BRN Discussion Ongoing
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- Start date
Yep! They've realized that to satisfy their avarice they have raked it all in and the global economy is on the verge of collapse, so to preserve their wealth they are prepared to do a little penance and pay a bit of tax so the proles can keep their noses to the grindstone.
[Thinks - "Now where did I put my lamp?"]
Quatrojos
Regular
Tothemoon24
Top 20
cosors
👀
Let everyone make up his own mind.
I post this opinion actually only because of the funny remarks below. Either we are in the WRONG forum here and we should switch to high quality discussions in the new generation forum for BrainChip's stock. Or else Simon hasn't discovered tse yet and should join us. ) I find some of his assessments to be.... ... ...
Just my opinion...
"BrainChip succeeds in coup with industry giant
Simon / 05.23.22 / 12:43 pm
Shares in Australian startup BrainChip (WKN: A14Z7W) shot up +15% after trading began in Australia on Monday. Late Sunday, the AI specialist had reported its inclusion in the partner program of an absolute industry giant. Is the Australian AI gem's breakthrough imminent?
BrainChip Holding is an Australian technology company with solutions in the field of artificial intelligence and machine learning (AI & ML). The chip developer's flagship project is a so-called neuromorphic processor called Akida. It is supposed to be very close to the way the brain works and thus, in particular, very energy-efficient. The tech stock is already worth over US$1.4 billion on the stock market.
Inclusion in ARM's partner program
BrainChip shares shot up +15% on the Australian Stock Exchange Monday morning, eventually exiting trading up 8.55% at AU$1.27.
What put investors of the tech stock in such a buying mood was, to all appearances, a company announcement from late Sunday. According to it, the Australians were accepted into the AI Partner Program of ARM, one of the biggest names in chip sector. The British manufacturer's blueprints are the world's dominant standard for smartphones, tablets and mobile IoT devices.
ARM is considered a sort of "neutral Switzerland" due to its status in the semiconductor industry. Earlier this year, tech giant Nvidia attempted to acquire the company for US$40 billion. However, the deal ultimately fell through due to regulatory concerns raised by the relevant competition watchdogs.
The British company's partner program is an ecosystem of hardware and software specialists designed to enable developers to build the next generation of AI solutions, according to the statement.
It reportedly helps members form strategic alliances and provides them with technical support and resources to reach partners, developers and decision makers in their target markets.
Mohamed Awad, vice president of IoT and embedded at ARM, said:
"As part of ARM's AI Partner Program, BrainChip will enable developers to address the need for high-performance and ultra-low-power edge AI inference, enabling new innovation opportunities."
Partner network grows
BrainChip has scored another strong coup by being accepted into the AI Partner Program of market giant ARM. In all likelihood, this will enable the chip manufacturer to land further partnerships to expand the commercial reach of its Akida processors.
In Europe, it already has distribution alliances with Easttronics and SalesLink. A month ago, it added an exciting collaboration with Swiss AI firm NVISO, which specializes in human behavior analysis. Heavyweights such as Mercedes and the US Air Force have also already announced cooperation with the Australians.
Breakthrough still unlikely at present
However, in our view it is probably still a bit too early for a substantial investment in BrainChip. Experience shows that the long-term chances of success for start-ups in the chip segment are extremely low. This insight has apparently also recently become widespread again among investors: After the Australians obtained an important patent in January and the share exploded by +200% to AU$2.20, the price promptly halved again.
And I thought that was because of Mercedes and patent was the cherry...
ARM's partner program will undoubtedly increase BrainChip's visibility in the industry, but the company is far from the only edge AI specialist in the ecosystem. In addition to an unlikely breakthrough, however, risk-averse investors can bet on an acquisition by a chip giant such as Intel or Nvidia - though they would prefer to do so only with a very small portfolio stake.
=>BrainChip: Discuss now!<=
High-quality discussions and real information advantages: Benefit just like thousands of other investors from our unique Live Chat, the new generation forum for BrainChip stock.
Not a member yet? Here you can register for free!"
https://www.sharedeals.de/brainchip-gelingt-coup-mit-branchengroesse/#gref
Come on, they need insight from you and it's free! Give yourselves a jolt and register now.
I post this opinion actually only because of the funny remarks below. Either we are in the WRONG forum here and we should switch to high quality discussions in the new generation forum for BrainChip's stock. Or else Simon hasn't discovered tse yet and should join us. ) I find some of his assessments to be.... ... ...
Just my opinion...
