Rise from the ashes
Regular
Monitoring Vital Signs with Radars and AI, Not Wires
Stevens works with Autonomous Healthcare to develop NASA-supported technology that monitors heartbeat and breathing with radar, cameras and algorithms
BRN Discussion Ongoing
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Rise from the ashes
Regular
I've got some btc dust left in a few wallets from years back from buying shit coins worth a few K now.
What do they produce?
D
Deleted member 118
Guest
Hopefully enough cash in a week or 2 to get more BrN, unless it shits itself further
Bravo
If ARM was an arm, BRN would be its biceps💪!
Inflammation
minus the "amm".
DingoBorat
Slim
I‘m with you on that FF
Dream gig just changing some font and a few colours
Rise from the ashes
Regular
I seriously believe btc will hit a few hundred K in years to come
robsmark
Regular
No risk no reward.I can never save up big parcels as I'm too scared to be left with my pants down.. I refuse to be on the bus with my suitcase left on the side of the road. I can't be the only one
Bravo
If ARM was an arm, BRN would be its biceps💪!
This article was written in 2017. I love the title! Hehehe! Makes you appreciate how far BrainChip has come. You know, I can't help but think that we'll get an announcement from Qualcomm sometime in the near future, especially in light of the following statement.
"Qualcomm is also a player in neuromorphic designs, but seems to have cooled on the technology – publicly, at least. Back in 2013, it was working on processors called Zeroth, but has since morphed the Zeroth project into a software-based proposition that will find its way into the core Snapdragon system-on-chip offerings – as a software code stack, rather than as a standalone processor."
Akida is a perfect match for the next generation of the Snapdragon Cockpit (digital cockpit and infotainment system). Please Qualcomm, just spill the beans already!
18 October 2017
By Caroline Gabriel
Intel has announced its first self-learning neuromorphic chip, named Loihi, which it says will get smarter over time and enable extremely power efficient designs. This follows IBM’s work on neuromorphic processors, which draw inspiration from the human brain, and are poised to heavily disrupt any application that needs processing power in a mobile device.
Following the Loihi announcement, Intel also unveiled a new quantum computing chip, in collaboration with QuTech (a Dutch company that scored $50m of Intel investment in 2015), which was developed over the past 18 months. That’s a very different proposition from the machine learning elements in Loihi, but Intel is pouring money into its R&D divisions, hoping to keep its processors ahead of the curve and fend off incursions by alternative architectures such as ARM (Qualcomm also has a ‘brain chip’), or Nvidia’s GPUs (graphics processing units).
Intel is far from the only neuromorphic player. IBM and its TrueNorth processors are the most advanced platform on the market, with IBM already having contracts with laboratories in the USA, including the Lawrence Livermore National Lab, which is using it to run simulations to evaluate the safety of the US nuclear arsenal. IBM also has a development partnership with Samsung, which sees the Korean firm use IBM’s newer SyNAPSE design in its Dynamic Vision Sensor – which provides a 2,000-frames per second view of the world in a 300mW power package.
Qualcomm is also a player in neuromorphic designs, but seems to have cooled on the technology – publicly, at least. Back in 2013, it was working on processors called Zeroth, but has since morphed the Zeroth project into a software-based proposition that will find its way into the core Snapdragon system-on-chip offerings – as a software code stack, rather than as a standalone processor.
The promise of neuromorphic chips is their potential for incredible power efficiency. The human brain is an incredibly efficient processing engine, and chips built to mimic its design appear to reap the rewards. Intel claims Loihi is about 1,000 times more energy efficient than the general purpose processor needed to train the neural networks that rival Loihi’s performance.
In theory, this means that chips like Loihi can be far more quickly turned to tasks that use pattern recognition and intuition, which currently rely on vast banks of CPUs and GPUs to achieve results. One chip could replace all the hard work of a traditional machine learning instance, as well as powering a device out in the wild that can carry out advanced pattern recognition – thanks to having both training and inference on the same silicon.
Intel says that this dual system will allow for machines to operate independently of a cloud connection, and says that its researchers have demonstrated a learning rate that boasts one million times improvement over typical spiking neural networks in finger/digit recognition problems. Intel says this is far more efficient than using convolutional neural networks (CNNs) or deep learning neural networks (DLNNs).
