Sorry for asking but anything to do with BRN?Menu
View attachment 65762
Blog
Sunny skies and electric energy: RISC-V Summit Europe 2024 shines in Munich
28 June, 2024
by Tora Fridholm
This week, the 2024 edition of RISC-V Summit Europe took place in lovely Munich, Germany. Those of us who attended last year’s edition in Barcelona might not have expected the same weather but Munich was up for the challenge and served us a sunny, hot week, only interrupted by a thunderstorm that shook up some conference attendees (including me!) on the Wednesday afternoon. However, thunderbolts and lightning were also present in a less literal form as massive applause following the many talks, and an abundance of photos and selfies taken in the expo hall and at the social events.
Our CEO Ron Black gave a keynote on: ”Solving the RISC-V puzzle – Optimal performance with zero risk”
AI, AI, AI…
Of course, AI is a hot topic and was mentioned probably in most of the presentations. I very much appreciated the keynote by Edward Wilford, analyst at Omdia. Edward talked about ”The intelligent wave: How a growth in advanced and accelerated compute will drive adoption of RISC-V.” I really enjoyed hearing his angle on generative AI not being a solution. Whereas embedded AI, on the edge, is where it’s getting interesting. Edward described embedded AI as AI you have control over, and encouraged the community to sell AI for what it can do: it’s a feature, not a product.
This ties in well with the demo at the Codasip booth of AI inference for anomaly detection on an embedded RISC-V core. We actually did the same demo at DAC in San Francisco and you can watch a video of this Codasip L110 demo here.
With my colleague Keith Graham at the Codasip booth
Pioneering next-generation automotive
The topic of AI-driven anomaly detection brings me to another highlight of RISC-V Summit Europe this year: the Wednesday morning keynote by Thomas Böhm, Senior Vice President & General Manager Microcontroller Automotive at Infineon Technologies. Thomas said AI will drive automotive feature disruption in the next decade. He also pointed out there is still much innovation to be done in the automotive industry for example related to safety and security features. This innovation will come from technologies such as accelerators enabled by RISC-V.
The strong trend of RISC-V driving innovation in automotive was also highlighted in talks by Bosch and Quintaris. It’s clear, RISC-V is here to stay in automotive and this trend is only getting started.
Several projects are working on increasing alignment and securing long-term support for RISC-V.
All the CHERI you can eat
At Codasip, we have invested in creating the first commercial implementation of the memory safety technology CHERI so obviously we see the great potential in this innovation from the University of Cambridge. At the Summit, CHERI was a hotter topic than ever and included in presentations and posters from lowRISC, the University of Cambridge, Minerva, and the University of Minho. Also SiFive’s Krste Asanovic talked about CHERI bringing capabilities to RISC-V in his State of the Union address.
Andres Amaya and Tariq Kurd from Codasip, and Franz Fuchs from the University of Cambridge presenting CHERI
Our Chief Architect Tariq Kurd had a presentation on standardizing CHERI for RISC-V. However, he hijacked his own presentation to go off script on a CHERI FAQ based on all the discussions he had during the conference. With a major delegation from the University of Cambridge present, Tariq was spot on in his opening statement: It’s safe to say any questions you have about CHERI can be answered by someone who is currently in this room.
And that is also a very nice way to wrap up this brief summary. With such a major gathering of RISC-V enthusiasts at the same event, you had ample opportunity to get questions answered, but the inspiring conversations also generated new ones. These fresh inquiries will surely spark ideas for presentations at the next event. All of us here at Codasip are looking forward to it!
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
DingoBorat
Slim
C'mon Guzzi, although BrainChip isn't mentioned, it's the Vibe!
A.I. A.I. A.I...
That's what we do!
So we are in the "right" Market and most definitely, at the "right" Time.
As Sean has said, on a couple of occasions now, the type of engagements he's having with potential customers (which includes the largest Tech Companies on this Planet) are more serious.
They have plans and they have budgets.
He also said, we are on the cusp of "generating sustainable revenue streams".
This to me, is an indication of things already in play, not the possibility of new IP deals (as revenue from these, while very significant "gold in the ground" would be some way out).
Some of this revenue, could be attributed to Edge Box sales, but I think the language is more far reaching than that and possibly alludes to Renesas or MegaChips associated business progress.
Of course, the proof is in the pudding and Sean has been caught out with his pants down a couple of times now, at least..
Hopefully this is the Reality, where I end up being rich
...
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wilzy123
Founding Member
No narrative mate. Just dishing back some of the rubbish you put out
Do you notice how the only reception your comments get are from me?
Does that give you any indication of how insignificant your concerns are?
Keep the bin dry and full of fresh material. We enjoy seeing it alight.