"BrainChip succeeds in coup with industry giant
Simon / 05.23.22 / 12:43 pm
Shares in Australian startup BrainChip (WKN: A14Z7W) shot up +15% after trading began in Australia on Monday. Late Sunday, the AI specialist had reported its inclusion in the partner program of an absolute industry giant. Is the Australian AI gem's breakthrough imminent?
BrainChip Holding is an Australian technology company with solutions in the field of artificial intelligence and machine learning (AI & ML). The chip developer's flagship project is a so-called neuromorphic processor called Akida. It is supposed to be very close to the way the brain works and thus, in particular, very energy-efficient. The tech stock is already worth over US$1.4 billion on the stock market.
Inclusion in ARM's partner program
BrainChip shares shot up +15% on the Australian Stock Exchange Monday morning, eventually exiting trading up 8.55% at AU$1.27.
What put investors of the tech stock in such a buying mood was, to all appearances, a company announcement from late Sunday. According to it, the Australians were accepted into the AI Partner Program of ARM, one of the biggest names in chip sector. The British manufacturer's blueprints are the world's dominant standard for smartphones, tablets and mobile IoT devices.
ARM is considered a sort of "neutral Switzerland" due to its status in the semiconductor industry. Earlier this year, tech giant Nvidia attempted to acquire the company for US$40 billion. However, the deal ultimately fell through due to regulatory concerns raised by the relevant competition watchdogs.
The British company's partner program is an ecosystem of hardware and software specialists designed to enable developers to build the next generation of AI solutions, according to the statement.
It reportedly helps members form strategic alliances and provides them with technical support and resources to reach partners, developers and decision makers in their target markets.
Mohamed Awad, vice president of IoT and embedded at ARM, said:
"As part of ARM's AI Partner Program, BrainChip will enable developers to address the need for high-performance and ultra-low-power edge AI inference, enabling new innovation opportunities."
Partner network grows
BrainChip has scored another strong coup by being accepted into the AI Partner Program of market giant ARM. In all likelihood, this will enable the chip manufacturer to land further partnerships to expand the commercial reach of its Akida processors.
In Europe, it already has distribution alliances with Easttronics and SalesLink. A month ago, it added an exciting collaboration with Swiss AI firm NVISO, which specializes in human behavior analysis. Heavyweights such as Mercedes and the US Air Force have also already announced cooperation with the Australians.
Breakthrough still unlikely at present
However, in our view it is probably still a bit too early for a substantial investment in BrainChip. Experience shows that the long-term chances of success for start-ups in the chip segment are extremely low. This insight has apparently also recently become widespread again among investors: After the Australians obtained an important patent in January and the share exploded by +200% to AU$2.20, the price promptly halved again.
And I thought that was because of Mercedes and patent was the cherry...
ARM's partner program will undoubtedly increase BrainChip's visibility in the industry, but the company is far from the only edge AI specialist in the ecosystem. In addition to an unlikely breakthrough, however, risk-averse investors can bet on an acquisition by a chip giant such as Intel or Nvidia - though they would prefer to do so only with a very small portfolio stake.
=>BrainChip: Discuss now!<=
High-quality discussions and real information advantages: Benefit just like thousands of other investors from our unique Live Chat, the new generation forum for BrainChip stock.
Not a member yet? Here you can register for free!"
https://www.sharedeals.de/brainchip-gelingt-coup-mit-branchengroesse/#gref
Come on, they need insight from you and it's free! Give yourselves a jolt and register now.
Last edited:
Zedjack33
Regular
Fact Finder
Top 20
Worth a second read:
What’s So Exciting About Neuromorphic Computing
By Aaryaa PadhyegurjarMay 18, 2022
41
Telegram
https://www.electronicsforu.com/technology-trends/exciting-neuromorphic-computing/amp#
The human brain is the most efficient and powerful computer that exists. Even after decades and decades of technological advancements, no computer has managed to beat the brain with respect to efficiency, power consumption, and many other factors.
Will neuromorphic computers be able to do it?
The exact sequence of events that take place when we do a particular activity on our computer, or on any other device, completely depends on its inherent architecture. It depends on how the various components of the computer like the processor and memory are structured in the solid state.
Fast forward to today
Nowadays, almost all companies have dedicated teams working on neuromorphic computing. Groundbreaking research is being done in multiple research organisations and universities. It is safe to say that neuromorphic computing is gaining momentum and will continue to do so as various advancements are being made.
What’s interesting to note is that although this is a specialised field with prerequisites from various topics, including solid-state physics, VLSI, neural networks, and computational neurobiology, undergraduate engineering students are extremely curious about this field.