“The brain’s neural networks relay information with pulses or spikes, modulate the synaptic strengths or weight of the interconnections based on timing of these spikes, and store these changes locally at the interconnections. Intelligent behaviors emerge from the cooperative and competitive interactions between multiple regions within the brain’s neural networks and its environment,” explained Michael Mayberry, MD of Intel Labs.
The reason Intel in particular is so keen on being at the heart of these new brain chips is their ability to generalize – something that the current model of training doesn’t do well. Currently, a machine learning process could be trained to identify cats expertly, but it would be awful at spotting dogs, even though they share many characteristics. This is because the training data set and model would not account for dogs, and so a completely different model would be needed for that purpose.
With a chip that can self-learn without the need for the new training data set, it should be far easier to tweak the system to spot smaller generalized differences in data or events.
Intel points to a system for monitoring a person’s heartbeat, taking readings after events such as exercise or eating, and using the neuromorphic chip to normalize the data and work out the ‘normal’ heartbeat. It can then spot abnormalities, but also deal with any new events or conditions that the user is subject to – without having to create a training data set to cover all bases. It should provide shorter development time, and better performance in the wild. Again, these are the promises – we’re still a long way from benchmarking these claims in real world situations.
Loihi will be released to research institutions and universities in the first half of 2018. They will get to test its fully asynchronous neuromorphic many-core mesh – a design that Intel says supports a wide range of neural network topologies, and allows each neuron to communicate with the other on-chip neurons (hence mesh). Each of the neuromorphic cores has a programmable learning engine, which the developers can use to adapt the neural network parameters, to support the different ‘learning paradigms’ – supervised, unsupervised, and reinforcement, mainly.
The first iteration of the Loihi chip was made using Intel’s 14nm fabrication process, and houses 1,024 artificial neurons that provide 130,000 simulated neurons – giving it 130m synapses, which is still a rather long way from the human brain’s 80bn synapses, and behind IBM’s TrueNorth, which has around 256m but using 4,096 cores. It seems Intel is getting more synapses with fewer cores, but there’s no practical way of benchmarking the two chips as yet.
As the neurons spike and communicate with other neurons, and as they process information, the inter-neuron connections are strengthened – which leads to improved performance (the learning element). That learning takes place on the chip, and doesn’t require the enormous data sets, but still requires knowing what the question is, and how to gauge a correct answer.
rethinkresearch.biz
"Qualcomm is also a player in neuromorphic designs, but seems to have cooled on the technology – publicly, at least. Back in 2013, it was working on processors called Zeroth, but has since morphed the Zeroth project into a software-based proposition that will find its way into the core Snapdragon system-on-chip offerings – as a software code stack, rather than as a standalone processor."
Akida is a perfect match for the next generation of the Snapdragon Cockpit (digital cockpit and infotainment system). Please Qualcomm, just spill the beans already!
18 October 2017
Intel joins IBM and Qualcomm in race for a ‘brain chip’
By Caroline Gabriel
Intel has announced its first self-learning neuromorphic chip, named Loihi, which it says will get smarter over time and enable extremely power efficient designs. This follows IBM’s work on neuromorphic processors, which draw inspiration from the human brain, and are poised to heavily disrupt any application that needs processing power in a mobile device.
Following the Loihi announcement, Intel also unveiled a new quantum computing chip, in collaboration with QuTech (a Dutch company that scored $50m of Intel investment in 2015), which was developed over the past 18 months. That’s a very different proposition from the machine learning elements in Loihi, but Intel is pouring money into its R&D divisions, hoping to keep its processors ahead of the curve and fend off incursions by alternative architectures such as ARM (Qualcomm also has a ‘brain chip’), or Nvidia’s GPUs (graphics processing units).
Intel is far from the only neuromorphic player. IBM and its TrueNorth processors are the most advanced platform on the market, with IBM already having contracts with laboratories in the USA, including the Lawrence Livermore National Lab, which is using it to run simulations to evaluate the safety of the US nuclear arsenal. IBM also has a development partnership with Samsung, which sees the Korean firm use IBM’s newer SyNAPSE design in its Dynamic Vision Sensor – which provides a 2,000-frames per second view of the world in a 300mW power package.
