Okeydokey01
Regular
This is a cracker!
I really like "MOST EFFICIENT SOLUTION EVER" pretty much sums us up!
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
This is a cracker!
I really like "MOST EFFICIENT SOLUTION EVER" pretty much sums us up!
Fact Finder
Top 20
Nice find but not AKIDA and not a threat to a tiny hand held unconnected device:
“The InspectIR COVID-19 Breathalyzer uses a technique called gas chromatography gas mass-spectrometry (GC-MS)”
They will only be making a hundred a week and they can only test 160 a day and you need two operators one medically trained and you still need to take the clinical history into account.
My opinion only DYOR
FF
AKIDA BALLISTA
Fact Finder
Top 20
In case you think I have lost the plot then consider this one public statement by Rob Telson:
‘NASA we are doing vision and other things we cannot talk about’
Then look to all the things that are in the public domain involving NASA/DARPA such as the ISL Brainchip US Airforce Radar project, the Intellisense Cognitive communications SBIR, the Vorago Brainchip partnership, the SiFive Brainchip hardened RISC-V Ai processor and despite all of these there are projects at NASA which cannot be talked about????
Still my Quantum annealing email despite being acknowledged and being followed up continues to be ignored.
My opinion and speculation only DYOR
FF
AKIDA BALLISTA
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Fact Finder
Top 20
Anyone else here think that the ASX has not yet accorded any current or future value to the following:
“A partnership has now been announced with SiFive, the founder and market leader of RISC-V computing. Thus, the respective technologies have been combined to offer chip designers optimized AI/ML computing power at the edge of the network. For BrainChip, the addition to its product portfolio is an opportunity to integrate Akida technology into a market-leading product offering, creating an efficient combination for edge computing…”
The way these writers have put the partnership between SiFive and Brainchip it does seem to be worth something but of course as we know the market is always right and if you say that enough eventually like a broken clock it will be.
My opinion only DYOR
FF
AKIDA BALLISTA
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Fact Finder
Top 20
Galaxy S22 overheating might not just be Samsung’s fault
A report says that Samsung might not be the only one to blame for any Galaxy S22 overheating issues - the problem might be bigger than that.
bgr.com
Is Brainchip the answer?
Sorry if this has already been posted.
Not sure where else to post this
Hey FF , when was this announcement made and by whom? it sounds fairly important to me, then why does BRN not make this an announcement to the ASX and keep some momentum in theSP. I understand many things are going on in the background ( I hear all these things BTW on here not from BRN)Anyone else here think that the ASX has not yet accorded any current or future value to the following:
“A partnership has now been announced with SiFive, the founder and market leader of RISC-V computing. Thus, the respective technologies have been combined to offer chip designers optimized AI/ML computing power at the edge of the network. For BrainChip, the addition to its product portfolio is an opportunity to integrate Akida technology into a market-leading product offering, creating an efficient combination for edge computing…”
The way these writers have put the partnership between SiFive and Brainchip it does seem to be worth something but of course as we know the market is always right and if you say that enough eventually like a broken clock it will be.
My opinion only DYOR
FF
AKIDA BALLISTA
If management are trying to spread the word and get our product out there , then it makes sense to me to keep the market continually updated, keep the SP doing something and keep other forums talking. Keep interest up, you have to keep throwing burley into the water if you eventually want to land the big ones. Its also important to keep owners (shareholders) up to speed with whats going on. I know big things are coming, but when theres months between decent announcements , its hard to keep positive watching the price do nothing when you're sitting on whats probably the most revolutionary tech I'll see in my lifetime.
Bravo
If ARM was an arm, BRN would be its biceps💪!
Yes. I noticed a reference to Brembo and aluminium brakes. The closed wheel covers also point to regenerative braking.
To achieve the efficiency Mercedes did, they must use regenerative braking.
This page from Brembo refers to hybrid friction/regenerative brakes:
Introducing the brake of the future! All of the benefits thanks to the new Brembo electric brakes
A leap into the future with Brembo brakes: changing the way you drive with benefits for drivers and for the environment.www.brembo.com
In fact, the brake system will automatically adapt to the vehicle's load conditions, keeping the braking space constant. In addition, a further feature of driving comfort due to the brake-by-wire system is provided by the transition from dissipative braking to regenerative braking that is smooth and imperceptible for the driver.
https://www.greencarreports.com/new...sion-eqxx-concept-626-mile-trip-single-charge
The drive, which was independently monitored by TÜV Süd, took the Vision EQXX over the Swiss Alps and throughout Northern Italy, creating plenty of opportunities for energy recuperation through regenerative braking while descending.