At IIT Kanpur, Dr Shubham Sahay, Assistant Professor at the Department of Electrical Engineering, introduced a course on neuromorphic computing last year. Despite being a post-graduate level course, he saw great participation from undergrads as well. “Throughout the course, they were very interactive. The huge B.Tech participation in my course bears testimony to the fact that undergrads are really interested in this topic. I believe that this (neuromorphic computing) could be introduced as one of the core courses in the UG curriculum in the future,” he says.
Getting it commercial
Until recently, neuromorphic computing was a widely used term only in research and not in the commercial arena. However, as of January 18, 2022, BrainChip, a leading provider of ultra-low-power high-performance AI technology, commercialised its AKD1000 AIOT chip. Developers, system integrators, and engineers can now buy AKD1000-powered Mini PCIe boards and leverage them in their applications, especially those requiring on-edge computing, low power consumption, and high-performance AI.
“It’s meant as our entry-level product. We want to proliferate this into as many hands as we can and get people designing in the Akida environment,” says Rob Telson, Vice President of WorldWide Sales at BrainChip. Anil Mankar, Co-founder and Chief Development Officer of BrainChip, explains, “We are enabling system integrators to easily use neuromorphic AI in their applications. In India, if some system integrators want to manufacture the board locally, they can take the bill of materials from us (BrainChip) and manufacture it locally.”
What’s fascinating about Akida is that it enables sensor nodes to compute without depending on the cloud. Further, BrainChip’s AI technology not only performs audio and video based learning but even focuses on other sensor modalities like taste, vibration, and smell. You can use it to make a sensor that performs wine tasting! Here is a link to their wine tasting demonstration: Link
Another major event that occurred this year was when Mercedes implemented BrainChip’s Akida technology in its Vision EQXX electric vehicle. This is definitely a big deal since the Akida technology is tried and tested for a smart automotive experience. All features that the Akida provides, including facial recognition, keyword spotting, etc consume extremely low power.
“This is where we get excited. You’ll see a lot of these functionalities in vehicles—recognition of voices, faces, and individuals in the vehicle. This allows the vehicles to have customisation and device personalisation according to the drivers or the passengers as well,” says Telson. These really are exciting times.
Neuromorphic hardware, neural networks, and AI
The process in which neurons work is eerily similar to an electric process. Neurons communicate with each other via synapses. Whenever they receive input, they produce electrical signals called spikes (also called action potentials), and the event is called neuron spiking. When this happens, chemicals called neurotransmitters are released into hundreds of synapses and activate the respective neurons. That’s the reason why this process is super-fast.Artificial neural networks mimic the logic of the human brain, but on a regular computer. The thing is, regular computers work on the Von Neumann architecture, which is extremely different from the architecture of our brain and is very power-hungry. We may not be able to deploy CMOS logic on the Von Neumann architecture for long. We will eventually reach a threshold to which we can exploit silicon. We are nearing the end of Moore’s Law and there is a need to establish a better computing mechanism. Neuromorphic computing is the solution because neuromorphic hardware realises the structure of the brain in the solid-state.
As we make progress in neuromorphic hardware, we will be able to deploy neural networks on it. Spiking Neural Network (SNN) is a type of artificial neural network that uses time in its model. It transmits information only when triggered—or, in other words, spiked. SNNs used along with neuromorphic chips will transform the way we compute, which is why they are so important for AI.
How to get started with SNNs
Since the entire architecture of neuromorphic AI chips is different, it is only natural to expect the corresponding software framework to be different too. Developers need to be educated on working with SNNs. However, that is not the case with MetaTF, a free software development framework environment that BrainChip launched in April 2021.“We want to make our environment extremely simple to use. Having people learn a new development environment is not an efficient way to move forward,” says Telson. “We had over 4600 unique users start looking at and playing with MetaTF in 2021. There’s a community out there that wants to learn.”
India and the future of neuromorphic computing
When asked about the scope of neuromorphic computing in India, Dr Sahay mentions, “As of now, the knowledge, dissemination, and expertise in this area is limited to the eminent institutes such as IITs and IISc, but with government initiatives such as India Semiconductor Mission (ISM) and NITI Ayog’s national strategy for artificial intelligence (#AIforall), this field would get a major boost. Also, with respect to opportunities in the industry, several MNCs have memory divisions in India—Micron, Sandisk (WesternDigital), etc—that develop the memory elements which will be used for neuromorphic computing.” There’s a long way to go, but there is absolutely no lack of potential. More companies would eventually have their neuromorphic teams in India.
The author, Aaryaa Padhyegurjar, is an Industry 4.0 enthusiast with a keen interest in innovation and research
Bravo
If ARM was an arm, BRN would be its biceps💪!
Now we are friends with SiFive, and SiFive is hooked up with Intel Foundry Services,Let everyone make up his own mind.