Qualcomm is also a player in neuromorphic designs, but seems to have cooled on the technology – publicly, at least. Back in 2013, it was working on processors called Zeroth, but has since morphed the Zeroth project into a software-based proposition that will find its way into the core Snapdragon system-on-chip offerings – as a software code stack, rather than as a standalone processor.
The promise of neuromorphic chips is their potential for incredible power efficiency. The human brain is an incredibly efficient processing engine, and chips built to mimic its design appear to reap the rewards. Intel claims Loihi is about 1,000 times more energy efficient than the general purpose processor needed to train the neural networks that rival Loihi’s performance.
In theory, this means that chips like Loihi can be far more quickly turned to tasks that use pattern recognition and intuition, which currently rely on vast banks of CPUs and GPUs to achieve results. One chip could replace all the hard work of a traditional machine learning instance, as well as powering a device out in the wild that can carry out advanced pattern recognition – thanks to having both training and inference on the same silicon.
Intel says that this dual system will allow for machines to operate independently of a cloud connection, and says that its researchers have demonstrated a learning rate that boasts one million times improvement over typical spiking neural networks in finger/digit recognition problems. Intel says this is far more efficient than using convolutional neural networks (CNNs) or deep learning neural networks (DLNNs).
“The brain’s neural networks relay information with pulses or spikes, modulate the synaptic strengths or weight of the interconnections based on timing of these spikes, and store these changes locally at the interconnections. Intelligent behaviors emerge from the cooperative and competitive interactions between multiple regions within the brain’s neural networks and its environment,” explained Michael Mayberry, MD of Intel Labs.
The reason Intel in particular is so keen on being at the heart of these new brain chips is their ability to generalize – something that the current model of training doesn’t do well. Currently, a machine learning process could be trained to identify cats expertly, but it would be awful at spotting dogs, even though they share many characteristics. This is because the training data set and model would not account for dogs, and so a completely different model would be needed for that purpose.
With a chip that can self-learn without the need for the new training data set, it should be far easier to tweak the system to spot smaller generalized differences in data or events.
Intel points to a system for monitoring a person’s heartbeat, taking readings after events such as exercise or eating, and using the neuromorphic chip to normalize the data and work out the ‘normal’ heartbeat. It can then spot abnormalities, but also deal with any new events or conditions that the user is subject to – without having to create a training data set to cover all bases. It should provide shorter development time, and better performance in the wild. Again, these are the promises – we’re still a long way from benchmarking these claims in real world situations.
Loihi will be released to research institutions and universities in the first half of 2018. They will get to test its fully asynchronous neuromorphic many-core mesh – a design that Intel says supports a wide range of neural network topologies, and allows each neuron to communicate with the other on-chip neurons (hence mesh). Each of the neuromorphic cores has a programmable learning engine, which the developers can use to adapt the neural network parameters, to support the different ‘learning paradigms’ – supervised, unsupervised, and reinforcement, mainly.
The first iteration of the Loihi chip was made using Intel’s 14nm fabrication process, and houses 1,024 artificial neurons that provide 130,000 simulated neurons – giving it 130m synapses, which is still a rather long way from the human brain’s 80bn synapses, and behind IBM’s TrueNorth, which has around 256m but using 4,096 cores. It seems Intel is getting more synapses with fewer cores, but there’s no practical way of benchmarking the two chips as yet.
As the neurons spike and communicate with other neurons, and as they process information, the inter-neuron connections are strengthened – which leads to improved performance (the learning element). That learning takes place on the chip, and doesn’t require the enormous data sets, but still requires knowing what the question is, and how to gauge a correct answer.
Intel joins IBM and Qualcomm in race for a ‘brain chip’ - Rethink
Intel has announced its first self-learning neuromorphic chip, named Loihi, which it says will get smarter over time and enable extremely power efficient designs. This follows IBM’s work on neuromorphic processors, which draw inspiration from the human brain, and are poised to heavily disrupt...
