focused on large-scale implementations that weren’t particularly suitable for edge platforms. However, Intel disrupted this landscape by introducing Loihi, a neuromorphic computing hardware platform based on open-source software frameworks designed for the development of intelligent computing applications.Intel continued its development in advancing neuromorphic technology, which led to the launch of Loihi’s second-generation, which had been developed utilizing Intel’s 4th-generation pre-production process. In this iteration, the company introduced programmable neuron models and a generalized spike messaging system, thereby opening doors to a wide array of neural network models that can be trained in deep learning.
Another embedded manufacturer in the field of commercial neuromorphic computing hardware, BrainChip recently unveiled its second-generation Akida IP solution, built on the neuromorphic principles, with a claim of delivering low-power performance in compact edge devices. This new generation enhances energy efficiency by supporting 8-bit weights, activations, and long-range skip connections, thereby making complex neural networks feasible on edge devices.
Amid all the buzz around these developments in neuromorphic hardware, it is essential to consider their future in the context of the exponential growth of generative AI, which heavily relies on cloud computing resources. As the industry moves toward hybrid AI solutions, the demand for more capable and efficient computing at the network edge becomes increasingly evident.
Neuromorphic computing hardware, such as Akida, get attention for their temporal event-based neural networks that support vision transformers, thus ensuring high accuracy for large language models. The future of these advanced computing technologies holds promise as they play a key role in addressing the evolving landscape of AI and edge computing.
Outlook on neuromorphic computing at the edge
In its 2023 report, Gartner highlights four emerging technologies expected to disrupt industries over the next three to eight years, with neuromorphic computing occupying the top position. According to the market research firm, neuromorphic computing is identified as a crucial enabler that will make a significant impact on existing products and markets.While the continuous evolution of computing hardware is a given, experts believe that there are opportunities to achieve unprecedented levels of algorithmic performance, particularly in terms of speed and energy efficiency, through the utilization of neuromorphic computers. More specifically, graph algorithms and optimization tasks stand to benefit significantly from the extensive parallelism and event-driven operations inherent to neuromorphic computing.
It is anticipated that the growth of neuromorphic computing will play an important role in supporting the requirements of generative AI. The trajectory of neuromorphic computing’s future hinges on the maturation of the technology to meet the demands of the next generation of intelligent applications.
Good Morning Stan9614 & Fellow Chippers ,
Stan , thankyou for providing the above info.... explanation.... for the volume increase yesterday.
Found this article on MSCI which I found rather interesting.
Worth reading the whole article, but for the time poor amoungst us, my two takeaways from article...
1, MSCI acts as a base for ETFs, as of Q4 2022 there were $14,970,000,000,000.00
Or $14.97 TRILLION in assets under management benchmarked to the firms indexes.
2, Each index in the MSCI family is reviewed quarterly & rebalanced two times per year.
Thanks once again Stan.
MSCI: What Does It Stand For and Its Importance
MSCI is an investment research firm that provides indexes, portfolio risk and performance analytics, and governance tools to institutional investors.
Needless to say, Morgan Stanley Capital International ( MSCI ) analysis is held to a higher degree than the odd article written by the Fickle Pickle .
Regards,
Esq.
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Learning
Learning to the Top 🕵♂️
Hi Frangipani,Hi Learning,
I think you misunderstood my post: I never claimed the media release said there was a collaboration between our company and Örebro University. In fact, I myself quoted part of the research paper to prove my point. My original post was in reaction to two forum members who may not have actually read the media release, but had obviously concluded just from seeing that tweet displaying both logos that it was about some kind of collaboration with Örebro University researchers utilising Akida.
I was simply trying to stick to the facts and correct that assumption. And that’s why I called the tweet ‘somewhat misleading’, as IMO it is understandable why someone just looking at the tweet could come to that conclusion and might interpret too much into it. And these kind of misinterpretations will ultimately play into the hands of downrampers. That’s all. Apart from that ambiguous use of Örebro University’s coat of arms, I love the announcement.
Cheers,
Frangipani
P.S.: It just occurred to me that ‘misleading’ may not have been the ideal choice of adjective here, as it could imply intention?The word I would use in German (‘missverständlich’) is much more neutral.
The point I was making is the tweet/ media release wasn't 'missverständlich'. It's information (words) in the tweet/ media release that informative.