I post this opinion actually only because of the funny remarks below. Either we are in the WRONG forum here and we should switch to high quality discussions in the new generation forum for BrainChip's stock. Or else Simon hasn't discovered tse yet and should join us. ) I find some of his assessments to be.... ... ...
Just my opinion...
"BrainChip succeeds in coup with industry giant
Simon / 05.23.22 / 12:43 pm
Shares in Australian startup BrainChip (WKN: A14Z7W) shot up +15% after trading began in Australia on Monday. Late Sunday, the AI specialist had reported its inclusion in the partner program of an absolute industry giant. Is the Australian AI gem's breakthrough imminent?
BrainChip Holding is an Australian technology company with solutions in the field of artificial intelligence and machine learning (AI & ML). The chip developer's flagship project is a so-called neuromorphic processor called Akida. It is supposed to be very close to the way the brain works and thus, in particular, very energy-efficient. The tech stock is already worth over US$1.4 billion on the stock market.
Inclusion in ARM's partner program
BrainChip shares shot up +15% on the Australian Stock Exchange Monday morning, eventually exiting trading up 8.55% at AU$1.27.
What put investors of the tech stock in such a buying mood was, to all appearances, a company announcement from late Sunday. According to it, the Australians were accepted into the AI Partner Program of ARM, one of the biggest names in chip sector. The British manufacturer's blueprints are the world's dominant standard for smartphones, tablets and mobile IoT devices.
ARM is considered a sort of "neutral Switzerland" due to its status in the semiconductor industry. Earlier this year, tech giant Nvidia attempted to acquire the company for US$40 billion. However, the deal ultimately fell through due to regulatory concerns raised by the relevant competition watchdogs.
The British company's partner program is an ecosystem of hardware and software specialists designed to enable developers to build the next generation of AI solutions, according to the statement.
It reportedly helps members form strategic alliances and provides them with technical support and resources to reach partners, developers and decision makers in their target markets.
Mohamed Awad, vice president of IoT and embedded at ARM, said:
"As part of ARM's AI Partner Program, BrainChip will enable developers to address the need for high-performance and ultra-low-power edge AI inference, enabling new innovation opportunities."
Partner network grows
BrainChip has scored another strong coup by being accepted into the AI Partner Program of market giant ARM. In all likelihood, this will enable the chip manufacturer to land further partnerships to expand the commercial reach of its Akida processors.
In Europe, it already has distribution alliances with Easttronics and SalesLink. A month ago, it added an exciting collaboration with Swiss AI firm NVISO, which specializes in human behavior analysis. Heavyweights such as Mercedes and the US Air Force have also already announced cooperation with the Australians.
Breakthrough still unlikely at present
However, in our view it is probably still a bit too early for a substantial investment in BrainChip. Experience shows that the long-term chances of success for start-ups in the chip segment are extremely low. This insight has apparently also recently become widespread again among investors: After the Australians obtained an important patent in January and the share exploded by +200% to AU$2.20, the price promptly halved again.
And I thought that was because of Mercedes...
ARM's partner program will undoubtedly increase BrainChip's visibility in the industry, but the company is far from the only edge AI specialist in the ecosystem. In addition to an unlikely breakthrough, however, risk-averse investors can bet on an acquisition by a chip giant such as Intel or Nvidia - though they would prefer to do so only with a very small portfolio stake.
=>BrainChip: Discuss now!<=
High-quality discussions and real information advantages: Benefit just like thousands of other investors from our unique Live Chat, the new generation forum for BrainChip stock.
Not a member yet? Here you can register for free!"
https://www.sharedeals.de/brainchip-gelingt-coup-mit-branchengroesse/#gref
Come on, they need insight from you and it's free! Give yourselves a jolt and register now.
We are also friends with Nvidia,
and now we are friends with ARM, so ...
if one of the big persons were to try a take-over of BRN, could that spark a bidding war?
And where would the SP be after that?
And could it sustain that price?
Bravo
If ARM was an arm, BRN would be its biceps💪!
Sorry everyone, this was a reaction against other slightly, sorta-sexist posts - just trying to keep the equilibrium. Love youze all! B x
Evermont
Stealth Mode
Interesting couple of posts on the Yahoo conversation board. The first article posted also provides a great illustration expanding on the chiplets topic touched on by FF and others over the weekend.
https://finance.yahoo.com/quote/BRCHF/community?p=BRCHF
www.fierceelectronics.com
https://finance.yahoo.com/quote/BRCHF/community?p=BRCHF
Tech giants Intel, Meta, Arm, Google Cloud, AMD, Qualcomm, TSMC and ASE form chiplet consortium
| Open UCIe standard defines how chiplets are integrated in system-on-chip design to benefit fabs and designers
JoMo68
Regular
LDN really was a legend…
... and let's not forget CSL's market cap - $132B, which, in BRN's case would be about $80 per share (which, IMO and considering the comparative market and earnings potentials, is a fraction of what BRN could be worth), so I can't see PvdM and Co selling anytime soon.