Proga
Regular
True. It hasn't helped the SP in the short term but BRN's main problem is there isn't a lot of understanding and capability when it comes to Edge AI development which the current global problems didn't cause. The good news is this is rapidly improving with a lot of partnering and cross pollination within the ecosystem which won't be slowed down by the current global problems.
Almost there.
Taproot
Regular
RFTA,
Yes, you are quite right.
Ibeo created SCALA.
With the ScaLa SOP in 2016 Ibeo is the first company worldwide, who has developed a mass-market automotive LIDAR sensor. The ScaLa sensor was designed for the customer Audi.
In this paper we evaluate the use of a laser scanner for future advanced driver assistance systems. We focus on the important task of predicting the target vehicle for longitudinal ego vehicle control. Our motivation is to decrease the reaction time of existing systems during cut-in maneuvers of other traffic participants. A state-of-the-art laser scanner, the Ibeo Scala B2 R , is presented, providing its sensing characteristics and the subsequent high level object data output.
Valeo Leads Deployment And Industrialization Of Automotive LiDAR
The business of LiDAR is poised to transition from hype, speculation and technology roadmaps into products, revenues and execution. A critical success factor is the ability to meet the demanding requirements of automotive deployment. Valeo is leading this effort.
www.forbes.com
Valeo and Ibeo to cooperate on automotive laser scanner technology
Valeo has signed a cooperation, development and license agreement with Ibeo Automotive Systems GmbH in the field of laser scanner technology. This agreement gives Valeo exclusive access to Ibeo’s expertise and know-how and enables it to evolve Ibeo’s laser scanner technology for high-volume...
www.greencarcongress.com
This agreement gives Valeo exclusive access to Ibeo’s expertise and know-how and enables it to evolve Ibeo’s laser scanner technology for high-volume applications. This technology complements Valeo’s own range of radar, ultrasonic, infrared and vision sensor systems. With the laser scanner, Valeo will be able to promote innovative active safety features in this area.
supersonic001
Regular
Ooh Anastasia, you had me at grey matter ….
Rise from the ashes
Regular
G'day mate yes already read that stuff in my researchingRFTA,
Yes, you are quite right.
Ibeo created SCALA.
With the ScaLa SOP in 2016 Ibeo is the first company worldwide, who has developed a mass-market automotive LIDAR sensor. The ScaLa sensor was designed for the customer Audi.
In this paper we evaluate the use of a laser scanner for future advanced driver assistance systems. We focus on the important task of predicting the target vehicle for longitudinal ego vehicle control. Our motivation is to decrease the reaction time of existing systems during cut-in maneuvers of other traffic participants. A state-of-the-art laser scanner, the Ibeo Scala B2 R , is presented, providing its sensing characteristics and the subsequent high level object data output.
Valeo is by far the most advanced company today in terms of industrialization, maturity, testing, reliability and manufacturing scalability of an automotive LiDAR product for ADAS, and eventually for AVs. The SCALA® design was initiated with a cooperation, development and licensing agreement with Ibeo in 2010. Valeo invested in maturing the initial design platform into the launch of the fully qualified second generation SCALA® product in 2021. More than 150,000 units have been sold to date.Valeo Leads Deployment And Industrialization Of Automotive LiDAR
The business of LiDAR is poised to transition from hype, speculation and technology roadmaps into products, revenues and execution. A critical success factor is the ability to meet the demanding requirements of automotive deployment. Valeo is leading this effort.
Valeo has signed a cooperation, development and license agreement with Ibeo Automotive Systems GmbH in the field of laser scanner technology.Valeo and Ibeo to cooperate on automotive laser scanner technology
Valeo has signed a cooperation, development and license agreement with Ibeo Automotive Systems GmbH in the field of laser scanner technology. This agreement gives Valeo exclusive access to Ibeo’s expertise and know-how and enables it to evolve Ibeo’s laser scanner technology for high-volume...www.greencarcongress.com
This agreement gives Valeo exclusive access to Ibeo’s expertise and know-how and enables it to evolve Ibeo’s laser scanner technology for high-volume applications. This technology complements Valeo’s own range of radar, ultrasonic, infrared and vision sensor systems. With the laser scanner, Valeo will be able to promote innovative active safety features in this area.
amazing company with links to zf
Taproot
Regular
FYI,RFTA,
Yes, you are quite right.
