BRN Discussion Ongoing

[Frangipani]

Buyzero, a German website run by Leipzig-based company pi3g that offers services around Raspberry Pi & AI and also currently sells the Akida PCIe Card and the Akida Edge AI Box over here…

Suche: 2 Ergebnisse gefunden für "BrainChip"

Kaufen Sie Raspberry Pi 4, Raspberry Pi Zero und Zero W, Zubehör für Pi Zero und Raspberry Pi 4, und Komplette Kits für Raspberry Pi Boards. Kaufen Sie auch Raspberry Pi 3B+ / 3B / 2 / 1B+, Pimoroni, Adafruit, Arduino, und viel mehr!

buyzero.de

… published a blog post earlier today promoting neuromorphic computing in general as well as BrainChip and Innatera in particular:

Unveiling Neuromorphic Computing: Exploring BrainChip and Innatera's Contributions to Edge AI

Artificial Intelligence (AI) has become an integral part of modern technology, influencing everything from personal assistants to autonomous vehicles. However, as AI systems grow more complex, traditional computing architectures

buyzero.de

Unveiling Neuromorphic Computing: Exploring BrainChip and Innatera's Contributions to Edge AI​

Patrick Hein
Dez 16, 2024

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"Stochastic phase-change neurons" by IBM Research is licensed under CC BY-ND 2.0.

Artificial Intelligence (AI) has become an integral part of modern technology, influencing everything from personal assistants to autonomous vehicles. However, as AI systems grow more complex, traditional computing architectures struggle to keep up with the demands of efficiency, speed, and energy consumption. Neuromorphic computing emerges as a revolutionary approach, drawing inspiration from the human brain's neural networks to process information more naturally and efficiently. In this blog post, we'll delve into the fundamentals of neuromorphic computing, examine the innovative contributions of BrainChip and Innatera, and explore how this technology is shaping the future of Edge AI devices like the Raspberry Pi.

Understanding Neuromorphic Computing​

Neuromorphic computing refers to the design of hardware and computational models that emulate the neuro-biological architectures present in the human nervous system. Unlike traditional computing systems that process instructions sequentially, neuromorphic systems operate in parallel and are event-driven, much like the synapses and neurons in our brains.
This paradigm shift allows for:

• Parallel Processing: Handling multiple computations simultaneously, leading to faster data processing.
• Event-Driven Operations: Reducing energy consumption by processing data only when events (or spikes) occur.
• Adaptive Learning: Enabling systems to learn from patterns and adapt over time without explicit programming.

By mimicking the brain's efficiency, neuromorphic computing aims to overcome the limitations of current AI hardware, particularly in terms of power consumption and scalability.

The Imperative for Neuromorphic Computing​

As AI applications become more ubiquitous, there's an increasing need for devices that can process large amounts of data in real-time while consuming minimal power. Traditional computing architectures are not optimized for the sparse and asynchronous nature of neural network computations. Neuromorphic computing addresses these challenges by offering:

ENERGY EFFICIENCY​

Neuromorphic chips are designed to be energy-efficient by nature. They activate only when necessary, conserving power by remaining idle when there's no data to process. This characteristic is crucial for battery-powered devices and IoT applications where energy resources are limited.

REAL-TIME PROCESSING​

The parallel and event-driven architecture allows for rapid data processing, which is essential for applications requiring immediate responses, such as autonomous driving, robotics, and real-time analytics.

SCALABILITY​

Neuromorphic systems can scale more effectively than traditional architectures. As more neurons and synapses are added, the system's ability to process complex tasks increases without a proportional rise in energy consumption or latency.

BrainChip: Pioneering the Akida Neural Processor​

BrainChip Akida PCIe Board
BrainChip is a leading company in the neuromorphic computing space, known for developing the AkidaTM Neural Processor. Akida, which means "spike" in Greek, is designed to bring AI processing capabilities to the edge, enabling devices to perform complex neural network computations without relying on cloud-based resources.

THE AKIDA ARCHITECTURE​

The Akida processor leverages Spiking Neural Networks (SNNs), which are more biologically plausible models of neural networks. Unlike traditional Artificial Neural Networks (ANNs), SNNs process information using spikes, or discrete events, which allows for more efficient and faster data processing.

