D
Deleted member 118
Guest
So we a partner with Merc now maybe brainchip (Tony Dawes) can you update your website
BRN Discussion Ongoing
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thelittleshort
Top Bloke
Jeff Herbst on LinkedIn: Episode 25 — BrainChip CEO Sean Hehir and GFT Founding Managing Partner…
Thanks Sean Hehir, BrainChip CEO, for including me in your recent podcast. I enjoyed the conversation, which just scratched the surface, and which will…
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equanimous
Norse clairvoyant shapeshifter goddess
High chance before Sean applied for CEO of BRN, Jeff Herbst gave the thumbs up and green light to Sean.View attachment 32246
Jeff Herbst on LinkedIn: Episode 25 — BrainChip CEO Sean Hehir and GFT Founding Managing Partner…
Thanks Sean Hehir, BrainChip CEO, for including me in your recent podcast. I enjoyed the conversation, which just scratched the surface, and which will…www.linkedin.com
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buena suerte :-)
BOB Bank of Brainchip
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MaxwellAnne
Regular
1. Thank goodness @stuart888 was not asleep. Thank you for sharing Stuart!I have said it many times when this place is used for its proper purpose to share thoughts (not anxieties) and research this is as close to insider trading as you will get without breaking the law. Many thanks @stuart888 . You see Americans are nice people too.
However lets look at what Teksun replaced Cisco, Toshiba and Lenaro with:
"BrainChip is a technology company making AI everywhere easier to deploy and scale. It’s neuromorphic processor called, Akida™, is pure digital and is an event-based technology that is inherently lower power when compared to conventional neural network accelerators. BrainChip IP supports incremental learning and high-speed inference in a wide variety of use cases, making it cost effective and simple to implement. Designed for sustainable AI, Akida™, performs complex functions at the device level, delivering a real-time, instant response.
BrainChip's solutions have applications in various industries, including automotive, smart homes, security and surveillance. The company has partnered with industry leaders such as Arm, Mercedes Benz, and Renesas driving intelligence into next generation devices."
So,
I knew Brainchip had partnered with ARM its on their website.
I DID NOT know that Brainchip had partnered with Renesas to drive intelligence into next generation devices what was announced on the ASX was that Renesas had purchased two nodes of AKIDA IP and more recently that Renesas had taped out its own chip which it would be bringing to market later in 2023. Even Chippy said in his magazine interview that they had purchased what they needed from Brainchip fullstop. No ongoing partnership was implied in any way shape or form.
I MOST CERTAINLY DID NOT KNOW THAT MERCEDES BENZ HAD PARTNERED WITH BRAINCHIP TO DRIVE INTELLIGENCE INTO NEXT GENERATION DEVICES because all I was told by Brainchip was they could not talk about Mercedes Benz other than to say they continued to work with Mercedes Benz and Mercedes Benz had said they were working with artificial intelligence experts Brainchip. Just because you are working with someone it does not mean it is a partnership nor does it signal anything about your future intentions. Brainchip has on its website that they are trusted by Mercedes Benz. I am trust my brother-in-law but I am not in partnership. This is a significant statement of intent.
Given this is a revised statement I think it is reasonable to conclude that both Teksun and Brainchip have agreed on this wording. Indeed Tony Dawe has said Brainchip has approved this new wording. As such I am just as excited if not more so by what it now publicly reveals. The significance in my opinion dictates the conclusion that Teksun had leverage and wanted something of equal or greater significance to replace Cisco, Toshiba and Lenaro with for the purpose of driving their customers interest in a Teksun Brainchip product offerings. In other words if you don't want us to use Cisco, Toshiba and Lenaro what can we use?
I hope that our German investor friends take comfort from the fact that this partnership between Mercedes Benz and Brainchip to drive intelligence into next generation devices has now been publicly confirmed.
My opinion only DYOR
FF
AKIDA BALLISTA
2. I will only speak for myself as many others are cleverer than me I am sure but I read the revised words and just thought oh ok we know about those. Then I read another ‘great @Fact Finder post’ that teveals there is so much more in those words than I realised. As they say the devil is in the details!
