BRN Discussion Ongoing

[equanimous]

The ones we have installed in our work vehicles(seeing machines sold and monitored by westrac) have no issue with glasses or sunglasses. the early version one models had a few issues with some polarised lenses but that has been fixed which is good as safety glasses have to be worn on site at all times, even while driving. As I have been installing and maintaining these I have had a good chance to play with them without sending out alerts to my boss. They are very accurate as far as I can tell no matter what your wearing. biggest issue has been people putting their heads on funny angles, particularly when driving into morning or afternoon sun, it thinks they have gone to sleep.

I wonder if the vehicle would consider road rage a medical fit, pull the car over and call the ambulance..

 

[ndefries]

What is the chance that Valeo is going to release ground breaking LiDAR in 2023. What is the chance this is going to be a significant development for the future of autonomous driving across the world and a very profitable and sustainable product for Valeo shareholders.

What is the chance that as a development partner of Brainchip that they will go it alone without our IP in the LiDAR.

It's good to be a shareholder!

 

[equanimous]

If the point of capping is to accumulate at a lower price, they sure are selling a lot to cap the price and not buying much to accumulate.

They are betting on CPI report sept 13 and interest rate announcement 21st of September

 

[Cyw]

They are betting on CPI report sept 13 and interest rate announcement 21st of September

Picking one stock to do that? I would write calls on the S&P500 instead.

 

[Bravo]

Interesting...SnapDragon CPUs utilizes Arm architecture.

Qualcomm, China Partner Unveil New LIDAR Platform​

By
GEORGE LURIE
September 7, 2022
https://www.linkedin.com/shareArtic...comm,+China+Partner+Unveil+New+LIDAR+Platform

https://www.sdbj.com/technology/qualcomm-china-partner-unveil-new-lidar-platform/#

Chinese auto maker Great Wall Motor Co.’s new WEY brand of vehicles will feature the Snapdragon Digital Chassis from Qualcomm. Photo courtesy of Qualcomm
Qualcomm Technologies and Great Wall Motor Co. Ltd. (GWM) made a splash in China last week with the debut of GWM’s new autonomous vehicle LIDAR driving system, which utilizes Qualcomm’s proprietary Snapdragon Digital Chassis Platform.

GWM’s new Mocca DHT-PHEV LIDAR – part of the Chinese automaker’s WEY brand — was unveiled at the Chengdu Motor Show on Aug. 29.
Building on the partnership between GWM and Qualcomm, GWM’s LIDAR will be equipped with the Snapdragon Digital Chassis.
Qualcomm said in a recent press note that the partnership “leverage[es] Snapdragon Auto Connectivity Platforms for fast and reliable connectivity” with third generation “Snapdragon Cockpit Platform’s leading compute performance and rich audio and visual processing capabilities.”

The LIDAR system utilizes the Snapdragon Ride Platform for advanced driving assistance systems (ADAS) and automated driving systems (AD), allowing GWM to offer “China’s first commercialized vehicle” to feature Qualcomm’s platform, the note also stated.
Cristiano Amon
CEO
Qualcomm
- Advertisement -

​

In July, Qualcomm CEO Cristiano Amon said, “In automotive, the Snapdragon Digital Chassis is fast becoming the industry’s platform of choice and is enabling the transition to next-generation vehicles.”
Qualcomm’s automotive design pipeline is now “over $19 billion,” Amon said – up $3 billion just since Q2. “We are very pleased with the continued traction and design wins across global automakers and Tier 1 partners,” Qualcomm’s CEO added.
Qualcomm made a major move into the automotive sector earlier this year when the company purchased Swedish firm Veoneer, a pioneer in autonomous driving software. In 2022, the Volkswagen Group’s software company CARIAD also tapped Qualcomm to supply chips to enable assisted and automated driving functions for VW-made vehicles expected to hit the market in 2025.