Ibeo created SCALA.
With the ScaLa SOP in 2016 Ibeo is the first company worldwide, who has developed a mass-market automotive LIDAR sensor. The ScaLa sensor was designed for the customer Audi.
In this paper we evaluate the use of a laser scanner for future advanced driver assistance systems. We focus on the important task of predicting the target vehicle for longitudinal ego vehicle control. Our motivation is to decrease the reaction time of existing systems during cut-in maneuvers of other traffic participants. A state-of-the-art laser scanner, the Ibeo Scala B2 R , is presented, providing its sensing characteristics and the subsequent high level object data output.
Valeo is by far the most advanced company today in terms of industrialization, maturity, testing, reliability and manufacturing scalability of an automotive LiDAR product for ADAS, and eventually for AVs. The SCALA® design was initiated with a cooperation, development and licensing agreement with Ibeo in 2010. Valeo invested in maturing the initial design platform into the launch of the fully qualified second generation SCALA® product in 2021. More than 150,000 units have been sold to date.Valeo Leads Deployment And Industrialization Of Automotive LiDAR
The business of LiDAR is poised to transition from hype, speculation and technology roadmaps into products, revenues and execution. A critical success factor is the ability to meet the demanding requirements of automotive deployment. Valeo is leading this effort.
Valeo has signed a cooperation, development and license agreement with Ibeo Automotive Systems GmbH in the field of laser scanner technology.Valeo and Ibeo to cooperate on automotive laser scanner technology
Valeo has signed a cooperation, development and license agreement with Ibeo Automotive Systems GmbH in the field of laser scanner technology. This agreement gives Valeo exclusive access to Ibeo’s expertise and know-how and enables it to evolve Ibeo’s laser scanner technology for high-volume...www.greencarcongress.com
This agreement gives Valeo exclusive access to Ibeo’s expertise and know-how and enables it to evolve Ibeo’s laser scanner technology for high-volume applications. This technology complements Valeo’s own range of radar, ultrasonic, infrared and vision sensor systems. With the laser scanner, Valeo will be able to promote innovative active safety features in this area.
Scala Gen 2 was developed for and in conjunction with Mercedes Benz.
Drive Pilot uses the car’s surround sensors already in place for the Driving Assistance Package, together with additional sensors the Mercedes people consider crucial for safe L3 automated driving. These include lidar—it’s Valeo’s latest Scala system—as well as a camera in the rear window and microphones, especially for detecting flashing lights and other signals from emergency vehicles. There is also a wetness sensor in the wheel well. The S-Class with optional Drive Pilot also has redundant steering and braking systems and a redundant electrical system to ensure it remains manœuvrable even if a primary system fails, and enables safe handover to the driver.
Mercedes, Valeo on Drive Pilot L3 - DVN
With Drive Pilot in the Vision EQXX, Mercedes-Benz last December received the world’s first approval for an L3 AD system under the UN Regulations recgonised by most of the world’s…
www.drivingvisionnews.com
DVN: And how does this 2nd-generation Scala system differ to the original?
C.N.: Scala 2 was meant to be an improvement over Scala 1, but has been redesigned from scratch to match stringent Mercedes-Benz requirements for L3 operation. It delivers a wider vertical field of view (10°) and more layers—16, against 4 layers for Scala 1. It stands today as the reference sensor to meet the requirements of traffic jam speed L3 on highways. Of course, its design is protected by a substantial number of patents.DVN: Do you think we’ll see Drive Pilot from other automakers soon?
C.N.: Strictly speaking, the Drive Pilot system belongs to Mercedes-Benz; only they can decide whether to extend it to other automakers. Scala 2 is currently in development for other automakers to achieve traffic jam L3 operation, exactly like Mercedes-Benz.