Pom down under
Regular
Product Engineering Services | IoT and AI Solutions Company
Teksun Inc is a Product Design & Development Company specializing in digital transformation and connected IoT and AI solutions across the industry spectrum.
teksun.com
Teksun Inc on LinkedIn: Product Engineering Services | IoT and AI Solutions Company
Introducing #TelepGunShotDetection is an advanced system equipped with cutting-edge AI algorithms designed for seamless integration with any hardware. Our…
Frangipani
Regular
It finally dawned on me why it is taking Sean (Irish variant of John) so long to pick a new CMO, despite stating at the AGM more than five weeks ago:
He must have decided to play it safe and wait for qualified applicants named Matthew, Mark or Luke
… 
He must have decided to play it safe and wait for qualified applicants named Matthew, Mark or Luke
… 
Mt09
Regular
Righto..It finally dawned on me why it is taking Sean (Irish variant of John) so long to pick a new CMO, despite stating at the AGM more than five weeks ago:
View attachment 65770
He must have decided to play it safe and wait for qualified applicants named Matthew, Mark or Luke
View attachment 65769
supersonic001
Regular
BrainChip on LinkedIn: We're on a mission to revolutionize the AI landscape by building an…
We're on a mission to revolutionize the AI landscape by building an exceptional team to develop and evangelize our leading edge solutions. If you're passionate…
Considering we have links to all 4 of these companies I'd say it's a good chance
socionextus.com
C-DAC AUM Development | Socionext HPC Processor SoC AUM
Socionext will design, develop, and deliver a high-performance computing processor (SoC) in the TSMC 5nm technology node for C-DAC
socionextus.com
Bravo
If ARM was an arm, BRN would be its biceps💪!
Considering we have links to all 4 of these companies I'd say it's a good chance
View attachment 65777C-DAC AUM Development | Socionext HPC Processor SoC AUM
Socionext will design, develop, and deliver a high-performance computing processor (SoC) in the TSMC 5nm technology node for C-DAC
buena suerte :-)
BOB Bank of Brainchip
Morning Chippers....
Not seen this kind of buy/sell ratio for a loooong time!! Surely we have to be seeing 25c +++++ again soon!?
Not seen this kind of buy/sell ratio for a loooong time!! Surely we have to be seeing 25c +++++ again soon!?
Bravo
If ARM was an arm, BRN would be its biceps💪!
Here's an interesting read from an Arm article dated all the way back in July 2017.
I wonder if these applications are covered in PVDM's "Cortical Columns" research?
Linux System Administrator - Technical Operations
July 1, 2017
Imagine the world where paralysis is considered to be a short-term condition; where those suffering from Parkinson’s disease or other neurological conditions can be treated, and where people suffering nerve damage can feel the heat from a freshly made cup of tea, or the texture of the ground underneath their feet.
If the Centre for Sensorimotor Neural Engineering (CSNE) and ARM have their way, this world could be a reality in a decade’s time. Their partnership has led to the development of a unique “’brain-implantable’ system-on-a-chip (SoC) for bi-directional brain-computer interfaces (BBCI) aimed at solving neurodegenerative disorders.”
To date, CSNE has worked on projects connecting into the brain and nervous system but this venture represents the first time there has been any real attempt to work on the closed loop feedback system between the cortex of the brain and the spinal cord, Peter Ferguson, Director of Healthcare Technologies at ARM, explains over the phone from Seattle.
“They’re trying to read and understand the signals from the brain and understand infinite detail what’s going on and how it can be linked into the nervous system in this closed loop manner. That’s quite special.”
So why hasn’t this been tried before? As one would expect, implanting a chip into an individual’s brain brings with it a whole host of ethical and biological challenges.
“First, there’s the challenge of connecting electrical systems into the brain and nervous system without destroying the cells,” Ferguson outlines. “Then there’s the challenge of having the compute capacity to read the data, filter the signals digitally and process it all in a way that doesn’t overheat the electronics and cause them to impact on the brain itself.”
It’s that second challenge that made finding the right partner so fundamental to this entire project.
ARM is already a market leader, designing low powered chips which are then licensed and manufactured by other people to be used in 99% of mobile phones and smart devices. ARM’s credentials for this project were obvious however, the question remained: How can you migrate the ability to compute using mobile phones into something that can compute within your brain?
According to Ferguson, the answer appears to lie with ARM Cortex-M0 processor, a chip efficient enough to combine the low power ARM technology with a sensible frequency and voltage design whilst being small enough to enable the necessary level of embedded control within the brain.
Whilst the development of this ‘brain-implantable’ chip is still in its infancy of the 10-year timeline, technology and healthcare services have increasingly come together in an attempt to improve patient care.
“The increase in chronic conditions such as diabetes is putting a strain on health services around the world,” Ferguson explains. “However, we live in a world where people are so used to using their smart devices they’re starting to say ‘if it’s easy for me to do this [banking, shopping, checking in at the airport] then why is it so difficult to have mobile health services?’”