Key Features:

• On-Chip Learning: Akida supports on-device learning, enabling systems to learn and adapt in real-time without the need for retraining on external servers.
• Low Latency: The processor's architecture allows for immediate processing of sensory inputs, which is critical for applications like gesture recognition or anomaly detection.
• Energy Efficiency: Consumes significantly less power compared to conventional AI processors, making it ideal for always-on devices.

​

APPLICATIONS OF AKIDA​

The versatility of the Akida processor opens up possibilities across various industries:

• Autonomous Vehicles: Enhances object recognition and decision-making capabilities while minimizing energy usage.
• Smart Home Devices: Improves voice and gesture recognition systems without compromising user privacy by keeping data processing local.
• Healthcare: Enables real-time monitoring and analysis in medical devices, facilitating proactive healthcare solutions.

For those interested in integrating Akida into their projects, exploring our selection of Edge AI devices can provide a starting point.

Innatera: Advancing Neuromorphic Innovation​

Innatera SNP T1
Innatera is another trailblazer in neuromorphic computing, focusing on ultra-low-power processors tailored for real-time sensory processing. Their approach centers on mimicking the brain's ability to process sensory inputs efficiently, making their technology suitable for applications that require immediate and energy-efficient responses.

INNATERA'S TECHNOLOGICAL APPROACH​

Innatera's processors utilize analog computation and event-based processing, which closely replicates the functioning of biological neurons and synapses.

Core Advantages:

• Event-Based Processing: Processes data only when changes occur, reducing unnecessary computations and saving energy.
• Ultra-Low Latency: Delivers immediate responses, crucial for time-sensitive applications like industrial automation or defense systems.
• Compact Design: The processors are designed to be small and lightweight, facilitating integration into a variety of devices.

POTENTIAL APPLICATIONS​

• Industrial IoT: Enhances predictive maintenance by analyzing sensory data in real-time to detect anomalies.
• Wearable Technology: Powers devices that monitor physiological signals, providing instant feedback without draining the battery.
• Environmental Monitoring: Enables sensors to process and respond to environmental changes promptly, useful in smart agriculture or disaster detection systems.

To experiment with Innatera's technology, consider exploring our range of AI development boards.

Neuromorphic Computing and Edge AI Devices​

The intersection of neuromorphic computing and Edge AI devices represents a significant advancement in the deployment of AI applications. Edge devices, which operate at the periphery of the network near the data source, benefit immensely from neuromorphic processors due to their need for efficient, real-time data processing.

SYNERGY OF TECHNOLOGIES​

• Enhanced Performance: Neuromorphic processors accelerate AI computations on edge devices, allowing for more sophisticated applications without cloud dependency.
• Data Privacy: Processing data locally minimizes the transmission of sensitive information over networks, enhancing security.
• Reduced Bandwidth Usage: Limits the amount of data sent to central servers, alleviating network congestion and reducing operational costs.

PRACTICAL IMPLICATIONS​

In sectors like healthcare, neuromorphic edge devices can monitor patient vitals and detect anomalies instantly, potentially saving lives. In manufacturing, they can oversee equipment functioning, predicting failures before they occur, thus optimizing maintenance schedules and reducing downtime.

Raspberry Pi: A Platform for Neuromorphic Exploration​

Image: Raspberry Pi connected to a neuromorphic computing module.
The Raspberry Pi is renowned for its versatility and accessibility, making it an ideal platform for those interested in experimenting with neuromorphic computing. By integrating neuromorphic modules or co-processors, developers can harness the power of neuromorphic computing on a familiar and cost-effective device.

GETTING STARTED​

• Hardware Integration: Neuromorphic accelerators or development kits can be connected to the Raspberry Pi, expanding its capabilities.
• Software Support: Various libraries and frameworks support neuromorphic programming, allowing users to implement SNNs and other models.
• Community Resources: The extensive Raspberry Pi community provides tutorials, forums, and projects that can guide newcomers through the learning process.

EDUCATIONAL AND RESEARCH OPPORTUNITIES​

For educators and students, the Raspberry Pi offers a tangible way to explore advanced computing concepts. Projects can range from simple neural network implementations to complex real-time data processing applications, providing valuable hands-on experience.

To begin your journey, you can find the necessary hardware and accessories on our Raspberry Pi product page.

Challenges and Considerations​

While neuromorphic computing holds great promise, it also presents certain challenges:

PROGRAMMING COMPLEXITY​

Developing applications for neuromorphic hardware often requires a shift from traditional programming paradigms. Understanding spiking neural networks and event-driven architectures can be a steep learning curve for developers accustomed to conventional models.