My apologies if I have misunderstood your post
.Learning
Ethinvestor
Regular
Where can you look up these infos about shorts ? Thx
buena suerte :-)
BOB Bank of Brainchip
Wow what a day in the US !!!!
And positive for Europe
And positive for Europe
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buena suerte :-)
BOB Bank of Brainchip
ShortMan - Short position graph for IMU
Short position graph and statistics for IMU
Normally around 1 week old data!
But @ndefries has been providing us with previous days shorts % (Thanks for that)
buena suerte :-)
BOB Bank of Brainchip
This was from yesterday (always 1 day behind) Not showing any BRNShortMan - Short position graph for IMU
Short position graph and statistics for IMUwww.shortman.com.au
Normally around 1 week old data!
But @ndefries has been providing us with previous days shorts % (Thanks for that)
Renesas Electronics on LinkedIn: We are thrilled to share that we have designed and tested a 32-bit CPU…
We are thrilled to share that we have designed and tested a 32-bit CPU core based on the open-standard RISC-V instruction set architecture (ISA). We’re among…
RISC-V to the Core: New Horizons
As the RISC-V platform continues to gain momentum, Renesas has developed a RISC-V CPU to expand its IP portfolio and provide the industry’s broadest platform choice to customers.
Evermont
Stealth Mode
Interesting company and tech. Their move out of stealth mode was liked by Rob.
'Monumo is at the forefront of a new technology trend, doing for electric motors what AI has done for drug delivery and genetics - motors that will drive the 21st Century'
monumo.com
'Monumo is at the forefront of a new technology trend, doing for electric motors what AI has done for drug delivery and genetics - motors that will drive the 21st Century'
In the EV market, we are working to:
- deliver optimal motor system designs for electric vehicles of all kinds
- remove the need to use rare earth magnets
- reduce weight, cost and materials for the same performance
- improve recyclability
- achieve high efficiency at across drive cycles all operational speeds both low and high speeds
- solve the problem of overheating
Monumo can now optimise motor systems faster and better than any other company and we’re only just getting started... By running over 2,000,000 simulations a day, we’re creating disruptive motor system designs that are highly improbable to conceive by conventional means.
Reinventing Electric Motors - Monumo
Monumo is a deeptech engineering company focused on creating the world’s best electric motors.
monumo.com
buena suerte :-)
BOB Bank of Brainchip
Mea culpa
prəmɪskjuəs
Morning Buena suerte
Thinking mildly positive.
That big spike in volume yesterday has confused my charting prowess for a little while.
Positive finnish, up three cents i shall go with = $0.25 finnish.
Regards ,
Esq
Your enthusiasm is infectious Esky. Although I'm hoping it's not one of those nasty contagious varieties.
wilzy123
Founding Member
Morning Ethinvestor ,
1, ASX daily shorts report , 4 day old data.displays short no taken out on the day.
Updated after 11:00East Coast time.
2, Shortman , gives a simple list , chart and ranking.
There are several others ....
Regards,
Esq.
1. I was under the impression that this report (https://www.asx.com.au/data/shortsell.txt) was day old data... not 4 day old data.
2, Shortman likely uses 4 day old data scraped from ASIC --> https://asic.gov.au/regulatory-resources/markets/short-selling/short-position-reports-table/
wilzy123
Founding Member
For more information, visit https://www.idtechex.com/en/researc...34-technologies-opportunities-and-markets/972.
Driver Monitoring Systems (DMS), Occupant Monitoring Systems (OMS), Interior Monitoring, Infrared Cameras, Time-of-Flight Cameras, Radars, Capacitive Sensors, Torque Sensors, ECG, EEG, Eye Movement Tracking
As the autonomous driving capabilities, specifically the SAE autonomous driving level, continue to advance, and with the imminent implementation of regional regulations such as Euro NCAP and the EU General Safety Regulation mandating driver monitoring systems (DMS), the global market for in-cabin sensing, encompassing driver monitoring, occupant monitoring, and advanced features like gesture control and vital sign monitoring, is projected to undergo an 11-fold increase from 2020 to 2034. This represents significant market opportunities.IDTechEx’s report on In-Cabin Sensing 2024-2034: Technologies, Players and Markets provides a detailed market forecast for in-cabin sensing technologies, segmented by regions including Europe, China, the USA, Japan, and the rest of the world. The report presents a granular forecast of volume sales and market size for various sensors, including IR cameras, ToF cameras, radar, capacitive steering sensors, and torque steering sensors across different regions.