US2021114464A1 METHOD AND SYSTEM FOR CONTROLLING THE REGENERATIVE BRAKING TORQUE OF A VEHICLE
A method for controlling the regenerative braking torque of a vehicle, the vehicle comprising at least one first axle on which at least one first moving member of the vehicle is mounted and at least one second axle on which at least one second moving member of the vehicle is mounted, the vehicle further comprising a braking system comprising a first plurality of components operatively associated with said at least one first axle and a second plurality of components operatively associated with said at least one second axle, the vehicle comprising at least one traction and regenerative braking supply module configured to provide the regenerative braking torque to one or more regenerative braking torque actuation modules with which the vehicle is provided, the vehicle further comprising a battery module and at least one data processing unit operatively connected to said at least one traction and regenerative braking supply module, to the first plurality of components of the braking system, to the second plurality of components of the braking system,
the method comprising steps of:
detecting, by the at least one data processing unit, a first information representing a deceleration request of the vehicle;
detecting, by the at least one data processing unit, a second information representing a speed of at least one of the vehicle, the first moving member of the vehicle and the second moving member of the vehicle;
determining, by the at least one data processing unit, a first temperature value of at least one component of the first plurality of components of the braking system operatively associated with said at least one first axle;
determining, by the at least one data processing unit, a second temperature value of at least one component of the second plurality of components of the braking system operatively associated with said at least one second axle;
determining, by the at least one data processing unit, a third information representing the state of at least one of the battery module and said at least one traction and regenerative braking supply module;
determining, by the at least one data processing unit, a regenerative braking power dynamic distribution ratio between the first axle and the second axle on the basis of the first information, of the first temperature value and of the second temperature value;
determining, by the at least one data processing unit, a first regenerative braking torque value to be applied to the first axle and a second regenerative braking torque value to be applied to the second axle on the basis of the determined regenerative braking power dynamic distribution ratio, of the second information and of the third information;
providing, by the at least one data processing unit, the first regenerative braking torque value and the second regenerative braking torque value to said at least one traction and regenerative braking supply module.
#################################################################
US11046295B2 Electronic system for controlling traction and braking of a vehicle and related method
View attachment 4283
An electronic system for controlling traction and braking of a vehicle is described. The system includes a device for actuating braking operatively connected to at least one first wheel of the vehicle, and at least one first traction and braking control unit. The device comprises: at least one first electric actuator and at least one electric motor. The at least one first traction and braking control unit being configured to control the at least one electric motor in regeneration mode to exert a regenerative braking torque on at least one first wheel. The at least one first traction and braking control unit also being configured to control the at least one electric motor in traction mode to exert a traction torque on the at least one first wheel.
I imagine the regenerative brake controls can automatically detect downhill and maintain a constant speed.
From the Brembo website.
Boab
I wish I could paint like Vincent
For those of us that were late to catch the bus we are grateful for reflective posts like this.An Easter reflection:
https://stocksdownunder.com/video/b...-semiconductor-conference-on-1-november-2021/
20211130
Marc: Okay. Regarding the Akida 2000 and the timeline specifically for that one, can you talk a little bit about the development timeline?
Peter: Yes. Akida 2000 is very exciting too. We are developing that here in Perth. We have an excellent team here in Perth of highly qualified people who are working on Akida 2000 and Akida 3000. So we’re really thinking ahead here. Akida 2000 will be optimized for more complex network architectures, such as [inaudible 00:29:37] {#LSTM#}* transformers. And for a very large part, those simulations of those chips are… At least Akida 2000 is already…the simulation is working already. And we are getting ready to hand it over to engineering.
So Akida 3000 is going to a cortical network. Cortical networks are based on the way the human cortex works. They’re still a lot of open questions about, especially in neuroscience, how that exactly works. We’ll be building models of the cortex and see how we can apply that to a real commercial environment. Of course, everything we do, of course, even though the science is fascinating, we have to always keep in mind that we are building commercial products.
Marc: All right. One interesting question I saw earlier coming from Nathan about the advantage you have in terms of time versus competitors. Previously you stated two to three years advantage versus competitors. With the Akida 1000 now almost sort of commercially available, do you still think your timeline or the time advantage is still two to three years or has that changed?