STANDARDIZATION​

The field is still evolving, and there is a lack of standardized tools and platforms. This can make interoperability and integration with existing systems more complicated.

COST AND ACCESSIBILITY​

High-end neuromorphic hardware can be expensive, potentially limiting access for hobbyists or smaller organizations. However, ongoing research and development are gradually making these technologies more affordable.

​

The Future of Neuromorphic Computing​

Despite the challenges, the potential benefits of neuromorphic computing are driving significant investment and research. As technology matures, we can expect:

• Broader Adoption: Increased standardization and more accessible development tools will facilitate wider use across industries.
• Advancements in AI: Neuromorphic computing may lead to breakthroughs in AI capabilities, particularly in areas like unsupervised learning and cognitive computing.
• Sustainability: The energy efficiency of neuromorphic systems aligns with global efforts to reduce energy consumption and environmental impact.

​

Conclusion​

Neuromorphic computing represents a paradigm shift in how we process information, offering a path toward more efficient, adaptable, and intelligent systems. Companies like BrainChip and Innatera are at the forefront of this innovation, pushing the boundaries of what's possible in AI and edge computing.
For developers, researchers, and enthusiasts, this is an exciting time to explore neuromorphic computing. With platforms like the Raspberry Pi and the availability of development tools, accessing and experimenting with this technology has never been more achievable.

If you're inspired to delve into neuromorphic computing or enhance your AI projects, consider visiting our shop at buyzero.de. We offer a range of Edge AI devices, development boards, and accessories to support your innovation journey. Also don't hesitate to contact us if any questions arise!

 

[Slade]

You know things are hotting up when members of the Crapper start appearing over here. There is desperation in the air and Brainchip is about to shut them up for good. And who got out of the wrong side of the bed this morning. Never mind, it is going to be a very positive week in the lead up to Xmas. Enjoy everyone.

 

[Esq.111]

Good Morning Chippers,

Softbank going hard , .

https://www.cnbc.com/2024/12/16/softbank-ceo-to-announce-100-billion-investment-in-us-during-visit-with-trump.html

Regards,
Esq.

 

[IloveLamp]

https://www.baesystems.com/en/digital/feature/2025-our-top-5-emerging-tech-predictions?utm_campaign=di_predictions_25&utm_medium=organic_social&utm_source=linkedin&utm_content=flipbook_1

BAE Systems Digital Intelligence on LinkedIn: 2025 Predictions Flipbook.pdf

As we edge closer to Christmas and 2024 starts to draw to a close, our experts look ahead to next year and share their top 5 emerging tech predictions for…

www.linkedin.com

 

[JB49]

ICNS | Maritime Situational Awareness using Neuromorphic Sensor Processors

www.westernsydney.edu.au

With our connection to Andre Van Schaik on our Scientific Advisory Board, if there are any limitation on what WSU's own technology can do, it wouldn't surprise me if they experiment with Akida on some of these projects.

Partners on this one are Raytheon, The Royal Australian Navy and BAE Systems.

 

[TECH]

Just as a footnote to comments made about Dr. Chris Eliasmith....we (Brainchip) did have a collaboration with Chris in either
2016, 2017 or 2018....can't be bothered checking the year, but I did reach out to him via Linkedin at the time, so we definitely
know each other, he focused mainly on SpiNNaker from memory.

We are still tied in with Mercedes Benz....that's the main thing to remember, better on the inner than the outer, if not, well, our company
would/could be charged with misrepresentation with having the Mercedes logo still displayed on our homepage.

The above views are solely mine, I own them.

Kind regards to all.....Tech.

 

[SharesForBrekky]

https://www.baesystems.com/en/digital/feature/2025-our-top-5-emerging-tech-predictions?utm_campaign=di_predictions_25&utm_medium=organic_social&utm_source=linkedin&utm_content=flipbook_1

BAE Systems Digital Intelligence on LinkedIn: 2025 Predictions Flipbook.pdf

As we edge closer to Christmas and 2024 starts to draw to a close, our experts look ahead to next year and share their top 5 emerging tech predictions for…

www.linkedin.com

View attachment 74342 View attachment 74343

Ooooh, I like this bit "Neuromorphic computing will become increasingly important in 2025 and beyond, particularly as AI demands more from computing than ever before"

Bring on 2025 I'd say (Still enjoying 2024 though, haha)

 

[7für7]

 

[Fullmoonfever]

Well, since Chris Eliasmith, who as head of the Computational Neuroscience Research Group (CNRG) will be leading the research collaboration with Mercedes-Benz at the University of Waterloo is one of ABR’s Co-Founders, their CTO as well as one of their Directors, I would be immensely surprised if he were to pick another company over ABR to co-collaborate, especially given ABR is a University of Waterloo spin-off!