Auto Investor Day Coming​

Qualcomm will be hosting its Automotive Investor Day on September 22 in San Diego. The event, to be livestreamed, will feature an overview of the company’s automotive-related business vision and strategies — and will also include a live Q&A session with company executives.
Qualcomm’s Snapdragon Ride Platform is a comprehensive portfolio for high performance central compute and vision system solutions based on the Snapdragon family of automotive system-on-chips (SoCs) and accelerator products.
Qualcomm’s low-power, high-performance platforms allow for scaling all tiers of ADAS and AD systems, ranging from regulatory NCAP solutions to highly automated driving.
Utilizing the Snapdragon Ride Platform, the WEY Mocca DHT-PHEV LIDAR Edition is designed to process more than 12 cameras, multi-radars and lidars on the combination of the industry leading 5nm ADAS SoC and accelerator, while implementing a safety critical ADAS system.
Qualcomm, in its press note, said its Snapdragon Ride Platform will provide “differentiated intelligent driving solutions and unique customization” for the WEY LIDAR system, “from concept to start of production, which is projected to be in less than two years.”
The system has support for real-time rendering, high-resolution display and extreme color reproduction of images captured with vehicle’s cameras on its cockpit screens, which allows users to enjoy “more convenient, smarter and safer immersive driving experiences,” the note also stated.

International Collaboration​

Great Wall and Qualcomm have collaborated for several years across multiple technology areas, including advanced in-vehicle connectivity and digital cockpit.
GWM has already launched several commercial vehicles using Qualcomm Technologies’ intelligent connected vehicle (ICV) products, which are powered by Snapdragon Digital Chassis solutions.
GWM makes gas and electric vehicles (EVs) and is planning to roll out hydrogen fuel cell SUVs later this year. The company was founded in 1984 and is headquartered in Hebei Province. China’s largest manufacturer of SUVs and the country’s eighth-largest auto maker, GWM sold 1.3 million vehicles in 2021.
GWM shares are listed on the Hong Kong (HSI) stock exchange and also on the U.S. OTC market under the ticker GWLLY. The company has more than 100 subsidiaries and over 60,000 employees.

Great Wall Motor Co.
FOUNDED: 1984
CEO: Wang Fengying
EMPLOYEES: 60,000+
HEADQUARTERS: Baoding, China
ANNUAL SALES: 1.3 million (2021)
STOCK: GWLLY (OTC)
NOTABLE: GWM is China’s largest SUV manufacturer.
Qualcomm Technologies
FOUNDED: 1985
CEO: Cristiana Amon
EMPLOYEES: 41,000+
HEADQUARTERS: San Diego
REVENUE: $33.57 billion (2021)
STOCK: QCOM (NASDAQ)
WEBSITE: www.qualcomm.com
SOCIAL IMPACT: Qualcomm says it is working to “create a world where everyone and everything can be intelligently connected.”
NOTABLE: The company just signed a multi-year global strategic collaboration agreement with English soccer club Manchester United that will feature Qualcomm’s Snapdragon brand.

 

[Pmel]

Looking at last 100 transactions . Hardly in total of 100k. They are trying hard to bring it down and accumulate more. Whatever i am not selling mine and by the looks of it many are not selling. They could be buying and selling to themselves.

DYOR

 

[Fullmoonfever]

On phone so bit abbreviated on content but links worth a look into.

Will try move to NASA thread as well when get chance.

Reckon given our existing links with those like Intellisense and Numem and NASA projects these are worth keeping an eye on for 2022 solicitations.

Specifically as Intellisense got the Ph II approval on NECR which is "congnitive" based.

NASA quote from the Deep Neural Net solicitation.

"Neuromorphic processing offers the potential to bridge this gap through a novel hardware approach. Existing research in the area shows neuromorphic processors to be up to 1,000 times more energy efficient than GP-GPUs in artificial intelligence applications. Obviously, the true performance depends on the application, but nevertheless the architecture has demonstrated characteristics that make it well-adapted to the space environment."