Ferguson makes it clear that this increasing shift towards digitising aspects of health care is no bad thing; with the emergence of smart devices and technologies such as patches that can be applied to the body to measure smells associated with cancer or listen to your chest to detect symptoms of asthma.
“There are patches appearing on the market that has machine-learning baked in that can act like a guardian angel. Why wait until you have an asthma attack happen when you can see the physiological signs showing you several hours early if an attack is likely to occur?”
Whilst the technology itself is undoubtedly exciting, the potential industry-wide benefits it could provide health care services with are just as groundbreaking. Take a phone case that doubles as an ECG monitor, for example. The data it can provide is fascinating but, not only can it be used to keep an eye on your health, it could pick up any abnormalities and uncover an undiagnosed condition that could have caused complications in later life.
“Reading your ECG is invaluable and the more powerful the compute models included in the technology, the more these devices can move from being data collectors into knowledge collectors; comparing your signals with what normal is or what normal was for you yesterday or what normal is for your height and weight. The more meaning you can gain from the data and the greater the context for the data when you present it to clinicians, the better they’ll be able to work out what’s going on and what medication is most appropriate for your health.
“All these technologies are coming out and whether it’s wearables or smart patches or ultimately implantable devices in the brain, we’re on a very exciting trajectory that will hopefully bring self-care to more people around the world.”
The future of healthcare and technology is clearly so intertwined, enquiring what the future could hold seems so impossibly open-ended it feels almost stupid to ask.
“The potential for this technology is multi-folded,” says Karthik Ranjan, Director of Healthcare and Emerging Technologies at ARM, who is also on the call. “While CSNE is primarily focused on neurological conditions, we’re already seeing the potential for this technology to be used to control the world around us by translating feelings into actions.”
Feeling too hot or too cold and automatically adjusting the thermostat, for example.
There are other opportunities too. Things like behaviour control is one that Ranjan singles out as having a great deal of potential. “Reducing things like alcoholism or tobacco and substance addictions by dampening the effect they have through accessing the neurons in our brain that are the receptors for them.”
ARM Holdings is based in Cambridge and with this thought in mind, Ranjan ends the conversation with a homage to Stephen Hawking.
“Although he uses a computer to communicate, he’s clearly still able to think. The opportunity is here, however; the question is how can we convert the thoughts we have and the words we want to speak into a neurological signal that can be digitised and transferred to other human beings?”
I wonder if these applications are covered in PVDM's "Cortical Columns" research?
Could an ARM brain chip end neurodegenerative diseases?
Raju Parsha
Linux System Administrator - Technical Operations
July 1, 2017
Imagine the world where paralysis is considered to be a short-term condition; where those suffering from Parkinson’s disease or other neurological conditions can be treated, and where people suffering nerve damage can feel the heat from a freshly made cup of tea, or the texture of the ground underneath their feet.
If the Centre for Sensorimotor Neural Engineering (CSNE) and ARM have their way, this world could be a reality in a decade’s time. Their partnership has led to the development of a unique “’brain-implantable’ system-on-a-chip (SoC) for bi-directional brain-computer interfaces (BBCI) aimed at solving neurodegenerative disorders.”
To date, CSNE has worked on projects connecting into the brain and nervous system but this venture represents the first time there has been any real attempt to work on the closed loop feedback system between the cortex of the brain and the spinal cord, Peter Ferguson, Director of Healthcare Technologies at ARM, explains over the phone from Seattle.
“They’re trying to read and understand the signals from the brain and understand infinite detail what’s going on and how it can be linked into the nervous system in this closed loop manner. That’s quite special.”
So why hasn’t this been tried before? As one would expect, implanting a chip into an individual’s brain brings with it a whole host of ethical and biological challenges.
“First, there’s the challenge of connecting electrical systems into the brain and nervous system without destroying the cells,” Ferguson outlines. “Then there’s the challenge of having the compute capacity to read the data, filter the signals digitally and process it all in a way that doesn’t overheat the electronics and cause them to impact on the brain itself.”
It’s that second challenge that made finding the right partner so fundamental to this entire project.
ARM is already a market leader, designing low powered chips which are then licensed and manufactured by other people to be used in 99% of mobile phones and smart devices. ARM’s credentials for this project were obvious however, the question remained: How can you migrate the ability to compute using mobile phones into something that can compute within your brain?
According to Ferguson, the answer appears to lie with ARM Cortex-M0 processor, a chip efficient enough to combine the low power ARM technology with a sensible frequency and voltage design whilst being small enough to enable the necessary level of embedded control within the brain.
Whilst the development of this ‘brain-implantable’ chip is still in its infancy of the 10-year timeline, technology and healthcare services have increasingly come together in an attempt to improve patient care.