Whereas the official MB announcement merely stated that the MoU’s research focus is “on the development of algorithms for advanced driving assistance systems”, an article published by the University of Waterloo itself (see below) mentions “software and hardware development”:

“In collaboration with Mercedes Benz, CNRG will apply their neuromorphic computing expertise — designing and developing software and hardware development designed to mimic how the brain works — to making autonomous vehicle technology safer and more efficient. This collaboration highlights the University’s commitment to building meaningful industry and research partnerships for societal, economic, technological, health and sustainable impact.

AV systems struggle with complex tasks like “scene understanding,” which Eliasmith explains is the use of body language and eye contact to interpret whether a pedestrian is about to cross the road. Using simulations and neuromorphic technology, the lab will enhance the system’s perception, prediction and control features, improving its ability to read and react to its environment correctly.”

Using our brains to advance the power and performance of AVs | Waterloo News

An interdisciplinary research team from the University of Waterloo is building systems that mimic the human brain to improve the power efficiency and performance of artificial neural networks like those used in autonomous vehicle (AV) technology. Self-driving cars must navigate, make decisions...

uwaterloo.ca

View attachment 74327

View attachment 74333


Also, have a look at these three University of Waterloo posts relating to the MoU with Mercedes-Benz that Chris Eliasmith reposted - not a single by someone working for BrainChip. Isn’t that rather telling?

LinkedIn Login, Sign in | LinkedIn

Login to LinkedIn to keep in touch with people you know, share ideas, and build your career.

www.linkedin.com

View attachment 74326




True, our CTO used to be a part-time Adjunct Associate Professor at the University of Waterloo (2003-2009) while working on robots in his own company - Iguana Robotics - but that was in a completely different department at the time, namely the Department of Kinesiology at the Faculty of Health, where he was collaborating with the late Aftab Patla on “human visuomotor coordination of locomotion”.


View attachment 74335

Aftab Patla biography | Kinesiology and Health Sciences

Aftab Patla's biography.

uwaterloo.ca

Hi @Frangipani

Thanks for posting that and I had seen it before I posted the LinkedIn post.

There is also the possibility that there is some poetic licence in what Waterloo posted re hardware. Is it solely their hardware, will they utilise some of MBs "industry partners" tech, will it complement what MB are already doing with other partners.

Neuromorphic computing: More energy efficiency in autonomous driving of the future | Mercedes-Benz Group

Future vehicles will include more and more functionalities, with those for autonomous driving being just one example. As this will lead to significantly higher energy requirements, efficiency is a crucial factor.

group.mercedes-benz.com

More energy efficiency in autonomous driving of the future.​

December 06, 2024 – Future vehicles will include more and more functionalities, with those for autonomous driving being just one example. As this will lead to significantly higher energy requirements, efficiency is a crucial factor.
Mercedes Benz is a pioneer in automated driving and safety technologies. The vision for the future is autonomous driving, which will redefine the role of the automobile. Not only will it increase safety, efficiency and comfort on the road. It will also give time back to passengers by allowing them to devote their attention to things other than driving. In addition, the autonomous car will communicate with the cities of the future. To realise all this calls for innovative algorithms and hardware components that overcome the limits of today’s computer hardware.

Through research into artificial neural networks, Mercedes-Benz and its partners from research and industry are breaking new ground in the creation of computer architectures. The company recently announced a research cooperation with the Canadian University of Waterloo in the field of neuromorphic computing. By mimicking the workings of the human brain, neuromorphic computing could make AI computations significantly more energy-efficient and faster.

Neuromorphic computing (NC) mimics the way the human brain works and could therefore make AI calculations more efficient and faster.

Innovative hardware components such as circuit boards are required to overcome the limitations of today's computer hardware.

Safety systems could, for example, recognise traffic signs, lanes and other road users much better and react faster, even in poor visibility.

Instead of full images (frames), neuromorphic camera for interior monitoring delivers individual pixels (events – hence the name event-based camera), which is extremely fast with minimal delay.

