BRN Discussion Ongoing

[Diogenese]

It may be that FG are working on another function that requires Gen 2 and TENNs hence the provision for another licence.
As space craft evolve there will be many different functions that require AKIDA. The size of the royalty indicates the importance of AKIDA to this program.

Yeah ... but ...

the nother licence is for Akida 1 IP for EU$150k oar 15%.

So for the immediate future, Akida 1 fits the bill.

There is nothing preventing FG negotiating an Akida 2 licence in future, but I expect it will be significantly more expensive.

 

[Diogenese]

What I liked about the FG announcement was the word augment.

View attachment 74291
View attachment 74290

... well I s'pose Peter's got a bit more time on his hands now ... how does he go on a ladder?

 

[rgupta]

Too many what ifs. We don’t want to have to depend on another company to maybe start generating large revenue. We want an established company that already generates high revenue. The AI industry is currently booming and making more money than ever so this small amount with such a minor company doesn’t get me that excited. Hopefully something with a bigger name arrives soon

I feel we can act like a tree than a climber. Brainchip have a merit of a tree, then why to remain like a parasite.

 

[FiveBucks]

Contract!!! Well done Sean. Now can you lock in about 20 more please!!

19 to go!

 

[Braintonic]

I have stayed away off this site due to its bias, but anyone here that seriously think there will be an announcement prior to Christmas on the iword of who is running this company Is delirious. Why would anyone sell shares in their company if they knew in the next 4 weeks that a deal would fall. Hehir has constantly strung shareholders along and continues to do it.You all had your chance to vote him out last AGM but no like lemmings you followed his words, Remember them IMMINENT…… what have we got FKN not a word since. Lemmings that what I called you bunch.IWork for one of the largest worldwide companies and today I had to resort to send a email to one of our General Managers as they were looking at integrating AI into our company. I forwarded him Brainchips website link In the hope of achieving something. It only takes 200 signatures from shareholders to instigate a extraordinary AGM. If Christmas hits and nothing announced.I suggest as a shareholder you must think TIME TO GO HEHIR. You missed your chance last AGM don’t make the same mistake. Don’t wait till there is no money left in the bank account get rid of them.

Sorry, what do you mean? No offence intended Galaxy, just tongue in cheek.

 

[HopalongPetrovski]

Sorry, what do you mean? No offence intended Galaxy, just tongue in cheek.

Yes, hasn't aged terribly well has it?
Still, no-one expects the......

 

[Galaxycar]

I stand by my statement, if the happy clappers think that a $150k up deal is going to change shareholders angst we’ll suggest you reconsider. How many shareholders have lost 80% plus of their shareholder value, A majority is the answer, cause this bullshit NDA path management have gone down. If Brainchip would have come out and quantified that the 10% net sales royalty Brn estimate would bring in estimated 20-30 million year ending 2026 I would doubt myself. But no they leave us guessing tell us nothing, All this absolute crap about shorters getting burnt today,is that crap they are laughing all the way to the bank they are still in control, Shares up 1 CENT, Why because the shorters know if they get in the shit management will sell them 50 millions shares just like in the last capital raise. Yes the sofisticated investers were the shorters. Management sold us all out to the shorters to stay afloat. So no the next investor votes won’t be any different than the last, votes will go against them and in a substantial way. The shorters aim is to get rid of management, choke the supply of money, keep the share price low at any cost, to upset shareholders. I cant for the life of me can’t see anything changing, WOW 150K deal, ALL THE HAPPY CLAPPERS HERE have stated wait for the first IP deal wait for the first IP Deal well we waited and what we were still all refreshing over share accounts all day 100 times 1 FUCKEN CENT. Pantene that

 

[manny100]

I stand by my statement, if the happy clappers think that a $150k up deal is going to change shareholders angst we’ll suggest you reconsider. How many shareholders have lost 80% plus of their shareholder value, A majority is the answer, cause this bullshit NDA path management have gone down. If Brainchip would have come out and quantified that the 10% net sales royalty Brn estimate would bring in estimated 20-30 million year ending 2026 I would doubt myself. But no they leave us guessing tell us nothing, All this absolute crap about shorters getting burnt today,is that crap they are laughing all the way to the bank they are still in control, Shares up 1 CENT, Why because the shorters know if they get in the shit management will sell them 50 millions shares just like in the last capital raise. Yes the sofisticated investers were the shorters. Management sold us all out to the shorters to stay afloat. So no the next investor votes won’t be any different than the last, votes will go against them and in a substantial way. The shorters aim is to get rid of management, choke the supply of money, keep the share price low at any cost, to upset shareholders. I cant for the life of me can’t see anything changing, WOW 150K deal, ALL THE HAPPY CLAPPERS HERE have stated wait for the first IP deal wait for the first IP Deal well we waited and what we were still all refreshing over share accounts all day 100 times 1 FUCKEN CENT. Pantene that

This deal is a real positive as is the recent contract simply because they validated the product and represent another step in the BRN journey to aspirational leadership in the Edge industry over the next decade.
The knocks are just smoke screens set up by THE NAPPY CRAPPERS.
Inside holdings at around 15 5% to 16.6% will effectively prevent any board spill attempts and takeovers less than 'to good to refuse offers'.