So India has a government sponsored program to boost AI SNN/ML, and has a couple of Unis with standing room only lectures, while Australia has a couple of PhD students lucky enough to work at Brainchip's research labs.
Worth a second read:
What’s So Exciting About Neuromorphic Computing
By Aaryaa Padhyegurjar
May 18, 2022
41
Telegram
https://www.electronicsforu.com/technology-trends/exciting-neuromorphic-computing/amp#
The human brain is the most efficient and powerful computer that exists. Even after decades and decades of technological advancements, no computer has managed to beat the brain with respect to efficiency, power consumption, and many other factors.
Will neuromorphic computers be able to do it?
The exact sequence of events that take place when we do a particular activity on our computer, or on any other device, completely depends on its inherent architecture. It depends on how the various components of the computer like the processor and memory are structured in the solid state.
Almost all modern computers we use today are based on the Von Neumann architecture, a design first introduced in the late 1940s. There, the processor is responsible for executing instructions and programs, while the memory stores those instructions and programs. When you think of your body as an embedded device, your brain is the processor as well as the memory. The architecture of our brain is such that there is no distinction between the two.
Since we know for a fact that the human brain is superior to every single computer that exists, doesn’t it make sense to modify computer architecture in a way that it functions more like our brain? This was what many scientists realised in the 1980s, starting with Carver Mead, an American scientist and engineer.
Fast forward to today
Nowadays, almost all companies have dedicated teams working on neuromorphic computing. Groundbreaking research is being done in multiple research organisations and universities. It is safe to say that neuromorphic computing is gaining momentum and will continue to do so as various advancements are being made.
The 5 sensor modalities (Source: BrainChip Inc.)
What’s interesting to note is that although this is a specialised field with prerequisites from various topics, including solid-state physics, VLSI, neural networks, and computational neurobiology, undergraduate engineering students are extremely curious about this field.
At IIT Kanpur, Dr Shubham Sahay, Assistant Professor at the Department of Electrical Engineering, introduced a course on neuromorphic computing last year. Despite being a post-graduate level course, he saw great participation from undergrads as well. “Throughout the course, they were very interactive. The huge B.Tech participation in my course bears testimony to the fact that undergrads are really interested in this topic. I believe that this (neuromorphic computing) could be introduced as one of the core courses in the UG curriculum in the future,” he says.
Until recently, neuromorphic computing was a widely used term only in research and not in the commercial arena. However, as of January 18, 2022, BrainChip, a leading provider of ultra-low-power high-performance AI technology, commercialised its AKD1000 AIOT chip. Developers, system integrators, and engineers can now buy AKD1000-powered Mini PCIe boards and leverage them in their applications, especially those requiring on-edge computing, low power consumption, and high-performance AI.
Getting it commercial
“It’s meant as our entry-level product. We want to proliferate this into as many hands as we can and get people designing in the Akida environment,” says Rob Telson, Vice President of WorldWide Sales at BrainChip. Anil Mankar, Co-founder and Chief Development Officer of BrainChip, explains, “We are enabling system integrators to easily use neuromorphic AI in their applications. In India, if some system integrators want to manufacture the board locally, they can take the bill of materials from us (BrainChip) and manufacture it locally.”
What’s fascinating about Akida is that it enables sensor nodes to compute without depending on the cloud. Further, BrainChip’s AI technology not only performs audio and video based learning but even focuses on other sensor modalities like taste, vibration, and smell. You can use it to make a sensor that performs wine tasting! Here is a link to their wine tasting demonstration: Link
Another major event that occurred this year was when Mercedes implemented BrainChip’s Akida technology in its Vision EQXX electric vehicle. This is definitely a big deal since the Akida technology is tried and tested for a smart automotive experience. All features that the Akida provides, including facial recognition, keyword spotting, etc consume extremely low power.
“This is where we get excited. You’ll see a lot of these functionalities in vehicles—recognition of voices, faces, and individuals in the vehicle. This allows the vehicles to have customisation and device personalisation according to the drivers or the passengers as well,” says Telson. These really are exciting times.