Main page.

https://www.sbir.gov/node/2120025

Spacecraft Autonomous Agent Cognitive Architectures for Human Exploration​

Spacecraft Autonomous Agent Cognitive Architectures for Human Exploration | SBIR.gov

www.sbir.gov

This subtopic solicits intelligent autonomous agent cognitive architectures that are open, modular, make decisions under uncertainty, and learn in a manner that the performance of the system is assured and improves over time. Cognitive agents for space applications need to adapt and learn from observation, instruction, and interaction as missions proceed. The value of preprogrammed agents that do not adapt over time will diminish in extended missions. This subtopic will enable small businesses to develop both the learning technology and the necessary assurance technology within the scope of cognitive agents that forward base mission control to spacecraft and habitats and multiply the cognitive assets available to the crew. It should be feasible for cognitive agents based on these architectures to be certified or licensed for use on deep space missions to act as liaisons that interact with the mission control operators, the crew, and most, if not all, of the spacecraft subsystems. With such a cognitive agent that has access to all onboard data and communications, the agent could continually integrate this dynamic information and advise the crew and mission control accordingly by multiple modes of interaction including text, speech, and animated images

Deep Neural Net and Neuromorphic Processors for In-Space Autonomy and Cognition​

Deep Neural Net and Neuromorphic Processors for In-Space Autonomy and Cognition | SBIR.gov

www.sbir.gov

This subtopic specifically focuses on advances in signal and data processing. Neuromorphic processing will enable NASA to meet growing demands for applying artificial intelligence and machine learning algorithms onboard a spacecraft to optimize and automate operations. This includes enabling cognitive systems to improve mission communication and data-processing capabilities, enhance computing performance, and reduce memory requirements. Neuromorphic processors can enable a spacecraft to sense, adapt, act, and learn from its experiences and from the unknown environment without necessitating involvement from a mission operations team. Additionally, this processing architecture shows promise for addressing the power requirements that traditional computing architectures now struggle to meet in space applications.

The goal of this program is to develop neuromorphic processing software, hardware, algorithms, architectures, simulators, and techniques as enabling capability for autonomous space operations. Emerging memristor and other radiation-tolerant devices, which show potential for addressing the need for energy-efficient neuromorphic processors and improved signal processing capability, are of particular interest due to their resistance to the effects of radiation.

Additional areas of interest for research and/or technology development include: (a) spiking algorithms that learn from the environment and improve operations, (b) neuromorphic processing approaches to enhance data processing, computing performance, and memory conservation, and (c) new brain-inspired chips and breakthroughs in machine understanding/intelligence. Novel memristor approaches that show promise for space applications are also sought.

Cognitive Communication​

Cognitive Communication | SBIR.gov

www.sbir.gov

NASA's Space Communication and Navigation (SCaN) program seeks innovative approaches to increase mission science data return, improve resource efficiencies for NASA missions and communication networks, and ensure resilience in the unpredictable space environment. The Cognitive Communication subtopic specifically focuses on advances in space communication driven by onboard data processing and modern space networking capabilities. A cognitive system is envisioned to sense, detect, adapt, and learn from its experiences and environment to optimize the communications capabilities for the user mission satellite or network infrastructure. The underlying need for these technologies is to reduce both the mission and network operations burden.

High-Performance Space Computing Technology​

We know SiFive probs in this one so...

High-Performance Space Computing Technology | SBIR.gov

www.sbir.gov

• Coprocessors to (a) accelerate onboard artificial intelligence applications, or (b) perform digital signal processing (DSP) functions. Specifically, technologies are sought that either enable the reliable use of commercial off-the-shelf (COTS) coprocessors in space systems, or fault-tolerant IP cores that can be implemented in a radiation-hardened field-programmable gate array (FPGA).

 

[equanimous]

Picking one stock to do that? I would write calls on the S&P500 instead.