“The increase in chronic conditions such as diabetes is putting a strain on health services around the world,” Ferguson explains. “However, we live in a world where people are so used to using their smart devices they’re starting to say ‘if it’s easy for me to do this [banking, shopping, checking in at the airport] then why is it so difficult to have mobile health services?’”
Ferguson makes it clear that this increasing shift towards digitising aspects of health care is no bad thing; with the emergence of smart devices and technologies such as patches that can be applied to the body to measure smells associated with cancer or listen to your chest to detect symptoms of asthma.
“There are patches appearing on the market that has machine-learning baked in that can act like a guardian angel. Why wait until you have an asthma attack happen when you can see the physiological signs showing you several hours early if an attack is likely to occur?”
Whilst the technology itself is undoubtedly exciting, the potential industry-wide benefits it could provide health care services with are just as groundbreaking. Take a phone case that doubles as an ECG monitor, for example. The data it can provide is fascinating but, not only can it be used to keep an eye on your health, it could pick up any abnormalities and uncover an undiagnosed condition that could have caused complications in later life.
“Reading your ECG is invaluable and the more powerful the compute models included in the technology, the more these devices can move from being data collectors into knowledge collectors; comparing your signals with what normal is or what normal was for you yesterday or what normal is for your height and weight. The more meaning you can gain from the data and the greater the context for the data when you present it to clinicians, the better they’ll be able to work out what’s going on and what medication is most appropriate for your health.
“All these technologies are coming out and whether it’s wearables or smart patches or ultimately implantable devices in the brain, we’re on a very exciting trajectory that will hopefully bring self-care to more people around the world.”
The future of healthcare and technology is clearly so intertwined, enquiring what the future could hold seems so impossibly open-ended it feels almost stupid to ask.
“The potential for this technology is multi-folded,” says Karthik Ranjan, Director of Healthcare and Emerging Technologies at ARM, who is also on the call. “While CSNE is primarily focused on neurological conditions, we’re already seeing the potential for this technology to be used to control the world around us by translating feelings into actions.”
Feeling too hot or too cold and automatically adjusting the thermostat, for example.
There are other opportunities too. Things like behaviour control is one that Ranjan singles out as having a great deal of potential. “Reducing things like alcoholism or tobacco and substance addictions by dampening the effect they have through accessing the neurons in our brain that are the receptors for them.”
ARM Holdings is based in Cambridge and with this thought in mind, Ranjan ends the conversation with a homage to Stephen Hawking.
“Although he uses a computer to communicate, he’s clearly still able to think. The opportunity is here, however; the question is how can we convert the thoughts we have and the words we want to speak into a neurological signal that can be digitised and transferred to other human beings?”
Here's an interesting read from an Arm article dated all the way back in July 2017.
I wonder if these applications are covered in PVDM's "Cortical Columns" research?
Could an ARM brain chip end neurodegenerative diseases?
Raju Parsha
Linux System Administrator - Technical Operations
July 1, 2017
Imagine the world where paralysis is considered to be a short-term condition; where those suffering from Parkinson’s disease or other neurological conditions can be treated, and where people suffering nerve damage can feel the heat from a freshly made cup of tea, or the texture of the ground underneath their feet.
If the Centre for Sensorimotor Neural Engineering (CSNE) and ARM have their way, this world could be a reality in a decade’s time. Their partnership has led to the development of a unique “’brain-implantable’ system-on-a-chip (SoC) for bi-directional brain-computer interfaces (BBCI) aimed at solving neurodegenerative disorders.”
To date, CSNE has worked on projects connecting into the brain and nervous system but this venture represents the first time there has been any real attempt to work on the closed loop feedback system between the cortex of the brain and the spinal cord, Peter Ferguson, Director of Healthcare Technologies at ARM, explains over the phone from Seattle.
“They’re trying to read and understand the signals from the brain and understand infinite detail what’s going on and how it can be linked into the nervous system in this closed loop manner. That’s quite special.”
So why hasn’t this been tried before? As one would expect, implanting a chip into an individual’s brain brings with it a whole host of ethical and biological challenges.
“First, there’s the challenge of connecting electrical systems into the brain and nervous system without destroying the cells,” Ferguson outlines. “Then there’s the challenge of having the compute capacity to read the data, filter the signals digitally and process it all in a way that doesn’t overheat the electronics and cause them to impact on the brain itself.”
It’s that second challenge that made finding the right partner so fundamental to this entire project.
ARM is already a market leader, designing low powered chips which are then licensed and manufactured by other people to be used in 99% of mobile phones and smart devices. ARM’s credentials for this project were obvious however, the question remained: How can you migrate the ability to compute using mobile phones into something that can compute within your brain?