Safety systems could, for example, recognise traffic signs, lanes and other road users much better and react faster, even in poor visibility. And they could do so ten times more efficiently than current systems. There would be benefits in using a neuromorphic camera for interior monitoring, for example. Instead of full images (frames), it delivers individual pixels (events – hence the name event-based camera). The process is extremely fast with minimal delay. This means, for instance, a rapid system reaction to the blinking of a driver’s eye caused by fatigue. Neuromorphic computing has the potential to reduce the energy required for data processing in autonomous driving by 90 per cent compared to current systems.

 

[JB49]

GPS-alternative tech swaps satellites for Earth fingerprints

The as-yet-unnamed new system, which is being developed by Australian firm Advanced Navigation and European missile manufacturer MBDA, swaps the GPS receiver for a downward-facing...

www.militaryaerospace.com

NILEQ, Advanced Navigation Aim to Give Drones GPS-Free Navigation — By Scanning Earth's Fingerprint

Unlike radio signals, which can be jammed, NILEQ's tech uses neuromorphic computing to turn ground scans into an absolute position fix.

www.hackster.io

NILEQ - RESILIENT ABSOLUTE POSITIONING

www.nileq.co.uk

Australian company MBDA in a joint venture with Airbus and Nileq to use a neuromorphic camera/sensor to map the terrain for UAV's

There is a pending patent - Can anybody find it?

The system the companies are developing is based on a technology developed by MDBA Systems subsidiary NILEQ, which maintains a database of the Earth's surface. Data captured by scanners on UAVs and other aerial vehicles is processed by brain-like neuromorphic processors and quickly matched to the database

 

[Fullmoonfever]

Hi @Frangipani

Thanks for posting that and I had seen it before I posted the LinkedIn post.

There is also the possibility that there is some poetic licence in what Waterloo posted re hardware. Is it solely their hardware, will they utilise some of MBs "industry partners" tech, will it complement what MB are already doing with other partners.

Neuromorphic computing: More energy efficiency in autonomous driving of the future | Mercedes-Benz Group

Future vehicles will include more and more functionalities, with those for autonomous driving being just one example. As this will lead to significantly higher energy requirements, efficiency is a crucial factor.

group.mercedes-benz.com

More energy efficiency in autonomous driving of the future.​

December 06, 2024 – Future vehicles will include more and more functionalities, with those for autonomous driving being just one example. As this will lead to significantly higher energy requirements, efficiency is a crucial factor.
Mercedes Benz is a pioneer in automated driving and safety technologies. The vision for the future is autonomous driving, which will redefine the role of the automobile. Not only will it increase safety, efficiency and comfort on the road. It will also give time back to passengers by allowing them to devote their attention to things other than driving. In addition, the autonomous car will communicate with the cities of the future. To realise all this calls for innovative algorithms and hardware components that overcome the limits of today’s computer hardware.

Through research into artificial neural networks, Mercedes-Benz and its partners from research and industry are breaking new ground in the creation of computer architectures. The company recently announced a research cooperation with the Canadian University of Waterloo in the field of neuromorphic computing. By mimicking the workings of the human brain, neuromorphic computing could make AI computations significantly more energy-efficient and faster.

Neuromorphic computing (NC) mimics the way the human brain works and could therefore make AI calculations more efficient and faster.

Innovative hardware components such as circuit boards are required to overcome the limitations of today's computer hardware.

Safety systems could, for example, recognise traffic signs, lanes and other road users much better and react faster, even in poor visibility.

Instead of full images (frames), neuromorphic camera for interior monitoring delivers individual pixels (events – hence the name event-based camera), which is extremely fast with minimal delay.

Safety systems could, for example, recognise traffic signs, lanes and other road users much better and react faster, even in poor visibility. And they could do so ten times more efficiently than current systems. There would be benefits in using a neuromorphic camera for interior monitoring, for example. Instead of full images (frames), it delivers individual pixels (events – hence the name event-based camera). The process is extremely fast with minimal delay. This means, for instance, a rapid system reaction to the blinking of a driver’s eye caused by fatigue. Neuromorphic computing has the potential to reduce the energy required for data processing in autonomous driving by 90 per cent compared to current systems.

Further to the above, another post by MB implies that a lot of these collaborations etc in Canada are part of an understanding with the Govt.