I'd settle for $2.34 for now please....ahh those were the days$$$$AU$360.00 per share!!
The fact that TEKSUN knew that Cisco and Toshiba were partners approved disclosure or not,means that our salesmen may have been namedropping in breach of the very NDA’S that they so vearmently hide behind ,think someone’s arses will be kicked and Brainchip will be quickly having meetings in the US to try and minimise the damage. May have to disclose to the market once the US markets open. Got to laugh might give shorters something to think about
GStocks123
Regular
STM32N6**I reckon Akida IP is in STM32. They are on my target list. Same market as Renesas.
Anil wouldn't like them if they were BRN competitors. So must be NDA partners.
A set of tools to enable Edge AI
on STM32 MCU, MPU and smart sensors
Embedded AI can improve many solutions in a simple, fast, and cost-effective way.
Predictive maintenance, IoT products, smart buildings, asset tracking, people counting and more.
Learn how these applications can become smarter by making data meaningful with machine learning!
Give your product an Edge
Free SW tools to embed Machine Learning on STM32 MCU and MPU. Edge AI can improve your product in a simple, fast, and cost-effective way.stm32ai.st.com
BaconLover
Founding Member
When the next $1.00 party?I'd settle for $2.34 for now please....ahh those were the days
VictorG
Member
I'm free this weekendWhen the next $1.00 party?
D
Deleted member 118
Guest
buena suerte :-)
BOB Bank of Brainchip
Steve10
Regular
Some more research indicates that STMicroelectronics are attempting to do neuromorphic computing with RRAM.
In an article in February, 2022 STM mentioned that neuromorphic chips are not mature enough. They want to move computation to the memory.
In the plenary session of the ISSCC conference, Marco Cassis, president of ST’s Analog, MEMS and Sensors Group, looked at the various AI technologies for sensors. He rules out spiking neural network chips, also called neuromorphic, as not mature, saying current convolutional neural networks can tap into reduced precision and semiconductor scaling to get more performance. However these CNN devices struggle with power consumption and memory bandwidth challenges that get in the way of scalability.
“To overcome this limitation is to partially or completely move the computation to the memory,” he said. “In Memory Computing can bring big benefits, 100x densities and efficiencies compared to current state of the art solutions. Here an especially promising avenue is the use of non volatile resistive memory devices to perform computations in the memory itself.
ST hints at analog in-memory computing chip
STMicroelectronics is looking at the development of an AI chip using analog in-memory computing with its resistive phase change memory. In the plenary session of the ISSCC conference, Marco Cassis, president of ST’s Analog, MEMS and Sensors Group, looked at the various AI technologies for...
www.eenewseurope.com
In May, 2019 to January 2023 a consortium of companies including STM & European Commission got together for the TEMPO project.
Technology and hardware for neuromorphic computing
Project description
New ways to integrate emerging memories to enable neuromorphic computing systems
Artificial intelligence (AI) and machine learning are used today for computing all kinds of data, making predictions and solving problems. These are processes based increasingly on deep neuronal network (DNN) models. As the volume of produced data slow down machines and consume greater amounts of energy, there is a new generation of neural units. The spiking neural networks (SNNs) incorporate biologically-feasible spiking neurons with their temporal dynamics. The EU-funded TEMPO project will leverage emerging memory technology to design new innovative technological solutions that make data integration simpler and easier via new neuronal DNN and SNN computing engines. Reduced core computational operational systems’ neuromorphic algorithms will serve as demonstrators.Objective
Massive adoption of computing in all aspects of human activity has led to unprecedented growth in the amount of data generated. Machine learning has been employed to classify and infer patterns from this abundance of raw data, at various levels of abstraction. Among the algorithms used, brain-inspired, or “neuromorphic”, computation provides a wide range of classification and/or prediction tools. Additionally, certain implementations come about with a significant promise of energy efficiency: highly optimized Deep Neural Network (DNN) engines, ranging up to the efficiency promise of exploratory Spiking Neural Networks (SNN). Given the slowdown of silicon-only scaling, it is important to extend the roadmap of neuromorphic implementations by leveraging fitting technology innovations. Along these lines, the current project aims to sweep technology options, covering emerging memories and 3D integration, and attempt to pair them with contemporary (DNN) and exploratory (SNN) neuromorphic computing paradigms. The process- and design-compatibility of each technology option will be assessed with respect to established integration practices. Core computational kernels of such DNN/SNN algorithms (e.g. dot-product/integrate-and-fire engines) will be reduced to practice in representative demonstrators.Some other well known companies involved are Valeo, Phillips, Thales, Bosch, Infineon & SynSense.