Peter: Yes, we are working very hard to make sure that we maintain that advantage. So Akida 1000, we estimate to be two or three years ahead of the market. For instance, we have convolution and hardware not by a processor. We have real-time learning that nobody else has been able to manage. So we definitely have a two or three advantage in Akida 1000, plus we have commercializing that product. But to maintain that advantage, we are working on Akida 2000 and 3000. So we stay ahead of the markets. With Akida 3000, we’re probably about five or six years ahead at the moment.
Thank you FF
AusEire
Founding Member. It's ok to say No to Dot Joining
Ah good old Luke "What's a Neuromorphic chip anyway" Winchester. I wouldn't be paying any heed to someone who has absolutely no idea or understanding of what it is that Brainchip does.
Boab
I wish I could paint like Vincent
Sean didnt seem to be worried about the logistical holdups around the world. He said they had planned ahead. I hope he's right.
The image below is from a few days ago. Not sure how long the Chinese Gov can keep it's people locked in there home before there is a rebellion?
That's not good. They could mount a land-based invasion of Taiwan.
Boab
I wish I could paint like Vincent
jtardif999
Regular
Repeating this part of the above translation:I have used Google to provide the following translation:
AI computing expands from cloud to edge miniaturized hardware and software solutions are booming
- Zheng Feiwen
- 2022-04-11
- forward print
With the participation of major software and hardware manufacturers, the TinyML ecological chain is becoming more and more mature
The development of artificial intelligence is becoming more and more mature. In the initial stage, the cloud was mainly responsible for computing and inference. It has gradually expanded to the edge to pursue the goals of low latency, low energy consumption, and low cost. TinyML is a new technology trend of the recent rise of AI edge computing. The TinyML solution usually integrates hardware, algorithms and application software. Its advantage is that it can still collect and analyze sensor data under the condition of low energy consumption of the device. The energy consumption is usually mW (milliwatt) level or below, which is suitable for battery as AI computing applications that are powered by devices and need to be always on.
According to DIGITIMES Research, Google, Arm, Intel, Qualcomm and innovative application companies have participated in the TinyML ecological chain, accelerating the maturity of their software and hardware solutions. The development status of TinyML can be explained from three aspects. The first aspect is the inference architecture and platform aspect. TensorFlow Lite is Google's solution for embedded and IoT edge devices, which can assist developers to execute TensorFlow models on embedded devices and IoT devices. , TensorFlow Lite function is to convert the cloud training model and deploy the compressed prediction model to the edge device, and execute the prediction inference program.
In addition, Edge Impulse is an embedded machine learning development platform that can quickly build edge-side inference models on the platform and deploy them to embedded MCU devices for sensors, audio frequency, and computer vision. Machine vision prediction and inference can choose the OpenMV platform, which has the advantages of low cost and scalability, and can be used in face recognition, object classification, etc.
The second level is the representative of hardware solution chips, Arm Cortex-M series, Intel embedded chip VPU Movidius series, Qualcomm QCC MCU series, STMicroelectronics STM32 series, NXP Semiconductors NXP i.MX RT series, etc. At present, the architecture and platform hardware that can support TinyML are mainly based on Arm architecture Cortex-M series MCU; TensorFlow Lite platform is represented by Arduino Cortex-M4 series and STMicroelectronics Cortex-M7 STM32 series. The Edge Impulse platform is represented by the Eta Compute Cortex-M4 and STMicroelectronics Cortex-M4 STM32 series. The OpenMV platform is represented by OpenMV Cortex-M7 series and Sipeed Maix Bit series RISC-V processors.
It is worth noting that DIGITIMES Rersearch has observed the recent development trend of foreign manufacturers entering the TinyML field. For example, Ericsson, a telecom equipment indicator, has published many TinyML research propositions on its official website. Micro Electro Mechanical Systems (MEMS) The sensor company Bosch (Bosch Sensortec) also expressed its support for TinyML and developed the corresponding MEMS driver, indicating that the industry attaches great importance to the future market prospects of TinyML.
Level 3 is for innovative applications, representing manufacturers such as American business BabbleLabs (which has been acquired by Cisco), which uses AI technology in the Webex Meetings conference software to distinguish human speech from unnecessary noise to improve communication quality and user experience; Australian manufacturer Brainchip product Akida The series of MCUs provide vision, sound frequency and sensor applications, enabling machine learning on the MCU without retraining in the cloud. The American manufacturer Qeexo AutoML platform uses various algorithms to automatically construct machine learning models, which are suitable for industry, Internet of Things, wearable devices, automobiles, etc. The visual AI software developed by French manufacturer GrAI Matter Labs is used in edge devices such as drones, robots, and surveillance cameras that require low power consumption.
