jtardif999
Regular
Yeah, isn’t SiFives RISKV architecture being used in NASAs space computer - would think it could not be open source for NASAs use.
BRN Discussion Ongoing
- Thread starter TechGirl
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Boab
I wish I could paint like Vincent
Don't be too disheartened as the original manuscript is now almost 12 months old and the latest reference they used was May 2021 with most other references being years earlier.
BRN has come a long way since then and my understanding is Loihi is still being developed.
mrgds
Regular
"Coulda, Woulda, Shoulda, Skutza. .....................
Fullmoonfever
Top 20
Yeah. If you watch the SiFive vid I posted below he discusses what parts of RiscV is open source and which parts of SiFive are not. I found it interesting myself.
BRN Discussion Ongoing
An interesting development as U.S. lawmakers are pushing to limit American corporate engagement with open-source chip technology RISC-V, alleging that it aids Beijing’s semiconductor goals and could potentially compromise US national security. Good news for Arm 💪 but bad news for Qualcomm I...
thestockexchange.com.au
Hiya Perhaps,
I believe Fullmoonfever’s memory does serve him excellently.
The Co can request the nominees a/c details such as Citicorp‘s Nominee A/c and as I understand, they have done this in the past, and would expect, if they so feel the need. Will do so in the future.
Just a friendly heads up.
Cheers
Edit. Woops. Sorry Perhaps. Didn’t realise Fullmoonfever had directly responded to your post.
Oh well maybe Just a FYI for others
Last edited:
robsmark
Regular
Agree Xray1...
Something of magnitude would have to be happening (Happened!) to issue 15 Million shares to divvy up as a...'Well done team for your fantastic efforts and managing to get over these huge hurdles that were presented to you all' ?
Here's hoping something big is about to drop!!
I’m guessing this relates to the release of AKD2000.
Hey, it'll just have to be a few years later than I thought"Coulda, Woulda, Shoulda, Skutza. .....................
Pom down under
Top 20
Well I suppose that's because all the blood has rushed to your feet.
Pom down under
Top 20
Tothemoon24
Top 20
BrainChip Unveils Second-Generation Akida Platform for Edge AI Advancements
ByNiharika Singh
-
October 8, 2023
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In an era marked by an insatiable appetite for artificial intelligence (AI) capabilities, BrainChip, a pioneer in neural network processors, has taken a significant stride towards empowering edge devices with unprecedented processing power. The company’s latest unveiling, the second-generation Akida platform, represents a groundbreaking leap in the realm of Edge AI, delivering the potential to liberate devices from cloud dependency.
The initial glimpse of BrainChip’s original Akida neuromorphic processing technology at the Linley Fall Processor Conference in 2019 paved the way for a journey that materialized in the form of development kits for the general public in 2021. In March 2023, there was an announcement of Akida 2.0, a refinement promising support for Temporal Event-Based Neural Network (TENN) acceleration and optional vision transformer hardware. This enhancement not only amplifies the platform’s capabilities but also lightens the computational load on the host processor. BrainChip classified Akida 2.0 into three distinct product classes: Akida-E, prioritizing energy efficiency; Akida-S, designed for seamless integration into microcontroller units and systems-on-chips; and Akida-P, a high-performance range supplemented by optional vision transformer acceleration.
We are also on WhatsApp. Join our AI Channel on Whatsapp.. Now, BrainChip has initiated an “early access” program, granting access to the Akida 2.0 intellectual property (IP) and promising an “order of magnitude” improvement in compute density through TENNs support. This transformative leap is a testament to the inevitable shift towards Multimodal Edge AI, a trend intensifying the demands on intelligent computing at the Edge. Researchers laud this development, emphasizing that BrainChip’s second-generation Akida aligns precisely with the critical requisites of performance, efficiency, accuracy, and reliability necessary to expedite this transition.