Multiple people do it on multuple stocks especially stocks they dislike like the Shareman crew

 

[jk6199]

Another tug of war today to try and limit the share price.

Most of the people on this site know the true value of BRN is hard to judge, especially the potential upside.

I sit here thinking that it won't be long before one of these behind the scenes companies, will want to break cover and get the word out they are well into the future with their technology. First advantage!

Shorting shares have this to deal with every day an announcement may come from no where, and it may not be from BRN like Mercedes?

Good luck to genuine holders.

 

[Bravo]

Neuromorphic Computing Will Revolutionize the Edge​

September 11, 2022 Sally Ward-Foxton

As biomimicry in computing becomes mainstream, it will start by changing everything about edge computing.

Biomimicry, the science-slash-art of copying natural structures, is not a new idea. For decades, we have been trying to copy biological brains to make efficient computers, only slightly deterred by the fact that we don’t know how biological intelligence works exactly. Armed with our best guesses, we developed models of the neuron and spiking neural networks based on the human brain, and we are now trying to develop these in silicon. Silicon imitations generally use simplified versions of the neuron, but they can still offer distinct advantages to edge applications that need fast, energy-efficient processing to make decisions.

ABI Research reports that 4.6 billion sensors will ship in 2027, embedded in smart-home devices, robots, and appliances, up from 1.8 billion in 2021. These additional sensors will support existing and new functions going forward, resulting in a surge of sensor data that will need to be processed. While the vast majority of smart-home devices and appliances will feature internet connections by 2027, the cloud may not be the best place for this data to be processed. There’s a cost attached to hosting and processing this data in the cloud, it’s slow, and there are privacy implications.

The best bet for processing sensor data in real time, very close to the sensor, may well be neuromorphic computing. Demonstrations of neuromorphic computing systems have proven the technology’s value for ultra-fast, ultra-low–power decision-making at the edge. Biomimicry in computing and neuromorphic computing are poised to bring a whole new level of intelligence to edge devices, making it feasible to add decision-making power to devices with extreme limits on energy consumption and speed. As spiking networks and specialized hardware continue to develop, the effects will become even more pronounced.

Neuromorphic’s competitor, deep learning (the paradigm that powers most of mainstream AI today), is developing fast. Today, it’s easily possible to do small deep-learning applications, including keyword spotting and basic image processing, on a sub-US$1 microcontroller. But neuromorphic concepts take this a step further, squeezing into minuscule energy budgets. Will these technologies compete or coexist at the edge? The most likely medium-term scenario is coexistence — with millions of use cases at the edge, there are millions of niches, and some may suit neuromorphic computing better, for technical or commercial reasons.

While the demise of Moore’s Law has been somewhat circumvented by accelerated computing/domain-specific computing, it’s still a tricky balance between flexibility in the computing architecture and performance, especially for quickly evolving workloads like AI. Taking our cue from the most efficient computer ever known — the human brain — and using the results of millions of years of evolution as a starting point feels like a safe bet.

https://www.eetimes.eu/neuromorphic-computing-will-revolutionize-the-edge/

 

[Fact Finder]

Neuromorphic Computing Will Revolutionize the Edge​

September 11, 2022 Sally Ward-Foxton

As biomimicry in computing becomes mainstream, it will start by changing everything about edge computing.

Biomimicry, the science-slash-art of copying natural structures, is not a new idea. For decades, we have been trying to copy biological brains to make efficient computers, only slightly deterred by the fact that we don’t know how biological intelligence works exactly. Armed with our best guesses, we developed models of the neuron and spiking neural networks based on the human brain, and we are now trying to develop these in silicon. Silicon imitations generally use simplified versions of the neuron, but they can still offer distinct advantages to edge applications that need fast, energy-efficient processing to make decisions.​