Akida MetaTF ML Framework (Source: MetaTF)
Neuromorphic hardware, neural networks, and AI
The process in which neurons work is eerily similar to an electric process. Neurons communicate with each other via synapses. Whenever they receive input, they produce electrical signals called spikes (also called action potentials), and the event is called neuron spiking. When this happens, chemicals called neurotransmitters are released into hundreds of synapses and activate the respective neurons. That’s the reason why this process is super-fast.
Artificial neural networks mimic the logic of the human brain, but on a regular computer. The thing is, regular computers work on the Von Neumann architecture, which is extremely different from the architecture of our brain and is very power-hungry. We may not be able to deploy CMOS logic on the Von Neumann architecture for long. We will eventually reach a threshold to which we can exploit silicon. We are nearing the end of Moore’s Law and there is a need to establish a better computing mechanism. Neuromorphic computing is the solution because neuromorphic hardware realises the structure of the brain in the solid-state.
As we make progress in neuromorphic hardware, we will be able to deploy neural networks on it. Spiking Neural Network (SNN) is a type of artificial neural network that uses time in its model. It transmits information only when triggered—or, in other words, spiked. SNNs used along with neuromorphic chips will transform the way we compute, which is why they are so important for AI.
How to get started with SNNs
Since the entire architecture of neuromorphic AI chips is different, it is only natural to expect the corresponding software framework to be different too. Developers need to be educated on working with SNNs. However, that is not the case with MetaTF, a free software development framework environment that BrainChip launched in April 2021.
“We want to make our environment extremely simple to use. Having people learn a new development environment is not an efficient way to move forward,” says Telson. “We had over 4600 unique users start looking at and playing with MetaTF in 2021. There’s a community out there that wants to learn.”
India and the future of neuromorphic computing
When asked about the scope of neuromorphic computing in India, Dr Sahay mentions, “As of now, the knowledge, dissemination, and expertise in this area is limited to the eminent institutes such as IITs and IISc, but with government initiatives such as India Semiconductor Mission (ISM) and NITI Ayog’s national strategy for artificial intelligence (#AIforall), this field would get a major boost. Also, with respect to opportunities in the industry, several MNCs have memory divisions in India—Micron, Sandisk (WesternDigital), etc—that develop the memory elements which will be used for neuromorphic computing.” There’s a long way to go, but there is absolutely no lack of potential. More companies would eventually have their neuromorphic teams in India.
BrainChip Inc. is also building its university strategy to make sure students are being educated in this arena. Slowly, the research done in neuromorphic computing is making its way into the commercial world and academia. Someday, we might be able to improve our self-driving cars, create artificial skins and prosthetic limbs that can learn things about their surroundings! Consider your smart devices. All of them are dependent on the internet and the cloud. If equipped with a neuromorphic chip, these devices can compute on their own! This is just the start of the neuromorphic revolution.
The author, Aaryaa Padhyegurjar, is an Industry 4.0 enthusiast with a keen interest in innovation and research
PYFO Australia.
Violin1
Regular
Wait until, you see mine......that'll bring the boots out........lolSo , what's happening other than that dorky dude's butt is getting way more attention than what it's worth.
Fullmoonfever
Top 20
I see the DoD issued a pre-release late April and may have already been covered but I found this one interesting.
Similar wording I've seen somewhere previously....not sure of too many COTS....my bold
Note - the doc is 422 pages.
DoD PDF
DEPARTMENT OF DEFENSE
SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM
SBIR 22.2 Program Broad Agency Announcement (BAA)
April 20, 2022: DoD BAA issued for pre-release
May 18, 2022: DoD begins accepting proposals
June 15, 2022: Deadline for receipt of proposals no later than 12:00 p.m. ET
AF NUMBER: AF222-0010
TITLE: Event Based Star Tracker
TECH FOCUS AREAS: Biotechnology Space; Nuclear
TECHNOLOGY AREAS: Nuclear; Sensors; Space Platform
OBJECTIVE: Develop a low SWAP, low cost, high angular rate star tracker for satellite and nuclear
enterprise applications.
DESCRIPTION: Existing star tracking attitude sensors for small satellites and rocket applications are
limited in their ability to operate above an angular rate of approximately 3-5 degrees/second, thus
rendering them useless for both satellite high spin (i.e. lost in space) applications, as well as spinning
rocket body applications. Recent advances in neuromorphic (a.k.a. event based) sensors have
dramatically improved their overall performance2, which allows them to be considered for these high
angular rate applications1. In addition, the difference between a traditional frame-based camera and
an event based camera is simply a matter of how the sensor is read out, which should allow for
electronic switching between event based (i.e. high angular rate) and frame (i.e. low angular rate) modes
within the star tracker. Additional advantages inherent in an event based sensor include high temporal
resolution (µs) and high dynamic range (140 dB), which could allow for multiple modes of continuous
attitude determination (i.e. star tracking, sun sensor, earth limb sensor) within a single small, low
cost sensor package. All technology solutions that meet the topic objective are solicited in this call,
however, neuromorphic sensors appear ideally suited to meet the technical objectives and should
therefore be considered in the solution trade space. The scope of this effort will be to first analyze the
capability of event based sensors to meet a high angular rate star tracker application, define the trade
space for the technical solution against the satellite and nuclear enterprise requirements, develop a
working prototype and test it against the requirements, and finally in Phase 3 move to initial production
of a commercial star tracker unit.