The academic research collaboration and participation in the OVIN Incubators Program are the latest in a series of initiatives underpinned by the company’s Memorandum of Understanding (MoU) with the government of Canada, signed in 2022. The aim of the MoU is to strengthen cooperation across the electric vehicle value chain. Through the partnership with the Ontario government through OVIN, Mercedes-Benz is accelerating and expanding its presence by tapping into Ontario’s international acclaim as a centre for tech development, recognizing the province’s significance for Mercedes-Benz’s global innovation network.

Also within the post they outline the Waterloo Collab and as @Frangipani pointed out, the key focus is algos.

Collaboration with the University of Waterloo​

Mercedes-Benz and the University of Waterloo have signed a Memorandum of Understanding to collaborate on research led by Prof. Chris Eliasmith in the field of neuromorphic computing. The focus is on the development of algorithms for advanced driving assistance systems. By mimicking the functionality of the human brain, neuromorphic computing could significantly improve AI computation, making it faster and more energy-efficient. While preserving vehicle range, safety systems could, for example, detect traffic signs, lanes and objects much better, even in poor visibility, and react faster. Neuromorphic computing has the potential to reduce the energy required to process data for autonomous driving by 90 percent compared to current systems.

The work with the University of Waterloo complements a series of existing Mercedes-Benz research collaborations on neuromorphic computing. One focus is on neuromorphic end-to-end learning for autonomous driving. To realize the full potential of neuromorphic computing, Mercedes-Benz is building up a network of universities and research partnerships. The company is, for example, consortium leader in the NAOMI4Radar project funded by the German Federal Ministry for Economic Affairs and Climate Action. Here, the company is working with partners to assess how neuromorphic computing can be used to optimise the processing of radar data in automated driving systems. In addition, Mercedes-Benz has been cooperating with Karlsruhe University of Applied Sciences. This work centres on neuromorphic cameras, also known as event-based cameras.

Mercedes-Benz expands open innovation activities in Canada alongside research in neuromorphic computing. | Mercedes-Benz Group

Mercedes-Benz and the Ontario government through the Ontario Vehicle Innovation Network (OVIN) establish incubators to foster startup creation, startup scouting and automotive innovation in Ontario, Canada. The OVIN Incubators will join the growing international Mercedes-Benz STARTUP AUTOBAHN...

group.mercedes-benz.com

 

[Fullmoonfever]

Gotta love MBs representation (or is it real ) of a board for neuromorphic

 

[Esq.111]

Morning Fullmoonfever ,

Believe that board in your above picture is real .

Sighted it some time ago and tried to find the company behind it , to no avail .

Regards ,
Esq.

 

[Space Cadet]

Like a piece of this.

https://www.militaryaerospace.com/c...ntelligence-ai-and-machine-learning-for-c4isr

SC

 

[JoMo68]

There’s some serious skullduggery going on with our share price. Two big announcements and we’re going down! WTAF!

 

[Fullmoonfever]

There’s some serious skullduggery going on with our share price. Two big announcements and we’re going down! WTAF!

 

[H.E. Pennypacker]

There’s some serious skullduggery going on with our share price. Two big announcements and we’re going down! WTAF!

As previously mentioned yesterday’s announcement was not a big announcement. We currently have a market cap of around 470 million.
If we want the SP to actually move we need a deal with millions attached or with a tier 1 name. Not a minor company that brings in a few million in revenue.

 

[Labsy]

As previously mentioned yesterday’s announcement was not a big announcement. We currently have a market cap of around 470 million.
If we want the SP to actually move we need a deal with millions attached or with a tier 1 name. Not a minor company that brings in a few million in revenue.

I suspect, given our dominance in space news as the latest innervation in Europe and the recent award by the US Air Force, SpaceX will be well aware of our existence..... Just a matter of time and BOOM!!!! You will get your tier 1 announcement.... Don't you worry about that.

 

[Fullmoonfever]

Suspect our Akida may also feature in this work. From a few hours ago.