Technology and hardware for neuromorphic computing | TEMPO Project | Fact Sheet | H2020 | CORDIS | European Commission
Massive adoption of computing in all aspects of human activity has led to unprecedented growth in the amount of data generated. Machine learning has been employed to classify and infer patterns from this abundance of raw data, at various levels of abstraction. Among the...
In June, 2022 STM released new inertial sensors containing the intelligent sensor processing unit (ISPU) for on device processing.
The ISM330IS embeds a new ST category of processing, ISPU (intelligent sensor processing unit) to support real-time applications that rely on sensor data. The ISPU is an ultra-low-power, high-performance programmable core which can execute signal processing and AI algorithms in the edge. The main benefits of the ISPU are C programming and an enhanced ecosystem with libraries and 3rd party tools/IDE.
The ISM330ISN is scheduled to enter production in H2 2022 and will be available from st.com or distributors for $3.48 for orders of 1000 pieces. NanoEdge AI Studio enabling the creation of libraries designed for specific ISPU part numbers is available at no charge on ST.com
Due to the release date the ISPU is unlikely to have Akida IP. As neuromorphic hardware becomes available & matures they may be interested.
STMicroelectronics’ new inertial modules enable AI training inside the sensor
Geneva, June 16, 2022 – STMicroelectronics (NYSE: STM), a global semiconductor leader serving customers across the spectrum of electronics applications, has introduced new inertial sensors that con…
www.eejournal.com
STM has a big ecosystem & 200,000 customers.
An integrated device manufacturer, we work with more than 200,000 customers and thousands of partners to design and build products, solutions, and ecosystems that address their challenges and opportunities, and the need to support a more sustainable world. Our technologies enable smarter mobility, more efficient power and energy management, and the wide-scale deployment of the Internet of Things and connectivity.
Steve10
Regular
Interesting.
ST to launch its first neural microcontroller with NPU
Business news | May 12, 2022By Nick Flaherty
STMicroelectronics is set to launch its first microcontroller with a full neural processing unit (NPU).
The STM32N6 includes a proprietary NPU alongside a ARM Cortex core. This gives the same AI performance as a quad core processor with AI accelerator but at one tenth the cost and one twelfth the power consumption, says Remi El-Ouazzane President, Microcontrollers & Digital ICs Group at ST.
The chip will sample at the end of 2022, he said. While there is no mention of the ARM core that will be used, the performance and power figures point to ARM’s M55 or even its latest core, the M85, which has recently been announced. The M85 is ARM’s highest performance M core, issuing up to three instruction per cycle with has internal accelerators for AI that help to boost the performance.
ST is a key lead developer for ARM’s microcontroller cores and uses the ARM M7 core in the dual core M4/M7 STM32H7 and in the STM32F7 family alongside an ART AI accelerator. A new family, N6, points to the use of a new core.
Supporting AI in industrial and embedded designs was a key driver for the recent acquisition of French software tool developer Cartesiam and is part of the strategy to achieve $20bn of revenue between 2025 and 2027.
“The new STM32N6 Neural MCU is dramatically lowering the AI technology implementation price point. This breakthrough supports our roadmap of new generation intelligent sensors allowing rapidly growing adoption in Smart Cities,” said Vincent SABOT, Executive Managing Director of developer Lacroix.
The choice of architecture is key for adding security support and integration with cloud services, and the M55 and M85 supports the ARMv8.1-M architecture. Yesterday ST announced deals with Microsoft and Amazon to connect the microcontrollers to the cloud.