TinyML data sources are biometrics, action data, sensor data, voice data, video (image) data, etc., and are used in access control systems, automatic driving, energy management, predictive maintenance, remote monitoring, etc. Among them, commercialization is implemented. The case is the QuickLogic QuickAI series, an American businessman in the field of smart manufacturing. A sound and multi-axis motion sensor is installed on the device (motor), and the data received by the sensor is sent to the EOS S3 MCU to predict and infer the real-time health status of the device. Develop maintenance and repair plans with management.
The Seeed SenseCAP solution, a Chinese company in the field of smart agriculture, uses sensors to measure air and soil temperature, air and soil moisture, and soil salinity. The Raspberry Pi Arm Cortex-A7 processor predicts and deduces the best growth conditions. Provide a numerical reference scheme for improving the environment.
Research firm Gartner predicts that by 2025, 75% of AI processing will occur at the edge, and TinyML may develop a market value of more than $70 billion in the next five years. However, DIGITIMES Research believes that TinyML still needs to face the challenges of software, hardware and performance at present. MCUs with higher hardware specifications only have built-in 1MB NOR Flash and 512KB SRAM, and the storage code and other functions have taken up most of the space. In addition, running TensorFlow Lite requires 20KB NOR Flash and 4KB SRAM, which limits the choice of algorithm/application field.
In addition, using keywords to wake up the application MCU requires a long-term standby state, and the power consumption also generates high temperature and heat dissipation problems. There are also problems such as different chip instructions from various manufacturers, lack of unified infrastructure, and difficulty in transferring program syntax and experience. In addition, when the model is established, the relevant resources and plug-in software are insufficient, and it is difficult and time-consuming to deploy the model at the edge; the performance aspect is due to the large differences in the MCU specifications of various manufacturers, which makes it difficult for designers and developers to convert into equivalent performance specifications. Operational benefit analysis.
Summarizing the trend of AI edge computing, although the above challenges still need to be overcome by consensus among manufacturers in the ecological chain, and related industry players will be hesitant in the short term, but in the medium and long term, TinyML is still the general trend, coupled with the transmission of market concepts , Through demonstration and trial implementation, end users will gradually feel the many benefits of TinyML, and TinyML will certainly be able to significantly commercialize.
Icon: With the participation of major software and hardware manufacturers, the TinyML ecological chain is becoming more and more mature. Compiled by DIGITIMES Research, April 2022
“””
Research firm Gartner predicts that by 2025, 75% of AI processing will occur at the edge, and TinyML may develop a market value of more than $70 billion in the next five years. However, DIGITIMES Research believes that TinyML still needs to face the challenges of software, hardware and performance at present. MCUs with higher hardware specifications only have built-in 1MB NOR Flash and 512KB SRAM, and the storage code and other functions have taken up most of the space. In addition, running TensorFlow Lite requires 20KB NOR Flash and 4KB SRAM, which limits the choice of algorithm/application field.
In addition, using keywords to wake up the application MCU requires a long-term standby state, and the power consumption also generates high temperature and heat dissipation problems. There are also problems such as different chip instructions from various manufacturers, lack of unified infrastructure, and difficulty in transferring program syntax and experience. In addition, when the model is established, the relevant resources and plug-in software are insufficient, and it is difficult and time-consuming to deploy the model at the edge; the performance aspect is due to the large differences in the MCU specifications of various manufacturers, which makes it difficult for designers and developers to convert into equivalent performance specifications.
“””
The Renesas MCUs should then be able to corner the market as by utilising Akida IP they have solved all of the above problems. AIMO.
Bravo
If ARM was an arm, BRN would be its biceps💪!
This looks interesting.
ZF's Automatic Valet Solution will debut at the end of 2022 and is meant to be the world's first valet parking globally that will enable parking only on the vehicle's sensor set. In other words it will operate independently of a pre-mapped garage infrastructure and looks like it doesn't require connectivity??? Actually, I think that means it doesn't require connecrtivity with the garage infrastructure.
www.zf.com
ZF's Automatic Valet Solution will debut at the end of 2022 and is meant to be the world's first valet parking globally that will enable parking only on the vehicle's sensor set. In other words it will operate independently of a pre-mapped garage infrastructure and looks like it doesn't require connectivity??? Actually, I think that means it doesn't require connecrtivity with the garage infrastructure.