According to Ferguson, the answer appears to lie with ARM Cortex-M0 processor, a chip efficient enough to combine the low power ARM technology with a sensible frequency and voltage design whilst being small enough to enable the necessary level of embedded control within the brain.
Whilst the development of this ‘brain-implantable’ chip is still in its infancy of the 10-year timeline, technology and healthcare services have increasingly come together in an attempt to improve patient care.
“The increase in chronic conditions such as diabetes is putting a strain on health services around the world,” Ferguson explains. “However, we live in a world where people are so used to using their smart devices they’re starting to say ‘if it’s easy for me to do this [banking, shopping, checking in at the airport] then why is it so difficult to have mobile health services?’”
Ferguson makes it clear that this increasing shift towards digitising aspects of health care is no bad thing; with the emergence of smart devices and technologies such as patches that can be applied to the body to measure smells associated with cancer or listen to your chest to detect symptoms of asthma.
“There are patches appearing on the market that has machine-learning baked in that can act like a guardian angel. Why wait until you have an asthma attack happen when you can see the physiological signs showing you several hours early if an attack is likely to occur?”
Whilst the technology itself is undoubtedly exciting, the potential industry-wide benefits it could provide health care services with are just as groundbreaking. Take a phone case that doubles as an ECG monitor, for example. The data it can provide is fascinating but, not only can it be used to keep an eye on your health, it could pick up any abnormalities and uncover an undiagnosed condition that could have caused complications in later life.
“Reading your ECG is invaluable and the more powerful the compute models included in the technology, the more these devices can move from being data collectors into knowledge collectors; comparing your signals with what normal is or what normal was for you yesterday or what normal is for your height and weight. The more meaning you can gain from the data and the greater the context for the data when you present it to clinicians, the better they’ll be able to work out what’s going on and what medication is most appropriate for your health.
“All these technologies are coming out and whether it’s wearables or smart patches or ultimately implantable devices in the brain, we’re on a very exciting trajectory that will hopefully bring self-care to more people around the world.”
The future of healthcare and technology is clearly so intertwined, enquiring what the future could hold seems so impossibly open-ended it feels almost stupid to ask.
“The potential for this technology is multi-folded,” says Karthik Ranjan, Director of Healthcare and Emerging Technologies at ARM, who is also on the call. “While CSNE is primarily focused on neurological conditions, we’re already seeing the potential for this technology to be used to control the world around us by translating feelings into actions.”
Feeling too hot or too cold and automatically adjusting the thermostat, for example.
There are other opportunities too. Things like behaviour control is one that Ranjan singles out as having a great deal of potential. “Reducing things like alcoholism or tobacco and substance addictions by dampening the effect they have through accessing the neurons in our brain that are the receptors for them.”
ARM Holdings is based in Cambridge and with this thought in mind, Ranjan ends the conversation with a homage to Stephen Hawking.
“Although he uses a computer to communicate, he’s clearly still able to think. The opportunity is here, however; the question is how can we convert the thoughts we have and the words we want to speak into a neurological signal that can be digitised and transferred to other human beings?”
Everyone is asking if akida is inside any product…. What they never questioned is …. IS AKIDA INSIDE AKIDA????? BaaaaaaAAAAM!!!
Bravo
If ARM was an arm, BRN would be its biceps💪!
Wow! That's really deep!
What about this for a saying?.. "I think, therefore I am AKIDA".
Oooops! I think I should have stopped at the one bowl full of Ayahuasca tea...
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DMT… a insider in da houseWow! That's really deep!
What about this for a saying?.. "I think, therefore I am AKIDA".
Oooops! I think I should have stopped at the one bowl full of Ayahuasca tea...
View attachment 65786
Bravo
If ARM was an arm, BRN would be its biceps💪!
STMicroelectronics in the news today. Remember when Rob Telson "liked" an EETimes article on STM32N6 MCUs back in March 2023 (see below post from @Sirod69).
ByELE Times Report
July 1, 2024
cs, a global semiconductor leader serving customers across the spectrum of electronics applications, today announced the availability of ST Edge AI Suite, bringing together tools, software and knowledge to simplify and accelerate building edge-AI applications.
The ST Edge AI Suite is an integrated collection of software tools, designed to facilitate the development and deployment of embedded AI applications. This comprehensive suite supports both optimization and deployment of machine-learning algorithms, starting from data collection to final deployment on hardware, streamlining the workflow for different types of users.
The tools from the suite are covering a broad range of ST products, from smart sensors to microcontrollers and microprocessors including upcoming STM32N6 neural-processing microcontrollers.