ST is integrating its STM32U5 microcontrollers (MCUs), based on the 160MHz ARM Cortex-M33 core, with Microsoft Azure real time operating system (RTOS) and IoT Middleware and a certified secure implementation of ARM Trusted Firmware -M (TF-M) secure services for embedded systems.
The integration uses the hardened security features of the STM32U5 complemented with the hardened key store of an STSAFE-A110 secure element.
The integration with Amazon Web Services (AWS) also uses the STM32U5, this time with Amazon’s FreeRTOS real time operating system and the ARM trusted-firmware for embedded systems (TF-M).
The reference implementation is built on ST’s B-U585I-IOT02A discovery kit for IoT nodes with support for USB, WiFi, and Bluetooth Low Energy connectivity, as well as multiple sensors. The STSAFE-A110 secure element support is pre-loaded with IoT object credentials to help secure and simplifies attachment between the connected objects and the AWS cloud.
FreeRTOS comprises a kernel optimized for resource-constrained embedded systems and software libraries for connecting various types of IoT endpoints to the AWS cloud or other edge devices. AWS’s long-term support (LTS) is maintained on FreeRTOS releases for two years, which provides developers with a stable platform for deploying and maintaining their IoT devices.
Hardware cryptographic accelerators, secure firmware installation and update, and enhanced resistance to physical attacks provide PSA Certified Level-3 and SESIP 3 certifications.
ST will release an STM32Cube-based integration of reference implementation for both the Azure and AWS integrations in Q3 2022 that will further simplify IoT-device design leveraging tight integration with the wider STM32 ecosystem.
ST to launch its first neural microcontroller with NPU
STMicroelectronics is set to launch its first microcontroller, the STM32N6, with a full neural processing unit (NPU).
www.eenewseurope.com
Food4 thought
Regular
FfBack home on PC.
Much criticism has been levelled at Sean Hehir for not communicating with shareholders over the last several months and to some extent this type of criticism has been made since shortly after he took the reins at Brainchip.
My intention is not to debate the merits of the criticism suffice to say I on two occasions have made clear a concern I had about his communication style, but as I am just an old technophobe without any experience of running, for the sake of this discussion a Silicon Valley type technology start-up that originated from Australia currently listed on the ASX and intending to eventually launch on Nasdaq during a time of global turbulence with the major shareholders and founders looking over my shoulder, so I expressed those concerns directly to the company.
In expressing those concerns it was emphasised that the company was in the process of reinventing its corporate branding as a commercial entity and while it appeared to be taking backward steps these measures were essential if the end goals were to be realised.
I probably do not need to write that Tony Dawe has been under almost constant attack for the best part of six months from shareholders concerned about the direction of the company and that over this time the company has only poorly at one level communicated the importance of what was taking place to set the foundations for success.
These foundations can be summed up from the company's point of view in the one word "ECOSYSTEMS".
So if we look at the avalanche of news over the last couple of weeks, today's promise by Sean Hehir of more to come, and the focus of today's podcast fronted by Sean Hehir being "ECOSYSTEMS" and the qualifications of the guest to speak precisely on this point it is my impression that this podcast was Sean Hehir trying to explain to shareholders why the pain of the last 18 months since his appointment had been necessary.
I posted earlier a quote relating to competitors but the overall paper is about whether the world is ready for neuromorphic computing and in essence it does nothing if not make clear that in the absence of what Sean Hehir and his guest describe as "Ecosystems" an AKIDA technology revolution cannot take place.
Building these "ECOSYSTEMS" is not sexy, it does not bring in immediate income but without technology "ECOSYSTEMS" AKIDA will have no value to anyone.
Sean Hehir used at the AGM last year his three legged chair to describe what he was doing and how without one of the legs a three legged chair cannot stand or be of any use.
"ECOSYSTEMS" were one of the legs of this chair and today was Sean Hehir attempting to explain with the assistance of someone who has done it for Nvidia why taking the time to build "ECOSYSTEMS" to support AKIDA technology just had to be accomplished otherwise failure would be the outcome.