Automated Valet Parking - ZF
With its cost-efficient "Automated Valet Parking" solution, ZF helps to reduce the stress of finding parking spaces. The system is one of the first worldwide to function independent of a pre-mapped and instrumented parking garage infrastructure.
www.zf.com
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Fact Finder
Top 20
It was released as a press release below. I have previously asked the company why similar press releases were not also non price sensitive announcements via the ASX without a response. Perhaps you could ask at the AGM as I do not have an answer:
Laguna Hills, Calif. – April 5, 2022 – BrainChip Holdings Ltd(ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power neuromorphic AI chips and IP, and SiFive, Inc., the founder and leader of RISC-V computing, have combined their respective technologies to offer chip designers optimized AI/ML compute at the edge.
BrainChip’s AkidaTM is a revolutionary advanced neural networking processor architecture that brings AI to the edge in a way that existing technologies are not capable, with high performance, ultra-low power, and on-chip learning. SiFive Intelligence™ solutions with their highly configurable multi-core, multi-cluster capable design, integrate software and hardware to accelerate AI/ML applications. The integration of BrainChip’s Akida technology and SiFive’s multi-core capable RISC-V processors will provide a highly efficient solution for integrated edge AI compute.
SiFive Intelligence™-based processors offer industry leading performance and efficiency for AI and ML workloads. The highly configurable multi-core, multi-cluster capable design has been optimized for the broadest range of applications requiring high-throughput, single-thread performance while under the tightest power and area constraints.
“Employing Akida, BrainChip’s specialized, differentiated AI engine, with high-performance RISC-V processors such as the SiFive Intelligence Series is a natural choice for companies looking to seamlessly integrate an optimized processor to dedicated ML accelerators that are a must for the demanding requirements of edge AI computing,” said Chris Jones, vice president, products at SiFive. “BrainChip is a valuable addition to our ecosystem portfolio”.
BrainChip’s first-to-market neuromorphic processor, Akida, mimics the human brain to analyze only essential sensor inputs at the point of acquisition, processing data with unparalleled efficiency, precision, and economy of energy. Keeping AI/ML local to the chip, independent of the cloud, also dramatically reduces latency while improving privacy and data security.
“We are pleased to partner with SiFive and have the opportunity to have our Akida technology integrated with their market-leading product offerings, creating an efficient combination for edge compute,” said Jerome Nadel, BrainChip CMO. “As we expand our ecosystem of portfolio partners, we want to be sure that these relationships are built on complementary technologies, enabling capabilities, and breadth of environments so that we can expand opportunities to as many potential customers as possible. Driving our technology into a SiFive-based subsystem is exactly the type of partnership that meets these goals.”
For additional information about the BrainChip, SiFive partnership contact sales@brainchip.com.
About BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY)
BrainChip is a global technology company that is producing a groundbreaking neuromorphic processor that brings artificial intelligence to the edge in a way that is beyond the capabilities of other products. The chip is high performance, small, ultra-low power and enables a wide array of edge capabilities that include on-chip training, learning and inference. The event-based neural network processor is inspired by the spiking nature of the human brain and is implemented in an industry standard digital process. By mimicking brain processing BrainChip has pioneered a processing architecture, called Akida™, which is both scalable and flexible to address the requirements in edge devices. At the edge, sensor inputs are analyzed at the point of acquisition rather than through transmission via the cloud to a data center. Akida is designed to provide a complete ultra-low power and fast AI Edge Network for vision, audio, olfactory and smart transducer applications. The reduction in system latency provides faster response and a more power efficient system that can reduce the large carbon footprint of data centers.Additional information is available at https://www.brainchipinc.com
Follow BrainChip on Twitter: https://www.twitter.com/BrainChip_inc
Follow BrainChip on LinkedIn: https://www.linkedin.com/company/7792006
About SiFive
As the pioneers who introduced RISC-V to the world, SiFive is transforming the future of compute by bringing the limitless potential of RISC-V to the highest performance and most data-intensive applications in the world. SiFive’s unrivaled compute platforms have enabled leading technology companies around the world to innovate, optimize and deliver the most advanced solutions of tomorrow across every market segment of chip design, including artificial intelligence, machine learning, automotive, data center, mobile, and consumer. With SiFive, the future of RISC-V has no limits. For more information, please visit www.sifive.com.
supersonic001
Regular
BrainChip on LinkedIn: #ai #neuromorphic #ml #edgeai
From News/Financial - Infineon, BrainChip, NVIDIA - Chip Market Facing The Next Wave https://lnkd.in/dusF4fek #AI #neuromorphic #ML #edgeAI
Potential further BUY opportunity or have we hit a stabilised base ?