Central to the Akida 2.0 platform are the TENNs, offering a staggering “order of magnitude” reduction in model size and computational requirements. This leap in efficiency augurs well for the acceleration of AI adoption and holds the promise of rendering Edge AI solutions more accessible and easy to deploy.
Join Our ML Subreddit of 30,000+ members As BrainChip opens the gateway to the Akida 2.0 IP, eager innovators and tech enthusiasts are encouraged to reach out to the company’s sales department for further details. While pricing remains undisclosed at this juncture, the launch timeline for hardware development kits based on the second-generation platform is yet to be confirmed.
In conclusion, BrainChip’s introduction of the second-generation Akida platform is poised to redefine the landscape of Edge AI. With TENNs at its core, this innovation addresses the pressing need for enhanced performance, efficiency, and reliability in Edge computing.
Fullmoonfever
Top 20
Hmmmm....wonder if legit cybersecurity and if so, whose neuromorphic they using
Neuromorphic Computing
Deep Convolutional Neural Networks (CNNs) boosted the artificial intelligence revolution, especially after 2015. Although CNNs provide impressive performance for classification and relational reasoning on data patterns, they also require application-oriented structural optimization.This motivates the developers and researchers to work on morphologically adaptive CNNs where the network topology is evolved as processed data and experience of the system increase. On the other hand, this also increases the level of time and space complexity. In other words, GPU/CPU processing power and memory requirement exponentially raise.
Neuromorphic computing intends to provide novel solutions for efficient utilization of hardware resources against increasing complexity for implementation of morphologically adaptive machine learning systems. For this reason, neuromorphic computing has become a forthcoming milestone as the next generation of AI after the development of deep convolutional networks. An important target of the neuromorphic systems is high-level cognitive functions that mimic human intelligence and provides situational awareness. In order to reduce power consumption with efficient information coding, one way of neuromorphic computing implementation is using dedicated hardware that depends on parallelism instead of sequential logical processing solutions.
Computation based on conventional digital computer architectures and materials is approaching to physical limitations. Due to the development of AI applications and their rising economic impact, nature-inspired emulation of cognitive functions has become a major target within new computational paradigms. Neuromorphic computing, also known as, Neuromorphic engineering is a concept describing the use of integrated systems containing morphologically adaptive analog, analog & digital hybrid circuits or equivalent circuit simulations to mimic neuro-biological architectures present in the nervous system.
Situational awareness and context awareness are becoming key factors in cybersecurity because of exponentially increasing amount of threats both in terms of variety and their complexity. Monitoring, diagnostics, defense, and recovery requires a high level of cognition in order to sustain security in cyberspace.
For this reason, CRYPTTECH AI team works on the development of high level of cognition depending on situational awareness on morphologically adaptive platforms for cybersecurity. We work on state of the art implementation of morphologically adaptive data coding and machine learning solutions on conventional computational systems as well as neuromorphic computing with dedicated hardware for high-performance cybersecurity systems.
However, determination of the best strategies to identify the threats and their content variability for different situations are still carried out with intensive cyber security expertise. As artificial intelligence technology advances, the possibility of computers to provide autonomous services including intensive cognitive functions increases.
CYBERDROIDs have emerged as an important tool in spite of increasing diverse threat and malware with high cognitive functions. In addition to mobile devices, we are in a period of widespread Internet of Things (IoT) applications. The number of devices connected to the Internet has exceeded 20 billion in the world and continues to increase rapidly. Research has shown that the growing need is actually higher than predicted and this leads to a number of undiagnosed problems, the effects of information security to system operating defects can be partially comprehensible at further stages. The use of CYBERDROIDs for cyber security is a strategic move in meeting the evolving need of human-like cognitive functions. CRYPTTECH is the first cyber security company in the world that demonstrates the use of
CYBERDROID with humanoid cognitive functions. The use of CYBERDROID in the future cyber defense systems is considered to be inevitable.