​

ABI Research reports that 4.6 billion sensors will ship in 2027, embedded in smart-home devices, robots, and appliances, up from 1.8 billion in 2021. These additional sensors will support existing and new functions going forward, resulting in a surge of sensor data that will need to be processed. While the vast majority of smart-home devices and appliances will feature internet connections by 2027, the cloud may not be the best place for this data to be processed. There’s a cost attached to hosting and processing this data in the cloud, it’s slow, and there are privacy implications.​

​

The best bet for processing sensor data in real time, very close to the sensor, may well be neuromorphic computing. Demonstrations of neuromorphic computing systems have proven the technology’s value for ultra-fast, ultra-low–power decision-making at the edge. Biomimicry in computing and neuromorphic computing are poised to bring a whole new level of intelligence to edge devices, making it feasible to add decision-making power to devices with extreme limits on energy consumption and speed. As spiking networks and specialized hardware continue to develop, the effects will become even more pronounced.​

​

Neuromorphic’s competitor, deep learning (the paradigm that powers most of mainstream AI today), is developing fast. Today, it’s easily possible to do small deep-learning applications, including keyword spotting and basic image processing, on a sub-US$1 microcontroller. But neuromorphic concepts take this a step further, squeezing into minuscule energy budgets. Will these technologies compete or coexist at the edge? The most likely medium-term scenario is coexistence — with millions of use cases at the edge, there are millions of niches, and some may suit neuromorphic computing better, for technical or commercial reasons.​

​

While the demise of Moore’s Law has been somewhat circumvented by accelerated computing/domain-specific computing, it’s still a tricky balance between flexibility in the computing architecture and performance, especially for quickly evolving workloads like AI. Taking our cue from the most efficient computer ever known — the human brain — and using the results of millions of years of evolution as a starting point feels like a safe bet.​

​

https://www.eetimes.eu/neuromorphic-computing-will-revolutionize-the-edge/

4.6 billion sensors in 2027.

Is it reasonable to expect that Valeo, ARM, SiFive, Renesas, MegaChips, Prophesee, nViso, Edge Impulse, NASA, ISL, Intellisense and Numen will capture 10 percent or more of this market which is 460 million sensors being made smart with neuromorphic edge computing.

460 million times 10 cents is $US46 million

460 million times 50 cents is $US230 million

Perhaps some might think 10% is far too conservative for these 12 companies to capture.

If they capture 40% of this market then these numbers jump to $US184 million to $US920 million.

Silly me I left out Mercedes Benz automotive sensor applications.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Bravo]

4.6 billion sensors in 2027.

Is it reasonable to expect that Valeo, ARM, SiFive, Renesas, MegaChips, Prophesee, nViso, Edge Impulse, NASA, ISL, Intellisense and Numen will capture 10 percent or more of this market which is 460 million sensors being made smart with neuromorphic edge computing.

460 million times 10 cents is $US46 million

460 million times 50 cents is $US230 million

Perhaps some might think 10% is far too conservative for these 12 companies to capture.

If they capture 40% of this market then these numbers jump to $US184 million to $US920 million.

Silly me I left out Mercedes Benz automotive sensor applications.

My opinion only DYOR
FF

AKIDA BALLISTA

Yes, silly you FF! You also left out Nanose which Professor Haick said will be available within 3 years.

 

[Fact Finder]

Yes, silly you FF! You also left out Nanose which Professor Haick said will be available within 3 years.

Sorry...My teachers were always saying 'Could do better.'

 

[Fact Finder]

Yes, silly you FF! You also left out Nanose which Professor Haick said will be available within 3 years.

And of course there might be other companies in the 8 to 10 yet to be exposed NDA EAP customers who work in the edge sensor space covering agriculture, industrial robotics, aviation, mining, health delivery, drones and before you pick me up on it I left out Biotome and Leaky Gut Belt.