ItsKane
Regular
Don't get me wrong I buy small parcels every paycheck, don't wanna miss out
jtardif999
Regular
There is really only one way atm, the 1000 eyes can continue to investigate and provide very much appreciated dots in every facet of existing and nascent technology in all the fields of electronics.. it doesn’t matter though, all roads will eventually lead to Akida - what other technology currently exists that could make performance improvements like thisValeo Group | 14 Jun, 2022 | 5 min
Valeo’s third generation LiDAR chosen by Stellantis for its level 3 automation capability
Stellantis has chosen Valeo's third-generation LiDAR to equip multiple models of its different automotive brands from 2024. The Valeo SCALA 3 LiDAR will enable these vehicles to be certified for level 3 automation, allowing drivers to safely take their hands off the steering wheel and their eyes off the road.
As Yves Bonnefont, Chief Software Officer and member of Stellantis’ Top Executive Team, explains: “What sets cars apart from others today is the driving experience they offer. Thanks to our L3 autonomous driving solution leveraging Valeo’s latest generation LiDAR, we will offer a more enjoyable driving experience and give back time to the driver during their journeys.“
Marc Vrecko, President of Valeo’s Comfort & Driving Assistance Systems Business Group, commented: “A new chapter in driving assistance systems is being written with our partners at Stellantis. Level 3 vehicle automation can only be achieved with LiDAR technology. Without it, some objects cannot be detected. Yet at this level of autonomy, the system’s perception capabilities must be extremely precise. Our third-generation Valeo SCALA LiDAR offers a resolution nearly 50 times that of the second-generation device. The technology comes with unique data collection features, allowing Stellantis to pave the way for new vehicle experiences.”
Valeo’s third-generation LiDAR sees everything, even when an object is far ahead, invisible to the human eye. It can identify objects more than 150 meters ahead that neither the human eye, cameras nor radars can, such as a small object with very low reflectivity, for example a tire lying in the road. It recreates a 3D image of the vehicle’s surroundings using a point cloud, with an as yet unparalleled resolution for an automotive system. It can map the ground topology and detect road markings.
Valeo LiDAR also features embedded high performance software based on artificial intelligence algorithms, which enables it to steer the vehicle’s trajectory, anticipating obstacle-free zones on the road ahead. It can self-diagnose and triggers its cleaning system when its field of vision is obstructed. Like all Valeo LiDAR, the technology is automotive grade, meaning that the data it generates remain fully reliable and accurate in all usage and weather conditions (from -40 up to +85°C). It stands as the key component in a sensor system enabling vehicles to achieve approval for SAE conditional driving automation (level 3), meeting the legal requirements of UN-R157.
Valeo’s third generation LiDAR makes driving safer and gives time back to the driver in bothersome driving situations, such as when traveling at low or medium speed in heavy traffic. These challenges are central to the partnership between Stellantis and Valeo. Through its data collection capabilities, this LiDAR will enable new services to be offered to Stellantis’ customers.
Valeo is already world number one in advanced driver assistance systems (ADAS), equipping one in three new cars globally with its technologies. It was the first, and to date remains the only, company to produce an automotive LiDAR scanner on an industrial scale. More than 170,000 units have been produced and the technology is protected by more than 500 patents. The Group intends to accelerate even further in this field, as announced in February 2022 with the launch of its Move Up plan, the value creation strategy at the heart of the four megatrends disrupting mobility (electrification, ADAS, reinvention of the interior experience and lighting).
Download the press release
Valeo's third generation LiDAR
“Our third-generation Valeo SCALA LiDAR offers a resolution nearly 50 times that of the second-generation device.” A 5000% improvement when other ‘latest’ technologies are claiming the sorts of 10-30% improvements.
LordByron
Member
JenkinsRiding shotgun. Called it first
Taproot
Regular
Yes ZF took a 40% stake in Ibeo.G'day mate yes already read that stuff in my researching
This is the future of Lidar
Ibeo's 4D Solid State Lidar sensor system.
All Products
MicroVision offers a family of automotive lidar sensors and solutions for advanced driver-assistance systems (ADAS), autonomous vehicles, and non-automotive applications, including industrial, smart infrastructure, and robotics.
www.ibeo-as.com
No moving parts
Size of a credit card
Fact Finder
Top 20
If I didn’t know better I would mistake you for the CEO Sean Hehir as he was making the exact same point at the AGM.
My opinion only DYOR
FF
AKIDA BALLISTA
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