I hope that this podcast has drawn a line in the sand and that going forward we will see a change in the communication that takes place with shareholders and in this regard I am not talking about lots of IP licence agreements being announced what I am talking about is a less introspective style, one where Sean Hehir takes on fully the role of visionary CEO leading from the front confident that all the foundations needed including "ECOSYSTEMS" are firmly in place.
If this all sounds a bit Tesla-ish having a vision that shareholders, customers and "ECOSYSTEM" partners can embrace is in my opinion absolutely essential if Brainchip is to lead the Artificial Intelligence revolution and have the world follow AKIDA technology science fiction forward into the 4th Industrial Revolution.
Well you did ask.
My opinion only DYOR
FF
AKIDA BALLISTA
In my line of business it’s the companies that are well connected seem to do very well.and the ones that don’t , drift along then close.
You can have the best food in town but ì no one knows then you’re gone.
And once people know about you it’s a landslide to see what all the fuss is about.
I just know once we start to roll it will be out of control
Five pages behind reading... I´m flashed with all these new posts every morning here in Germany, when I get up.No mention of said names during an earlier grilling.
BRN Discussion Ongoing
Brand recognition. Everyone in Australia knows Intel. Everyone in Australia knows Mercedes. No one in Australia (TSX aside) knows Renesas. There is an announcement re Renesas which carries the very real implication of royalty income in 9 months give or take, and the share price goes down...thestockexchange.com.au
I bet on an ChatGPT-generated text. Here is my first try and it hit Cisco... So I wouldn´t give too much about the other names. ChatGPT is useful but not smart in every way.
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Steve10
Regular
Remi El-Ouazzane’s Post
Remi El-Ouazzane
10mo
Earlier today during STMicroelectronics Capital Markets Day (https://cmd.st.com), I gave a presentation on MDG contribution to our ambition of reaching $20B revenue ambition by 2025-27. During the event, I was proud to pre-announce the #STM32N6: a high performance #STM32 #MCU with our new internally developed Neural Processing Unit (#NPU) providing an order of magnitude benefit in both inference/w and inference/$ against alternative MPU solutions The #STM32N6 will deliver #MPU #AI workloads at the cost and the power consumption of #MCU. This a complete game changer that will open new ranges of applications for our customers and allow them to democratise #AI at the edge. I am excited to say we are on track to deliver first samples of the #STM32N6by the end of 2022. I I am even more excited to announce that LACROIX will leverage this technology in their next generation smart city products. Stay tuned for more news on the #STM32N6 in the coming months :=)
From in memory computing to in-house developed NPU. That was a quick change of direction.
ARM Cortex-M55 has been mentioned in a few AI articles. This chip should also be suitable for Akida IP integration as it has Helium technology same as M85.
The STM32N6 was still not launched in late November 2022.
AMend.7 (Customer) asked a question.
November 22, 2022 at 9:43 PM
STM32N6
Hi,
When ST will release more information about the STM32N6? Will it use the new cortex-m55? Can it be used in motor control applications?
Some more research indicates that STMicroelectronics are attempting to do neuromorphic computing with RRAM.
In an article in February, 2022 STM mentioned that neuromorphic chips are not mature enough. They want to move computation to the memory.
In the plenary session of the ISSCC conference, Marco Cassis, president of ST’s Analog, MEMS and Sensors Group, looked at the various AI technologies for sensors. He rules out spiking neural network chips, also called neuromorphic, as not mature, saying current convolutional neural networks can tap into reduced precision and semiconductor scaling to get more performance. However these CNN devices struggle with power consumption and memory bandwidth challenges that get in the way of scalability.
“To overcome this limitation is to partially or completely move the computation to the memory,” he said. “In Memory Computing can bring big benefits, 100x densities and efficiencies compared to current state of the art solutions. Here an especially promising avenue is the use of non volatile resistive memory devices to perform computations in the memory itself.
ST hints at analog in-memory computing chip
STMicroelectronics is looking at the development of an AI chip using analog in-memory computing with its resistive phase change memory. In the plenary session of the ISSCC conference, Marco Cassis, president of ST’s Analog, MEMS and Sensors Group, looked at the various AI technologies for...