“ST Edge AI Suite is the new starting point on st.com for embedded AI development. Here, today’s innovators, driven by imagination, can find help to realize tomorrow’s smart things that sense, infer, and respond intelligently, autonomously, and efficiently to the world around,” said Alessandro Cremonesi, Executive Vice President, Chief Innovation Officer and General Manager of STMicroelectronics’ System Research and Applications Group. “This environment brings developers simplicity through an easy choice of models and data sources, finding the right tools quickly and easily, optimizing and benchmarking, then automatically generating code and libraries – all within one unified framework.”
While working across multiple hardware platforms, ST Edge AI Suite meets the needs of different types of users such as data scientists, embedded software developers, and hardware system engineers.
There is seamless access to online tools such as the ST Edge AI Model Zoo and Developer Cloud, as well as desktop tools for data tuning and model optimization on the chosen hardware platform. These include NanoEdge AI Studio for generating machine learning libraries automatically, and STM32Cube.AI, MEMS Studio, and Stellar Studio, for model optimization on STM32 devices, MEMS inertial sensors, and Stellar processors. All are ready to use free of charge.
The release of this suite is also an opportunity to introduce world-first innovations for AI applications in the MEMS Studio tool: the “ISPU NN model optimizer” and “automatic selection of MLC features and filters.”
Lead customers’ experiences:
Honeywell, Soxai, and HPE Group explain how tools such as MEMS Studio and Stellar Studio in the ST Edge AI Suite help simplify and accelerate edge-AI development.
Israel Herrera, Firmware Architect & Embedded Systems Engineer, Honeywell Fire, commented, “We recognize the innovative strides ST has made in the realm of edge computing with their sensors. MEMS Studio, as featured in the ST Edge AI Suite, has proved to be a great software development tool to help us perform quick tests using multiple MEMS sensor modules from ST. It enables us to create proof of concepts easily through its code generation feature. MEMS Studio is also very useful in testing different and independent Machine Learning and Data Analysis algorithms.”
Tatsuhiko Watanabe, CEO & Founder of SOXAI, which is using ST’s edge-AI sensors, said, “While we were developing SOXAI RING 1, ST introduced the world’s first sensor with edge AI, and we quickly adopted it to boost our product’s performance. The machine-learning core software tool featured in the ST Edge AI Suite helped us quickly integrate this new technology and allowed our developers to harness the full potential of the sensor with minimal effort. Compared to the first generation, our new SOXAI RING 1 now boasts an extended battery life of at least 10 hours, a game-changer in the world of wearable technology.”
Andrea Bozzoli, CEO of HPE Group, added, “HPE is at the forefront of transforming the automotive sector through our collaboration with STMicroelectronics and their Stellar MCU and Stellar Studio software, which is part of the ST Edge AI Suite. Our Prometeo Joint Innovation Lab efforts are set to deliver a proof-of-concept for next-generation vehicle powertrains, leveraging AI to enhance predictive maintenance and control systems. This synergy will not only elevate electric vehicle performance but also enrich the digital cockpit experience, setting a new standard for smart, sustainable mobility.“
www.eletimes.com
ST Edge AI Suite goes live, accelerating AI-enabled product development with STMicroelectronics’ technologies
ByELE Times Report
July 1, 2024
cs, a global semiconductor leader serving customers across the spectrum of electronics applications, today announced the availability of ST Edge AI Suite, bringing together tools, software and knowledge to simplify and accelerate building edge-AI applications.
The ST Edge AI Suite is an integrated collection of software tools, designed to facilitate the development and deployment of embedded AI applications. This comprehensive suite supports both optimization and deployment of machine-learning algorithms, starting from data collection to final deployment on hardware, streamlining the workflow for different types of users.
The tools from the suite are covering a broad range of ST products, from smart sensors to microcontrollers and microprocessors including upcoming STM32N6 neural-processing microcontrollers.
“ST Edge AI Suite is the new starting point on st.com for embedded AI development. Here, today’s innovators, driven by imagination, can find help to realize tomorrow’s smart things that sense, infer, and respond intelligently, autonomously, and efficiently to the world around,” said Alessandro Cremonesi, Executive Vice President, Chief Innovation Officer and General Manager of STMicroelectronics’ System Research and Applications Group. “This environment brings developers simplicity through an easy choice of models and data sources, finding the right tools quickly and easily, optimizing and benchmarking, then automatically generating code and libraries – all within one unified framework.”
While working across multiple hardware platforms, ST Edge AI Suite meets the needs of different types of users such as data scientists, embedded software developers, and hardware system engineers.
There is seamless access to online tools such as the ST Edge AI Model Zoo and Developer Cloud, as well as desktop tools for data tuning and model optimization on the chosen hardware platform. These include NanoEdge AI Studio for generating machine learning libraries automatically, and STM32Cube.AI, MEMS Studio, and Stellar Studio, for model optimization on STM32 devices, MEMS inertial sensors, and Stellar processors. All are ready to use free of charge.