PHASE I: Acquire existing state of the art COTS neuromorphic (a.k.a. event based) sensor or modify
existing star tracking sensor as appropriate. Perform analysis and testing of the event based sensor to
determine feasibility in the high angular rate star tracking satellite and nuclear enterprise applications
PHASE II: Development of a prototype event based high angular rate star tracker. Ideally this prototype
will have the ability to be operated in both event based mode, as well as switch back and forth to
standard (i.e. frame) mode. Explore and document the technical trade space (maximum angular rate,
minimum detection threshold, associated algorithm development, etc.) and potential
military/commercial application of the prototype device.
PHASE III DUAL USE APPLICATIONS: Phase 3 efforts will focus on transitioning the developed
high angular rate attitude sensor technology to a working commercial and/or military solution. Potential
applications include commercial and military satellites, as well as missile applications.
NOTES: The technology within this topic is restricted under the International Traffic in Arms
Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related
material and services, including export of sensitive technical data, or the Export Administration
Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any
proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit
possessed, and the proposed tasks intended for accomplishment by the FN(s) in accordance with
section 5.4.c.(8) of the Announcement and within the AF Component-specific instructions. Offerors are
advised foreign nationals proposed to perform on this topic may be restricted due to the technical data
under US Export Control Laws. Please direct questions to the Air Force SBIR/STTR HelpDesk:
usaf.team@afsbirsttr.us
The only other mention of neuromorphic in my search (haven't checked other keywords yet) is:
OSD222-D02 TITLE: Advanced Integrated CMOS Terahertz (THz) Focal Plane Arrays (FPA)
OUSD (R&E) MODERNIZATION PRIORITY: Microelectronics, AI/ML
TECHNOLOGY AREA(S): Information Systems, Modeling and Simulation Technology
OBJECTIVE: Develop advanced THz-FPA that offer large pixel count, high dynamic range, and high
speed over a broad THz frequency range.
DESCRIPTION: Electromagnetic waves in the THz spectral band (roughly covering the 0.1 – 3 THz
frequency range) offer unique properties for chemical identification, nondestructive imaging, and remote
sensing. However, existing THz devices have not yet provided all the functionalities required to fulfill
many of these applications. Although complementary metal–oxide–semiconductor (CMOS) technologies
have been offering robust solutions below 1 THz, the high-frequency portion of the THz band still lacks
mature devices. For example, most of the THz imaging and spectroscopy systems use single-pixel
detectors, which results in a severe tradeoff between the measurement time and field of view. To address
this problem, a large pixel count, high dynamic range, high speed, and broadband THz-FPA needs to be
developed. The proposed THz-FPA can operate either as a frequency-tunable continuous-wave detector
or a broadband-pulsed detector. It should be able to operate over a 1 – 3 THz frequency range while
offering more than 30 decibel (dB) dynamic range per pixel. It should have more than 1,000 pixels and a
frame rate of at least 1 hertz (Hz). Some anticipated features include developing THz-FPAs by exploring
three-dimensional microstructures, smart readout integrated circuits, and processors that incorporate
neuromorphic computing and ML to increase the data collection efficiency.
Similar wording I've seen somewhere previously....not sure of too many COTS....my bold
Note - the doc is 422 pages.
DoD PDF
DEPARTMENT OF DEFENSE
SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM
SBIR 22.2 Program Broad Agency Announcement (BAA)
April 20, 2022: DoD BAA issued for pre-release
May 18, 2022: DoD begins accepting proposals
June 15, 2022: Deadline for receipt of proposals no later than 12:00 p.m. ET
AF NUMBER: AF222-0010
TITLE: Event Based Star Tracker
TECH FOCUS AREAS: Biotechnology Space; Nuclear
TECHNOLOGY AREAS: Nuclear; Sensors; Space Platform
OBJECTIVE: Develop a low SWAP, low cost, high angular rate star tracker for satellite and nuclear
enterprise applications.