In May, 2019 to January 2023 a consortium of companies including STM & European Commission got together for the TEMPO project.
Technology and hardware for neuromorphic computing
Project description
New ways to integrate emerging memories to enable neuromorphic computing systems
Artificial intelligence (AI) and machine learning are used today for computing all kinds of data, making predictions and solving problems. These are processes based increasingly on deep neuronal network (DNN) models. As the volume of produced data slow down machines and consume greater amounts of energy, there is a new generation of neural units. The spiking neural networks (SNNs) incorporate biologically-feasible spiking neurons with their temporal dynamics. The EU-funded TEMPO project will leverage emerging memory technology to design new innovative technological solutions that make data integration simpler and easier via new neuronal DNN and SNN computing engines. Reduced core computational operational systems’ neuromorphic algorithms will serve as demonstrators.
Objective
Massive adoption of computing in all aspects of human activity has led to unprecedented growth in the amount of data generated. Machine learning has been employed to classify and infer patterns from this abundance of raw data, at various levels of abstraction. Among the algorithms used, brain-inspired, or “neuromorphic”, computation provides a wide range of classification and/or prediction tools. Additionally, certain implementations come about with a significant promise of energy efficiency: highly optimized Deep Neural Network (DNN) engines, ranging up to the efficiency promise of exploratory Spiking Neural Networks (SNN). Given the slowdown of silicon-only scaling, it is important to extend the roadmap of neuromorphic implementations by leveraging fitting technology innovations. Along these lines, the current project aims to sweep technology options, covering emerging memories and 3D integration, and attempt to pair them with contemporary (DNN) and exploratory (SNN) neuromorphic computing paradigms. The process- and design-compatibility of each technology option will be assessed with respect to established integration practices. Core computational kernels of such DNN/SNN algorithms (e.g. dot-product/integrate-and-fire engines) will be reduced to practice in representative demonstrators.
Some other well known companies involved are Valeo, Phillips, Thales, Bosch, Infineon & SynSense.
Technology and hardware for neuromorphic computing | TEMPO Project | Fact Sheet | H2020 | CORDIS | European Commission
Massive adoption of computing in all aspects of human activity has led to unprecedented growth in the amount of data generated. Machine learning has been employed to classify and infer patterns from this abundance of raw data, at various levels of abstraction. Among the...cordis.europa.eu
In June, 2022 STM released new inertial sensors containing the intelligent sensor processing unit (ISPU) for on device processing.
The ISM330IS embeds a new ST category of processing, ISPU (intelligent sensor processing unit) to support real-time applications that rely on sensor data. The ISPU is an ultra-low-power, high-performance programmable core which can execute signal processing and AI algorithms in the edge. The main benefits of the ISPU are C programming and an enhanced ecosystem with libraries and 3rd party tools/IDE.
The ISM330ISN is scheduled to enter production in H2 2022 and will be available from st.com or distributors for $3.48 for orders of 1000 pieces. NanoEdge AI Studio enabling the creation of libraries designed for specific ISPU part numbers is available at no charge on ST.com
Due to the release date the ISPU is unlikely to have Akida IP. As neuromorphic hardware becomes available & matures they may be interested.
STMicroelectronics’ new inertial modules enable AI training inside the sensor
Geneva, June 16, 2022 – STMicroelectronics (NYSE: STM), a global semiconductor leader serving customers across the spectrum of electronics applications, has introduced new inertial sensors that con…
STM has a big ecosystem & 200,000 customers.
An integrated device manufacturer, we work with more than 200,000 customers and thousands of partners to design and build products, solutions, and ecosystems that address their challenges and opportunities, and the need to support a more sustainable world. Our technologies enable smarter mobility, more efficient power and energy management, and the wide-scale deployment of the Internet of Things and connectivity.
Boab
I wish I could paint like Vincent
GM to put Chatgpt into vehicles
GM explores using ChatGPT in vehicles
General Motors Co is exploring uses for ChatGPT as part of its broader collaboration with Microsoft Corp , a company executive told Reuters.
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