The release of this suite is also an opportunity to introduce world-first innovations for AI applications in the MEMS Studio tool: the “ISPU NN model optimizer” and “automatic selection of MLC features and filters.”
Lead customers’ experiences:
Honeywell, Soxai, and HPE Group explain how tools such as MEMS Studio and Stellar Studio in the ST Edge AI Suite help simplify and accelerate edge-AI development.
Israel Herrera, Firmware Architect & Embedded Systems Engineer, Honeywell Fire, commented, “We recognize the innovative strides ST has made in the realm of edge computing with their sensors. MEMS Studio, as featured in the ST Edge AI Suite, has proved to be a great software development tool to help us perform quick tests using multiple MEMS sensor modules from ST. It enables us to create proof of concepts easily through its code generation feature. MEMS Studio is also very useful in testing different and independent Machine Learning and Data Analysis algorithms.”
Tatsuhiko Watanabe, CEO & Founder of SOXAI, which is using ST’s edge-AI sensors, said, “While we were developing SOXAI RING 1, ST introduced the world’s first sensor with edge AI, and we quickly adopted it to boost our product’s performance. The machine-learning core software tool featured in the ST Edge AI Suite helped us quickly integrate this new technology and allowed our developers to harness the full potential of the sensor with minimal effort. Compared to the first generation, our new SOXAI RING 1 now boasts an extended battery life of at least 10 hours, a game-changer in the world of wearable technology.”
Andrea Bozzoli, CEO of HPE Group, added, “HPE is at the forefront of transforming the automotive sector through our collaboration with STMicroelectronics and their Stellar MCU and Stellar Studio software, which is part of the ST Edge AI Suite. Our Prometeo Joint Innovation Lab efforts are set to deliver a proof-of-concept for next-generation vehicle powertrains, leveraging AI to enhance predictive maintenance and control systems. This synergy will not only elevate electric vehicle performance but also enrich the digital cockpit experience, setting a new standard for smart, sustainable mobility.“
ST Edge AI Suite goes live, accelerating AI-enabled product development with STMicroelectronics’ technologies
The ST Edge AI Suite is an integrated collection of software tools, designed to facilitate the development and deployment of embedded AI applications.
www.eletimes.com
MDhere
Regular
Happy new fin year fellow brners
Apologies if already posted i've been a little behind in reading . This came out 7 days ago.
Tata Elxsi 35th Integrated Report 2023-24 Page 6
Healthcare and Life Sciences Projects, Alliances and Collaborations Partnership with BrainChip for driving Akida technology into medical devices and industrial applications leveraging its superior AI performance on the edge
Apologies if already posted i've been a little behind in reading . This came out 7 days ago.
Tata Elxsi 35th Integrated Report 2023-24 Page 6
Healthcare and Life Sciences Projects, Alliances and Collaborations Partnership with BrainChip for driving Akida technology into medical devices and industrial applications leveraging its superior AI performance on the edge
Hi Bravo,STMicroelectronics in the news today. Remember when Rob Telson "liked" an EETimes article on STM32N6 MCUs back in March 2023 (see below post from @Sirod69).
ST Edge AI Suite goes live, accelerating AI-enabled product development with STMicroelectronics’ technologies
ByELE Times Report
July 1, 2024
cs, a global semiconductor leader serving customers across the spectrum of electronics applications, today announced the availability of ST Edge AI Suite, bringing together tools, software and knowledge to simplify and accelerate building edge-AI applications.
The ST Edge AI Suite is an integrated collection of software tools, designed to facilitate the development and deployment of embedded AI applications. This comprehensive suite supports both optimization and deployment of machine-learning algorithms, starting from data collection to final deployment on hardware, streamlining the workflow for different types of users.
The tools from the suite are covering a broad range of ST products, from smart sensors to microcontrollers and microprocessors including upcoming STM32N6 neural-processing microcontrollers.
“ST Edge AI Suite is the new starting point on st.com for embedded AI development. Here, today’s innovators, driven by imagination, can find help to realize tomorrow’s smart things that sense, infer, and respond intelligently, autonomously, and efficiently to the world around,” said Alessandro Cremonesi, Executive Vice President, Chief Innovation Officer and General Manager of STMicroelectronics’ System Research and Applications Group. “This environment brings developers simplicity through an easy choice of models and data sources, finding the right tools quickly and easily, optimizing and benchmarking, then automatically generating code and libraries – all within one unified framework.”
While working across multiple hardware platforms, ST Edge AI Suite meets the needs of different types of users such as data scientists, embedded software developers, and hardware system engineers.
There is seamless access to online tools such as the ST Edge AI Model Zoo and Developer Cloud, as well as desktop tools for data tuning and model optimization on the chosen hardware platform. These include NanoEdge AI Studio for generating machine learning libraries automatically, and STM32Cube.AI, MEMS Studio, and Stellar Studio, for model optimization on STM32 devices, MEMS inertial sensors, and Stellar processors. All are ready to use free of charge.