Fact Finder
Top 20
I know the late former Prime Minister Whitlam used the phase but not sure if he was the first but stealing his words “Luke will be remembered in infamy”.
My opinion only DYOR
FF
AKIDA BALLISTA
ThanksIt was released as a press release below. I have previously asked the company why similar press releases were not also non price sensitive announcements via the ASX without a response. Perhaps you could ask at the AGM as I do not have an answer:
Laguna Hills, Calif. – April 5, 2022 – BrainChip Holdings Ltd(ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power neuromorphic AI chips and IP, and SiFive, Inc., the founder and leader of RISC-V computing, have combined their respective technologies to offer chip designers optimized AI/ML compute at the edge.
BrainChip’s AkidaTM is a revolutionary advanced neural networking processor architecture that brings AI to the edge in a way that existing technologies are not capable, with high performance, ultra-low power, and on-chip learning. SiFive Intelligence™ solutions with their highly configurable multi-core, multi-cluster capable design, integrate software and hardware to accelerate AI/ML applications. The integration of BrainChip’s Akida technology and SiFive’s multi-core capable RISC-V processors will provide a highly efficient solution for integrated edge AI compute.
SiFive Intelligence™-based processors offer industry leading performance and efficiency for AI and ML workloads. The highly configurable multi-core, multi-cluster capable design has been optimized for the broadest range of applications requiring high-throughput, single-thread performance while under the tightest power and area constraints.
“Employing Akida, BrainChip’s specialized, differentiated AI engine, with high-performance RISC-V processors such as the SiFive Intelligence Series is a natural choice for companies looking to seamlessly integrate an optimized processor to dedicated ML accelerators that are a must for the demanding requirements of edge AI computing,” said Chris Jones, vice president, products at SiFive. “BrainChip is a valuable addition to our ecosystem portfolio”.
BrainChip’s first-to-market neuromorphic processor, Akida, mimics the human brain to analyze only essential sensor inputs at the point of acquisition, processing data with unparalleled efficiency, precision, and economy of energy. Keeping AI/ML local to the chip, independent of the cloud, also dramatically reduces latency while improving privacy and data security.
“We are pleased to partner with SiFive and have the opportunity to have our Akida technology integrated with their market-leading product offerings, creating an efficient combination for edge compute,” said Jerome Nadel, BrainChip CMO. “As we expand our ecosystem of portfolio partners, we want to be sure that these relationships are built on complementary technologies, enabling capabilities, and breadth of environments so that we can expand opportunities to as many potential customers as possible. Driving our technology into a SiFive-based subsystem is exactly the type of partnership that meets these goals.”
For additional information about the BrainChip, SiFive partnership contact sales@brainchip.com.
About BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY)
BrainChip is a global technology company that is producing a groundbreaking neuromorphic processor that brings artificial intelligence to the edge in a way that is beyond the capabilities of other products. The chip is high performance, small, ultra-low power and enables a wide array of edge capabilities that include on-chip training, learning and inference. The event-based neural network processor is inspired by the spiking nature of the human brain and is implemented in an industry standard digital process. By mimicking brain processing BrainChip has pioneered a processing architecture, called Akida™, which is both scalable and flexible to address the requirements in edge devices. At the edge, sensor inputs are analyzed at the point of acquisition rather than through transmission via the cloud to a data center. Akida is designed to provide a complete ultra-low power and fast AI Edge Network for vision, audio, olfactory and smart transducer applications. The reduction in system latency provides faster response and a more power efficient system that can reduce the large carbon footprint of data centers.
Additional information is available at https://www.brainchipinc.com
Follow BrainChip on Twitter: https://www.twitter.com/BrainChip_inc
Follow BrainChip on LinkedIn: https://www.linkedin.com/company/7792006
About SiFive
As the pioneers who introduced RISC-V to the world, SiFive is transforming the future of compute by bringing the limitless potential of RISC-V to the highest performance and most data-intensive applications in the world. SiFive’s unrivaled compute platforms have enabled leading technology companies around the world to innovate, optimize and deliver the most advanced solutions of tomorrow across every market segment of chip design, including artificial intelligence, machine learning, automotive, data center, mobile, and consumer. With SiFive, the future of RISC-V has no limits. For more information, please visit www.sifive.com.
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