 

[Diogenese]

Hello fellow brners,
Happy silly season soon,
Been waiting like everyone else but things are slowly being uncovered and it was very nice to see this announcement this morning re Frontgrade Gaisler inc a nice mention in the Herald Sun.
BrainChip Holdings (ASX:BRN) has announced that Frontgrade Gaisler, a provider of radiation-hardened microprocessors for space, has licensed its Akida 1.0 Neuromorphic AI IP for integration into space-grade, fault-tolerant chips. BrainChip will receive royalties from Frontgrade.

I also happy to come across an interesting article on Risc-V with Brainchip mentioned. (this probably has surfaced here on tse before) but given the injection of funds by Jeff Bezos to Tenstorrent in early December, I thought it might be worth a revisit of it especially the part where it says Synergies between Risc-v, Tenstorrent and Brainchip.
The combination of Tenstorrent’s GPU capabilities and BrainChip’s neuromorphic approach demonstrates the broad applicability of RISC-V in both conventional AI workloads and next-generation computational neuroscience



It's good to be a shareholder.
Hope Bravo gets new running shoes for xmas.

Hi MDhere,

What do you know d Dr Jerry A. Smith?

While they say that no publicity is bad publicity, I'm not sure I understand his assertion that Akida uses RISC-V.

RISC-V is software, and Akida does not use software.

The links to his Linkedin and other links use such termd and buzzwords as "agentic", "heuristic", "quantum entanglement", "free energy principle (there's a law of thermodynamics about this)", so they are rabit holes I keep a good 40 foot pole's length away.

The titles of some of his recorded talks does little to allay my doubts:

https://soundcloud.com/drjerryasmith

Not so much the far edge as the far side.

 

[Galaxycar]

What if one of the 16.6% are the ones instigating the turmoil as yourself the last announcement shorts went up,price stayed still, this announcement without seeing the short sales yet,moneys on they went up, aim of the game upset shareholders get rid of management. Tommorrow unless something strange happens shares will be even or down 1.5 cent. Result shareholders will start whinging again rinse and repeat.

 

[Fullmoonfever]

I suppose one could conclude that MB were still working on neuromorphic with Akida through pretty much all of 2024

https://de.linkedin.com/in/sreelakshmi-rameshan-037159b1

Sreelakshmi Rameshan​

Graduate student at University of Stuttgart| Computer Science​

Mercedes-Benz AG University of Stuttgart​

Stuttgart, Baden-Württemberg, Germany​

Experience​

• 
  

  Master Thesis​

  Mercedes-Benz AG​

  Feb 2024 - Sep 2024 8 months
  Stuttgart, Baden-Württemberg, Germany
  For my master's thesis at Mercedes-Benz AG, I conducted an in-depth analysis of frameworks and strategies for converting neural networks (NN) into spiking neural networks (SNN) for neuromorphic processors. The project involved evaluating SDKs for neuromorphic hardware like BrainChip Akida, Intel Loihi, and SynSense to assess their compatibility, functionality, and performance. Using frameworks such as MetaTF, Lava, and Sinabs, I translated the PilotNet model into SNNs and analyzed their practical feasibility, documenting challenges and conducting performance evaluations based on metrics like MSE and accuracy. This work also explored the use of neuromorphic processors as accelerators for neural networks, identifying hurdles and proposing solutions to optimize translation processes.

 

[Frangipani]

I suppose one could conclude that MB were still working on neuromorphic with Akida through pretty much all of 2024

https://de.linkedin.com/in/sreelakshmi-rameshan-037159b1

Sreelakshmi Rameshan​

Graduate student at University of Stuttgart| Computer Science​

Mercedes-Benz AG University of Stuttgart​

Stuttgart, Baden-Württemberg, Germany​

Experience​

• 
  

  Master Thesis​

  Mercedes-Benz AG​

  Feb 2024 - Sep 2024 8 months
  Stuttgart, Baden-Württemberg, Germany
  For my master's thesis at Mercedes-Benz AG, I conducted an in-depth analysis of frameworks and strategies for converting neural networks (NN) into spiking neural networks (SNN) for neuromorphic processors. The project involved evaluating SDKs for neuromorphic hardware like BrainChip Akida, Intel Loihi, and SynSense to assess their compatibility, functionality, and performance. Using frameworks such as MetaTF, Lava, and Sinabs, I translated the PilotNet model into SNNs and analyzed their practical feasibility, documenting challenges and conducting performance evaluations based on metrics like MSE and accuracy. This work also explored the use of neuromorphic processors as accelerators for neural networks, identifying hurdles and proposing solutions to optimize translation processes.

Hi Fullmoonfever,

that’s the same Master’s thesis I had alluded to in a previous post of mine I had not yet followed up on:

And then there is also a recent Master’s thesis sort of connected to MB’s neuromorphic research (more on that later, as posts have a limit of 10 upload images) that strengthens my belief that MB are still weighing their options…


Lots of points raised that cannot simply be glossed over and that suggest to me Mercedes-Benz is nowhere near to implementing neuromorphic technology at scale into serial cars.