The release of this suite is also an opportunity to introduce world-first innovations for AI applications in the MEMS Studio tool: the “ISPU NN model optimizer” and “automatic selection of MLC features and filters.”
Lead customers’ experiences:
Honeywell, Soxai, and HPE Group explain how tools such as MEMS Studio and Stellar Studio in the ST Edge AI Suite help simplify and accelerate edge-AI development.
Israel Herrera, Firmware Architect & Embedded Systems Engineer, Honeywell Fire, commented, “We recognize the innovative strides ST has made in the realm of edge computing with their sensors. MEMS Studio, as featured in the ST Edge AI Suite, has proved to be a great software development tool to help us perform quick tests using multiple MEMS sensor modules from ST. It enables us to create proof of concepts easily through its code generation feature. MEMS Studio is also very useful in testing different and independent Machine Learning and Data Analysis algorithms.”
Tatsuhiko Watanabe, CEO & Founder of SOXAI, which is using ST’s edge-AI sensors, said, “While we were developing SOXAI RING 1, ST introduced the world’s first sensor with edge AI, and we quickly adopted it to boost our product’s performance. The machine-learning core software tool featured in the ST Edge AI Suite helped us quickly integrate this new technology and allowed our developers to harness the full potential of the sensor with minimal effort. Compared to the first generation, our new SOXAI RING 1 now boasts an extended battery life of at least 10 hours, a game-changer in the world of wearable technology.”
Andrea Bozzoli, CEO of HPE Group, added, “HPE is at the forefront of transforming the automotive sector through our collaboration with STMicroelectronics and their Stellar MCU and Stellar Studio software, which is part of the ST Edge AI Suite. Our Prometeo Joint Innovation Lab efforts are set to deliver a proof-of-concept for next-generation vehicle powertrains, leveraging AI to enhance predictive maintenance and control systems. This synergy will not only elevate electric vehicle performance but also enrich the digital cockpit experience, setting a new standard for smart, sustainable mobility.“
ST Edge AI Suite goes live, accelerating AI-enabled product development with STMicroelectronics’ technologies
The ST Edge AI Suite is an integrated collection of software tools, designed to facilitate the development and deployment of embedded AI applications.
View attachment 65788
STMicroelectronics are long on MACs and analog:
US2024212751A1 IN-MEMORY COMPUTATION DEVICE HAVING AN IMPROVED CURRENT READING CIRCUIT AND CONTROL METHOD 20221223
A word line activation unit of an in-memory computation generates activation signals as a function of an input value. The in-memory computation device includes a memory array with a plurality of memory cells (each storing a computational weight) coupled to a bit line and each to a word line and a digital detector. A cell current flows through each memory cell as a function of the activation signal and the computational weight and a bit line current is generated as a function of a summation of the cell currents. The digital detector performs successive iterations on the bit line current. In each iteration: an integration stage generates an integration signal indicative of a time integral of the bit line current, and resets the integration signal when the integration signal reaches a threshold; and the counter stage updates the output signal in response to the integration signal reaching the threshold.
CN117667013A Computing unit for multiplication and accumulation operations 20230821
The invention relates to a computing unit for multiplication and accumulation operations. A device includes a multiplier, an accumulator, and a floating point adder. The multiplier generates a product of a first factor having sign bits and exponent bits and a second factor having sign bits and exponent bits. The multiplier comprises a symbol multiplier and a subtractor. A sign multiplier generates a product of sign bits of a first factor and sign bits of a second factor. The subtractor subtracts the exponent bit of the first factor from the exponent bit of the second factor. The accumulator stores the current accumulated value. The floating point adder is coupled to the multiplier and the accumulator, and in operation, the adder generates an updated accumulated value based on a sum of the product and the current accumulated value and stores the updated accumulated value in the accumulator. The first factor may be a weight of the neural network.
CN117809716A Analog in-memory computing processing circuitry using segmented memory architecture 20230928
The invention relates to analog in-memory computing processing circuitry using a segmented memory architecture. A memory array includes a sub-array having memory cells arranged in a matrix of rows and columns, wherein each row includes word lines and each sub-array column includes local bit lines. The control circuit supports a first mode of operation in which only one word line in the memory array is actuated during memory access, and a second mode of operation in which only one word line is activated during memory access. One word line of each sub-array is simultaneously actuated during in-memory computations performed according to weight data stored in the memory and applied feature data in a second mode of operation. Computing circuitry coupling each memory cell to a local bit line of each column of the sub-array logically combines bits of feature data for in-memory computation with bits of weight data to generate a logical output on the local bit line sharing charge with the global bit line.
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