My opinion only but even 40% might be seen as conservative so DYOR
FF

AKIDA BALLISTA

 

[supersonic001]

How to benefit from BrainChip’s breathtaking potential in 2022​

Behzad Golmohammadi, June 17, 2022

Who is BrainChip?​

BrainChip Holdings Ltd (ASX: BRN) develops software and hardware solutions for artificial intelligence (AI) and machine learning applications. The company’s key product is the Akida Neuromorphic Processor, which is in essence a Spiking Neural Network (SNN). It provides ultra-low power and fast AI (artificial intelligence) Edge computing solutions without the need for a continuous internet connection. Additionally, unsupervised learning capabilities and on-chip processing (rather than in the Cloud) set Akida apart from other AI solutions on the market

do you have a link to this report @Fact Finder ? i'm not a member ....... chrs

 

[Fact Finder]

And of course there might be other companies in the 8 to 10 yet to be exposed NDA EAP customers who work in the edge sensor space covering agriculture, industrial robotics, aviation, mining, health delivery, drones and before you pick me up on it I left out Biotome and Leaky Gut Belt.

My opinion only but even 40% might be seen as conservative so DYOR
FF

AKIDA BALLISTA

Then there are those less important things like intelligent door bells, home & commercial security, white goods, aged and disability in home monitoring that might be covered by these NDA EAP's. Just think how big the market would be on social media for an intelligent common sense detector (made this one up) but in the 5G and 6G network space the cognitive communication system will need intelligent sensors and someone was at least talking to Brainchip in the communication space according to the CEO Sean Hehir not that long ago.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Fact Finder]

How to benefit from BrainChip’s breathtaking potential in 2022​

Behzad Golmohammadi, June 17, 2022

Who is BrainChip?​

BrainChip Holdings Ltd (ASX: BRN) develops software and hardware solutions for artificial intelligence (AI) and machine learning applications. The company’s key product is the Akida Neuromorphic Processor, which is in essence a Spiking Neural Network (SNN). It provides ultra-low power and fast AI (artificial intelligence) Edge computing solutions without the need for a continuous internet connection. Additionally, unsupervised learning capabilities and on-chip processing (rather than in the Cloud) set Akida apart from other AI solutions on the market

Sorry I am not either but the full article was posted by someone else here so we must have someone else amongst the 1,000 Eyes who can assist with Stocks Down Under.
Regards
FF

AKIDA BALLISTA

 

[buena suerte :-)]

Sorry I am not either but the full article was posted by someone else here so we must have someone else amongst the 1,000 Eyes who can assist with Stocks Down Under.
Regards
FF

AKIDA BALLISTA

BRN Discussion Ongoing

Hi FF, my minds in a bit of a quandary in regard to Intel's ( Loihi ) and IBM's ( TrueNorth ) and there usefulness only as research hardware ?. Are they both still being developed further, and could still be contenders, ( competition ) as they are or could be, ??. For years it has been stated...

thestockexchange.com.au

 

[Steve10]

4.6 billion sensors in 2027.

Is it reasonable to expect that Valeo, ARM, SiFive, Renesas, MegaChips, Prophesee, nViso, Edge Impulse, NASA, ISL, Intellisense and Numen will capture 10 percent or more of this market which is 460 million sensors being made smart with neuromorphic edge computing.

460 million times 10 cents is $US46 million

460 million times 50 cents is $US230 million

Perhaps some might think 10% is far too conservative for these 12 companies to capture.

If they capture 40% of this market then these numbers jump to $US184 million to $US920 million.

Silly me I left out Mercedes Benz automotive sensor applications.

My opinion only DYOR
FF

AKIDA BALLISTA

Appears 5G IoT will have 159% CAGR from 2021-2025.

 

[DaBenjamins]

I know we've spoken about 'Gaming', but anyone notice its highlighted in list of applications mentioned in the latest Brainchip video. All the other apps seem to have some general infrastructure, machinery link, however Gaming seems to be a bit of an outlier and more specific that IOT, also mentioned.

Interesting in the context of Megachips/Nintendo. New Switch 2 console tipped to be released 2024.

Video again. Giddy-up.

BrainChip demonstrates Regression Analysis with Vibration Sensors​