Interested to hear your or anyone else’s thoughts on those points.

However, it was already completed in August 2024, so I did not come to the same conclusion as you have…

https://elib.uni-stuttgart.de/bitstream/11682/15133/1/Sreelakshmi-Thesis%20Report.pdf

Here are some excerpts:

 

[Fullmoonfever]

Hi Fullmoonfever,

that’s the same Master’s thesis I had alluded to in a previous post of mine I had not yet followed up on:



However, it was already completed in August 2024, so I did not come to the same conclusion as you have…

https://elib.uni-stuttgart.de/bitstream/11682/15133/1/Sreelakshmi-Thesis%20Report.pdf

Here are some excerpts:



View attachment 74307
View attachment 74308
View attachment 74311
View attachment 74312


View attachment 74313

Interestingly, she says Akida had limitations with complex temporal tasks....was she using Akida 1 or TENNS is the question for mine.

Would like to suspect it was V1 and that TENNS would reduce some of the said limitations.

Curious to see what the research cooperation with Waterloo brings and whether they move closer to someone like ABR or if they are utilising Waterloo's skill sets to assist further with something like Akida.

 

[Frangipani]

Interestingly, she says Akida had limitations with complex temporal tasks....was she using Akida 1 or TENNS is the question for mine.

Would like to suspect it was V1 and that TENNS would reduce some of the said limitations.

There is neither mention of Akida 2.0 nor TENNs in this Master’s thesis, even though the author’s research was conducted in the first half of 2024 (she would have required a few weeks prior to submission for the actual write-up).

To me this was yet another indication that the Mercedes-Benz neuromorphic researchers have not been charging ahead with Akida 2.0 / TENNs behind the scenes as much as some fellow posters will try to make you believe - or in the worst case, have not even started to do any research on Akida’s second generation at all…

Here are some more screenshots I took when I first chanced upon this Master’s thesis in October:

 

[Tothemoon24]

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

Gothenburg, Sweden (16 December 2024) – 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.
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
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.
# # #

 

[MDhere]

Hi MDhere,

What do you know d Dr Jerry A. Smith?

While they say that no publicity is bad publicity, I'm not sure I understand his assertion that Akida uses RISC-V.

RISC-V is software, and Akida does not use software.

The links to his Linkedin and other links use such termd and buzzwords as "agentic", "heuristic", "quantum entanglement", "free energy principle (there's a law of thermodynamics about this)", so they are rabit holes I keep a good 40 foot pole's length away.

The titles of some of his recorded talks does little to allay my doubts:

https://soundcloud.com/drjerryasmith

Not so much the far edge as the far side.

Hi Diogenese,
The article moreover talks about Tenstorrent and Brainchip (hardware) enhancing Risc-v (software) -
Notable Hardware Implementations Using RISC-V
RISC-V’s versatility is demonstrated through its adoption by companies such as Tenstorrent and BrainChip. Tenstorrent leverages RISC-V in high-performance GPUs for training and inference of large neural networks, providing an adaptable platform for machine learning workloads. Meanwhile, BrainChip’s Akida neuromorphic processor uses RISC-V to perform event-driven neural computation inspired by the human brain, emphasizing energy efficiency and real-time responsiveness for edge applications. These implementations illustrate how RISC-V enables innovative hardware solutions across traditional and next-generation AI workloads.
All in all I made reference to this article as Frontgrade Gaisler deals with Risc-V and is licensing Akida and Tenstorrent recently had a large $$ injection of funds by JB,that the podcast which Brainchip and Tenstorrent did some time back makes it a little more interesting as well as the connection in the article. Gotta love synergies. But what would I know.., I am just a simple gal trying to make my way through the maze

 

[goodvibes]

Here is the answere for using Akida 1 & 2 by frontgrade gaisler

 

[Frangipani]

Curious to see what the research cooperation with Waterloo brings and whether they move closer to someone like ABR or if they are utilising Waterloo's skill sets to assist further with something like Akida.

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

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

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University of Waterloo & BC

Shared expertise:
Our CTO, Dr. M. Anthony (Tony) Lewis, has served as a visiting or adjunct professor at the University of Waterloo, among other institutions. This suggests a potential for knowledge exchange between BrainChip and the university, although it doesn't indicate a formal collaboration.

Research on hardware for artificial intelligence:
Both BrainChip and researchers at the University of Waterloo (Chris Eliasmith and Terry Stewart) have been exploring hardware architectures needed for implementing sophisticated machine intelligence (see pic below)


View attachment 72842

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”.

Aftab Patla biography | Kinesiology and Health Sciences | University of Waterloo

Aftab Patla's biography.

uwaterloo.ca

 

[Frangipani]

Embedded World 2025 March 11-13

Embedded World 2025 March 11-13 Join BrainChip at Embedded World 2025. BrainChip is excited to participate at Embedded World 2025, taking place from March 11-13 in Nuremberg, Germany. As the premier global event for the embedded systems community, Embedded World brings together leading experts...

brainchip.com

 

[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

Teilen
0 Kommentare

"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!