Unlike traditional methods of machine learning, CYBERDROIDs have four main features that bring them closer to humanoid behavior and abilities. There are cortical networks between their sensor and perception just like human beings. These networks provide efficient coding of data-to-information conversion and inferring their differentiating properties by coding based on neuromorphic calculation as in humans.
Another important feature is the state awareness by fusion to the coded information passing through different sensor cortices. This is a very important stage in the acquisition of humanoid behavior skills into machines. Sequential coding of the sensor cortices with contextual cortical networks provides state awareness.
CYBERDROIDs can be adapted to fixed network security devices in a discrete box structure in the future or can be used in mobile critical infrastructure such as transportation systems, autonomous vehicles. They will also provide high energy efficiency in cyber security with the development of neuromorphic computing. The first examples of neuromorphic processors have been successfully implemented by DARPA, which established the first internet network, in target tracking application in combat aircraft. Machine learning, especially developed with artificial neural networks, gained momentum with convolutional neural networks after 2010 and increased the commercialization rate after 2015. In this development process,
CYBERDROIDs have a significant advantage especially in cyber security and cyber defense by its ability to making decisions to inferences with context awareness. CYBERDROIDs will continue to increase their superiority in services & applications in the road map of artificial intelligence on low power consumption structures parallel to neuromorphism.
Neuromorphic Computing
Deep Convolutional Neural Networks (CNNs) boosted the artificial intelligence revolution, especially after 2015. Although CNNs provide impressive performance for classification and relational reasoning on data patterns, they also require application-oriented structural optimization.This motivates the developers and researchers to work on morphologically adaptive CNNs where the network topology is evolved as processed data and experience of the system increase. On the other hand, this also increases the level of time and space complexity. In other words, GPU/CPU processing power and memory requirement exponentially raise.
Neuromorphic computing intends to provide novel solutions for efficient utilization of hardware resources against increasing complexity for implementation of morphologically adaptive machine learning systems. For this reason, neuromorphic computing has become a forthcoming milestone as the next generation of AI after the development of deep convolutional networks. An important target of the neuromorphic systems is high-level cognitive functions that mimic human intelligence and provides situational awareness. In order to reduce power consumption with efficient information coding, one way of neuromorphic computing implementation is using dedicated hardware that depends on parallelism instead of sequential logical processing solutions.
Computation based on conventional digital computer architectures and materials is approaching to physical limitations. Due to the development of AI applications and their rising economic impact, nature-inspired emulation of cognitive functions has become a major target within new computational paradigms. Neuromorphic computing, also known as, Neuromorphic engineering is a concept describing the use of integrated systems containing morphologically adaptive analog, analog & digital hybrid circuits or equivalent circuit simulations to mimic neuro-biological architectures present in the nervous system.
Situational awareness and context awareness are becoming key factors in cybersecurity because of exponentially increasing amount of threats both in terms of variety and their complexity. Monitoring, diagnostics, defense, and recovery requires a high level of cognition in order to sustain security in cyberspace.
For this reason, CRYPTTECH AI team works on the development of high level of cognition depending on situational awareness on morphologically adaptive platforms for cybersecurity. We work on state of the art implementation of morphologically adaptive data coding and machine learning solutions on conventional computational systems as well as neuromorphic computing with dedicated hardware for high-performance cybersecurity systems.
CYBERDROID
Today, the diversity of malware and threats exponentially increases. The increase in malware and threat types is estimated to exceed 8 million annually. CYBERDROIDs have significant operational potentials, especially in the maintenance of cyber security and information systems. In cyber security infrastructures against threats and malware, the development process started from the installation of devices and security software at different levels on the network to the establishment of the security operations center (SOC).However, determination of the best strategies to identify the threats and their content variability for different situations are still carried out with intensive cyber security expertise. As artificial intelligence technology advances, the possibility of computers to provide autonomous services including intensive cognitive functions increases.