Frontgrade Gaisler Leads European Initiative for Ultra Deep Sub-Micron Semiconductor Technology for Space Applications

Under a newly signed contract with the European Space Agency (ESA), Frontgrade Gaisler is leading an ambitious initiative to secure European sovereign

www.businesswire.com

Frontgrade Gaisler Leads European Initiative for Ultra Deep Sub-Micron Semiconductor Technology for Space Applications​

Dr. Dietmar Pilz, Director of Technology, Engineering & Quality at ESA (left) with Sandi Habinc, General Manager at Frontgrade Gaisler, signed a contract for a Gaisler-led initiative as part of the ESA-backed “EEE Space Component Sovereignty for Europe” program. Frontgrade Gaisler will work with its industry partners to develop foundational technology for some of the world’s most sophisticated integrated circuits for space, leveraging Ultra Deep Sub-Micron (UDSM) nodes as advanced as 7nm. (Photo: Business Wire)

• 
• 

December 16, 2024 11:23 AM Eastern Standard Time
GOTHENBURG, Sweden--(BUSINESS WIRE)--Under a newly signed contract with the European Space Agency (ESA), Frontgrade Gaisler is leading an ambitious initiative to secure European sovereignty in advanced semiconductor technologies for space applications. This project aims to develop foundational technology for some of the world’s most sophisticated integrated circuits for space, leveraging Ultra Deep Sub-Micron (UDSM) nodes as advanced as 7nm.

“ESA is proud to support this groundbreaking initiative, which represents a critical step toward European sovereignty in advanced semiconductor technologies for space”
Post this

As part of the ESA-backed “EEE Space Component Sovereignty for Europe” program, Frontgrade Gaisler is collaborating with key industry leaders such as imec (Interuniversity Microelectronics Centre vzw) and IMST GmbH, to leverage their collective expertise in high-performance microprocessors, advanced semiconductor libraries, and high-speed memory interfaces. To meet the ever-increasing performance needs of space computing, the project will incorporate additional state-of-the-art technologies from adjacent developments and partners, including high-speed serial interfaces, die-to-die interconnect, and System-in-Package concepts.
“ESA is proud to support this groundbreaking initiative, which represents a critical step toward European sovereignty in advanced semiconductor technologies for space,” said Boris Glass, Technical Officer at ESA. “By investing in Ultra Deep Sub-Micron processes such as 7 nm FinFET CMOS technology, we are ensuring that Europe remains at the forefront of space innovation and autonomy, securing the technology necessary for next-generation space exploration and satellite constellations. This collaboration with Frontgrade Gaisler and its industry partners is essential to meet the growing demands of the space sector and strengthen Europe’s capabilities in the global arena.”
The consortium’s initial focus is to establish radiation-hardened libraries and Intellectual Property (IP) cores that will serve as the foundation for highly reliable and efficient UDSM-based integrated circuits. Building on this foundation, an advanced RISC-V microprocessor prototype will be developed and tested for performance and radiation.
In a future project, this microprocessor prototype will be advanced toward full functionality, production, and qualification, providing Europe with autonomous and highly competitive space computing capabilities, facilitating advanced AI and Edge computing to meet the demands of next-generation satellite constellations and deep-space missions.
"Frontgrade Gaisler has decades of experience supplying the space sector with advanced semiconductor products, which lends itself well to the work of EEE Space Component Sovereignty for Europe,” said Sandi Habinc, General Manager at Frontgrade Gaisler. “Through this program, we’re leveraging our expertise – along with the other participants – to advance UDSM technology and to strengthen our position in this industry.”
With its extensive history, Frontgrade Gaisler is well positioned to lead the efforts toward the next-generation, space-grade microprocessor technology. Since inception, the team has been committed to providing tangible benefits that help progress and grow the entire space community and that enable new types of space missions, offering long-term growth opportunities for the industry as a whole.
About the European Space Agency
The European Space Agency (ESA) is Europe’s gateway to space. Its mission is to shape the development of Europe’s space capability and ensure that investment in space continues to deliver benefits to the citizens of Europe and the world.
About Frontgrade Gaisler
Frontgrade Gaisler, a Frontgrade company, is a leading provider of radiation-hardened microprocessors and IP cores for critical applications, particularly in the space industry. The company’s processors are ideal for any space mission or other high-reliability application due to their reliability, fault tolerance, and radiation tolerance. Frontgrade Gaisler microprocessors can be found all over the solar system, from Mercury to Neptune.
About Frontgrade
Frontgrade Technologies is the leading provider of high-reliability, radiation-hardened solutions for defense, intelligence, commercial, and civil applications. The Company offers a complementary and integrated suite of mission critical electronics. Key products include rad-hard components, mission processing subsystems, high power amplifiers, custom ASICs, motion control systems, waveguides, antennas, and power management solutions. For more information, visit www.frontgrade.com.

 

[Boab]

There’s some serious skullduggery going on with our share price. Two big announcements and we’re going down! WTAF!

Nuff said @JoMo68