Regulations
In accordance with the EU General Safety Regulation, all newly manufactured vehicles falling under categories M and N are mandated to incorporate an advanced driver distraction warning system (ADDW) from mid-2024. The ADDW system primarily monitors the movements of the driver’s eyes and issues warnings if signs of distraction are detected. With the enforcement of this regulation looming within a year, IDTechEx has observed a prompt response from several automotive OEMs. For instance, as early as 2019, the BMW X5 was already equipped with driver attention cameras designed to observe the opening of the driver’s eyes and the position of the driver’s head, thus assessing the driver’s level of engagement.While DMS is not a novel concept, traditional DMS typically rely on passive technologies that gather information from the vehicle, such as lane-keeping and driving duration, as well as steering sensors. However, these passive technologies have been shown to be prone to inaccuracies, leading to a high incidence of false positives. In addition, the ADDW regulation stipulates a shift towards actively monitoring driver eye movement, signalling a transition from passive to vision-based active technology.
Despite this transition, IDTechEx acknowledges that the current adoption rate of cameras in DMS, coupled with feedback from the European Automobile Manufacturers Association (ACEA) proposing the commencement of the ADDW system in July 2028, suggests that the widespread implementation of DMS in all new vehicles within categories M and N may extend beyond the initially stipulated mid-2024 deadline.
Apart from Europe, IDTechEx has identified comparable regulations in other key regions. For example, both the Association of Global Automakers and the Alliance of Automobile Manufacturers in the USA have voluntarily pledged to establish standardized rear seat reminders by 2025. In China, the Ministry of Transport has issued a directive titled “Notice of the General Office of the Ministry of Transport on Promoting the Application of Intelligent Video Surveillance and Alarm Technology,” outlining explicit requirements aimed at enhancing driver safety.
Driver Monitoring System
DMS can be classified into two categories: direct/active monitoring and passive/indirect monitoring. Passive monitoring relies on vehicle information such as driving duration and lane-keeping to evaluate driver fatigue, but it has the drawback of potentially generating false positives. On the other hand, active monitoring, prompted by the requirements of the ADDW, utilizes near-infrared (NIR) cameras, which are particularly effective for detecting eye movements without adversely affecting drivers. NIR cameras typically incorporate one or two LEDs and an image sensor, and they are strategically installed in locations such as A pillars and steering columns. Software plays a crucial role in extracting features such as eyelid closure and yawning to identify signs of driver drowsiness or fatigue.Occupant Monitoring System
OMS are experiencing increased traction, propelled by regulations such as the U.S. Federal Communications Commission (FCC) mandating child presence detection (CPD) systems in new cars. OMS, equipped with advanced features like vital signal monitoring and gesture control, predominantly employ time-of-flight (ToF) cameras and/or radar. IDTechEx has seen both radars and ToF cameras being adopted in vehicles already, such as the Li Auto L9 utilizing ToF cameras and the Volvo EX90 incorporating radar modules.
A few examples of automotive OEMs and their sensing methods.
Market Opportunities
Regarding market opportunities, there is a clear trend toward increased adoption of DMS and OMS, driven by upcoming regulations and the emergence of innovative smart cockpit features. DMS is expected to experience rapid and widespread adoption, driven by regulatory mandates. In contrast, while OMS is also growing rapidly, it is foreseen to remain a premium feature predominantly found in mid- and high-end vehicles in the medium-term future. The swift rise of both DMS and OMS presents substantial opportunities for hardware suppliers, including sensor suppliers, chip makers, tier-one suppliers, and others, as well as for software solution providers. IDTechEx’s latest research report titled “In-Cabin Sensing 2024-2034: Technologies, Players, and Markets” provides a thorough analysis of the technological requirements and potential market opportunities in this domain. The research delves into the intricacies of the rapidly evolving landscape, offering insights for both hardware and software solution providers.
The Global In-cabin Sensing Market Will Exceed US$8.5 Billion by 2034
For more information, visit https://www.idtechex.com/en/research-report/in-cabin-sensing-2024-2034-technologies-opportunities-and-markets/972. Driver
www.edge-ai-vision.com
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