CYBERDROIDs have emerged as an important tool in spite of increasing diverse threat and malware with high cognitive functions. In addition to mobile devices, we are in a period of widespread Internet of Things (IoT) applications. The number of devices connected to the Internet has exceeded 20 billion in the world and continues to increase rapidly. Research has shown that the growing need is actually higher than predicted and this leads to a number of undiagnosed problems, the effects of information security to system operating defects can be partially comprehensible at further stages. The use of CYBERDROIDs for cyber security is a strategic move in meeting the evolving need of human-like cognitive functions. CRYPTTECH is the first cyber security company in the world that demonstrates the use of
CYBERDROID with humanoid cognitive functions. The use of CYBERDROID in the future cyber defense systems is considered to be inevitable.
Unlike traditional methods of machine learning, CYBERDROIDs have four main features that bring them closer to humanoid behavior and abilities. There are cortical networks between their sensor and perception just like human beings. These networks provide efficient coding of data-to-information conversion and inferring their differentiating properties by coding based on neuromorphic calculation as in humans.
Another important feature is the state awareness by fusion to the coded information passing through different sensor cortices. This is a very important stage in the acquisition of humanoid behavior skills into machines. Sequential coding of the sensor cortices with contextual cortical networks provides state awareness.
CYBERDROIDs can be adapted to fixed network security devices in a discrete box structure in the future or can be used in mobile critical infrastructure such as transportation systems, autonomous vehicles. They will also provide high energy efficiency in cyber security with the development of neuromorphic computing. The first examples of neuromorphic processors have been successfully implemented by DARPA, which established the first internet network, in target tracking application in combat aircraft. Machine learning, especially developed with artificial neural networks, gained momentum with convolutional neural networks after 2010 and increased the commercialization rate after 2015. In this development process,
CYBERDROIDs have a significant advantage especially in cyber security and cyber defense by its ability to making decisions to inferences with context awareness. CYBERDROIDs will continue to increase their superiority in services & applications in the road map of artificial intelligence on low power consumption structures parallel to neuromorphism.
CYBER DROID
www.cyberdroid.com
Humble Genius
Regular
Could be related to a sales target?
robsmark
Regular
Continual disclosure says otherwise
Boab
I wish I could paint like Vincent
Humble Genius
Regular
What, so hypothetically if Megachips sold/used 15 million AKIDA IP units, Would that need to be disclosed?Continual disclosure says otherwise
Tothemoon24
Top 20
Most likely been posted from May this year ;
Thales /AstrositeTM Dot. Dot . Dot .
Currently, Thales is working with Western Sydney University (WSU) to deliver an entirely sovereign sensor solution, the AstrositeTM. WSU developed the core intellectual property associated with the use of event-based sensing technology for Thales’s Space Domain Awareness (SDA) sensor capability. Astrosite uses neuromorphic vision sensors that mimic the way that humans detect and process visual input. They outperform existing optical sensor technology and have the potential to see what other sensors cannot. Testing reveals numerous technological advantages over conventional optical sensors, including:
www.thalesgroup.com
Thales /AstrositeTM Dot. Dot . Dot .
Currently, Thales is working with Western Sydney University (WSU) to deliver an entirely sovereign sensor solution, the AstrositeTM. WSU developed the core intellectual property associated with the use of event-based sensing technology for Thales’s Space Domain Awareness (SDA) sensor capability. Astrosite uses neuromorphic vision sensors that mimic the way that humans detect and process visual input. They outperform existing optical sensor technology and have the potential to see what other sensors cannot. Testing reveals numerous technological advantages over conventional optical sensors, including:
The future of Space capability in Australia is an international effort
As a global organisation, Thales understands that it has a responsibility to support the creation of a mutually beneficial ecosystem made up of Australian SMEs and academic research institutions.
Humble Genius
Regular
Casey Jones on LinkedIn: BrainChip Unveils Second-Generation Akida Platform for Edge AI Advancements
Greetings AI enthusiasts 🚀🧠, The groundbreaking #EdgeAI technology continues to redefine the future of advanced computing! BrainChip, known for its…
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