DESCRIPTION: Existing star tracking attitude sensors for small satellites and rocket applications are
limited in their ability to operate above an angular rate of approximately 3-5 degrees/second, thus
rendering them useless for both satellite high spin (i.e. lost in space) applications, as well as spinning
rocket body applications. Recent advances in neuromorphic (a.k.a. event based) sensors have
dramatically improved their overall performance2, which allows them to be considered for these high
angular rate applications1. In addition, the difference between a traditional frame-based camera and
an event based camera is simply a matter of how the sensor is read out, which should allow for
electronic switching between event based (i.e. high angular rate) and frame (i.e. low angular rate) modes
within the star tracker. Additional advantages inherent in an event based sensor include high temporal
resolution (µs) and high dynamic range (140 dB), which could allow for multiple modes of continuous
attitude determination (i.e. star tracking, sun sensor, earth limb sensor) within a single small, low
cost sensor package. All technology solutions that meet the topic objective are solicited in this call,
however, neuromorphic sensors appear ideally suited to meet the technical objectives and should
therefore be considered in the solution trade space. The scope of this effort will be to first analyze the
capability of event based sensors to meet a high angular rate star tracker application, define the trade
space for the technical solution against the satellite and nuclear enterprise requirements, develop a
working prototype and test it against the requirements, and finally in Phase 3 move to initial production
of a commercial star tracker unit.
PHASE I: Acquire existing state of the art COTS neuromorphic (a.k.a. event based) sensor or modify
existing star tracking sensor as appropriate. Perform analysis and testing of the event based sensor to
determine feasibility in the high angular rate star tracking satellite and nuclear enterprise applications
PHASE II: Development of a prototype event based high angular rate star tracker. Ideally this prototype
will have the ability to be operated in both event based mode, as well as switch back and forth to
standard (i.e. frame) mode. Explore and document the technical trade space (maximum angular rate,
minimum detection threshold, associated algorithm development, etc.) and potential
military/commercial application of the prototype device.
PHASE III DUAL USE APPLICATIONS: Phase 3 efforts will focus on transitioning the developed
high angular rate attitude sensor technology to a working commercial and/or military solution. Potential
applications include commercial and military satellites, as well as missile applications.
NOTES: The technology within this topic is restricted under the International Traffic in Arms
Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related
material and services, including export of sensitive technical data, or the Export Administration
Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any
proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit
possessed, and the proposed tasks intended for accomplishment by the FN(s) in accordance with
section 5.4.c.(8) of the Announcement and within the AF Component-specific instructions. Offerors are
advised foreign nationals proposed to perform on this topic may be restricted due to the technical data
under US Export Control Laws. Please direct questions to the Air Force SBIR/STTR HelpDesk:
usaf.team@afsbirsttr.us
The only other mention of neuromorphic in my search (haven't checked other keywords yet) is:
OSD222-D02 TITLE: Advanced Integrated CMOS Terahertz (THz) Focal Plane Arrays (FPA)
OUSD (R&E) MODERNIZATION PRIORITY: Microelectronics, AI/ML
TECHNOLOGY AREA(S): Information Systems, Modeling and Simulation Technology
OBJECTIVE: Develop advanced THz-FPA that offer large pixel count, high dynamic range, and high
speed over a broad THz frequency range.
DESCRIPTION: Electromagnetic waves in the THz spectral band (roughly covering the 0.1 – 3 THz
frequency range) offer unique properties for chemical identification, nondestructive imaging, and remote
sensing. However, existing THz devices have not yet provided all the functionalities required to fulfill
many of these applications. Although complementary metal–oxide–semiconductor (CMOS) technologies
have been offering robust solutions below 1 THz, the high-frequency portion of the THz band still lacks
mature devices. For example, most of the THz imaging and spectroscopy systems use single-pixel
detectors, which results in a severe tradeoff between the measurement time and field of view. To address
this problem, a large pixel count, high dynamic range, high speed, and broadband THz-FPA needs to be
developed. The proposed THz-FPA can operate either as a frequency-tunable continuous-wave detector
or a broadband-pulsed detector. It should be able to operate over a 1 – 3 THz frequency range while
offering more than 30 decibel (dB) dynamic range per pixel. It should have more than 1,000 pixels and a
frame rate of at least 1 hertz (Hz). Some anticipated features include developing THz-FPAs by exploring
three-dimensional microstructures, smart readout integrated circuits, and processors that incorporate
neuromorphic computing and ML to increase the data collection efficiency.
Fact Finder
Top 20
Sorry was that your lamp? I left it in the change room near the lockers after my shift finished. Really sorry.
FFAKIDA BALLISTA
PS: It needs oil.
lynv
Emerged
Dead right. Brain dead Australian Governments! Pardon the pun.
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