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BrainChip Introduces Second-Generation Akida Platform
Peter Van Der Made
Chief Technology Officer at BrainChip
1 article
March 8, 2023
Introduces Vision Transformers and Spatial-Temporal Convolution for radically fast, hyper-efficient, and secure Edge AIoT products, untethered from the cloud
Laguna Hills, Calif. – March 6, 2023 –
BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power, fully digital, neuromorphic AI IP, today announced the second generation of its Akida™ platform that drives extremely efficient and intelligent edge devices for the Artificial Intelligence of Things (AIoT) solutions and services market that is expected to be $1T+ by 2030. This hyper-efficient yet powerful neural processing system, architected for embedded Edge AI applications, now adds efficient 8-bit processing to go with advanced capabilities such as time domain convolutions and vision transformer acceleration, for an unprecedented level of performance in sub-watt devices, taking them from perception towards cognition.
The second-generation of Akida now includes Temporal Event Based Neural Nets (TENN) spatial-temporal convolutions that supercharge the processing of raw time-continuous streaming data, such as video analytics, target tracking, audio classification, analysis of MRI and CT scans for vital signs prediction, and time series analytics used in forecasting, and predictive maintenance. These capabilities are critically needed in industrial, automotive, digital health, smart home and smart city applications. The TENNs allow for radically simpler implementations by consuming raw data directly from sensors – drastically reduces model size and operations performed, while maintaining very high accuracy. This can shrink design cycles and dramatically lower the cost of development.
Another addition to the second generation of Akida is Vision Transformers (ViT) acceleration, a leading edge neural network that has been shown to perform extremely well on various computer vision tasks, such as image classification, object detection, and semantic segmentation. This powerful acceleration, combined with Akida’s ability to process multiple layers simultaneously and hardware support for skip connections, allows it to self-manage the execution of complex networks like RESNET-50 completely in the neural processor without CPU intervention and minimizes system load.
The Akida IP platform has a unique ability to learn on the device for continuous improvement and data-less customization that improves security and privacy. This, combined with the efficiency and performance available, enable very differentiated solutions that until now have not been possible. These include secure, small form factor devices like hearable and wearable devices, that take raw audio input, medical devices for monitoring heart and respiratory rates and other vitals that consume only microwatts of power. This can scale up to HD-resolution vision solutions delivered through high-value, battery-operated or fanless devices enabling a wide variety of applications from surveillance systems to factory management and augmented reality to scale effectively.
“We see an increasing demand for real-time, on-device, intelligence in AI applications powered by our MCUs and the need to make sensors smarter for industrial and IoT devices,” said Roger Wendelken, Senior Vice President in Renesas’ IoT and Infrastructure Business Unit. “We licensed Akida neural processors because of their unique neuromorphic approach to bring hyper-efficient acceleration for today’s mainstream AI models at the edge. With the addition of advanced temporal convolution and vision transformers, we can see how low-power MCUs can revolutionize vision, perception, and predictive applications in wide variety of markets like industrial and consumer IoT and personalized healthcare, just to name a few.”
“Advancements in AI require parallel advancements in on-device learning capabilities while simultaneously overcoming the challenges of efficiency, scalability, and latency,” said Richard Wawrzyniak, principal analyst at Semico Research. “BrainChip has demonstrated the ability to create a truly intelligent edge with Akida and moves the needle even more in terms of how Edge AI solutions are developed and deployed. The benefits of on-chip AI from a performance and cost perspective are hard to deny.”
“Our customers wanted us to enable expanded predictive intelligence, target tracking, object detection, scene segmentation, and advanced vision capabilities. This new generation of Akida allows designers and developers to do things that were not possible before in a low-power edge device,” said Sean Hehir, BrainChip CEO. “By inferring and learning from raw sensor data, removing the need for digital signal pre-processing, we take a substantial step toward providing a cloudless Edge AI experience.”
Akida’s software and tooling further simplifies the development and deployment of solutions and services with these features:
- An efficient runtime engine that autonomously manages model accelerations completely transparent to the developer
- MetaTF™ software that developers can use with their preferred framework, like TensorFlow/Keras, or development platform, like Edge Impulse, to easily develop, tune, and deploy AI solutions.
- Supports all types of Convolutional Neural Networks (CNN), Deep Learning Networks (DNN), Vision Transformer Networks (ViT) as well as Spiking Neural Networks (SNNs), future-proofing designs as the models get more advanced.
Akida comes with a Models Zoo and a burgeoning ecosystem of software, tools, and model vendors, as well as IP, SoC, foundry and system integrator partners. BrainChip is engaged with early adopters on the second generation IP platform. General availability will follow in Q3’ 2023.
See what they’re saying:
“At Prophesee, we are driven by the pursuit of groundbreaking innovation addressing event-based vision solutions. Combining our highly efficient neuromorphic-enabled Metavision sensing approach with Brainchip’s Akida neuromorphic processor holds great potential for developers of high-performance, low-power Edge AI applications. We value our partnership with BrainChip and look forward to getting started with their 2nd generation Akida platform, supporting vision transformers and TENNs,” said Luca Verre, Co-Founder and CEO at Prophesee.
Luca Verre, Co-Founder and CEO, Prophesee
“BrainChip and its unique digital neuromorphic IP have been part of IFS’ Accelerator IP Alliance ecosystem since 2022,” said Suk Lee, Vice President of Design Ecosystem Development at IFS. “We are keen to see how the capabilities in Akida’s latest generation offerings enable more compelling AI use cases at the edge”
Suk Lee, VP Design Ecosystem Development, Intel Foundry Services
“Edge Impulse is thrilled to collaborate with BrainChip and harness their groundbreaking neuromorphic technology. Akida’s 2nd generation platform adds TENNs and Vision Transformers to a strong neuromorphic foundation. That’s going to accelerate the demand for intelligent solutions. Our growing partnership is a testament to the immense potential of combining Edge Impulse’s advanced machine learning capabilities with BrainChip’s innovative approach to computing. Together, we’re forging a path toward a more intelligent and efficient future,” said Zach Shelby, Co-Founder and CEO at Edge Impulse.
Zach Shelby, Co-Founder and CEO, Edge Impulse
“BrainChip has some exciting upcoming news and developments underway,” said Daniel Mandell, Director at VDC Research. “Their 2nd generation Akida platform provides direct support for the intelligence chip market, which is exploding. IoT market opportunities are driving rapid change in our global technology ecosystem, and BrainChip will help us get there.”
Daniel Mandell, Director, VDC Research
“Integration of AI Accelerators, such as BrainChip’s Akida technology, has application for high-performance RF, including spectrum monitoring, low-latency links, distributed networking, AESA radar, and 5G base stations,” said John Shanton, CEO of Ipsolon Research, a leader in small form factor, low power SDR technology.
John Shanton, CEO, Ipsolon Research
“Through our collaboration with BrainChip, we are enabling the combination of SiFive’s RISC-V processor IP portfolio and BrainChip’s 2nd generation Akida neuromorophic IP to provide a power-efficient, high capability solution for AI processing on the Edge,” said Phil Dworsky, Global Head of Strategic Alliances at SiFive. “Deeply embedded applications can benefit from the combination of compact SiFive Essential™ processors with BrainChip’s Akida-E, efficient processors; more complex applications including object detection, robotics, and more can take advantage of SiFive X280 Intelligence™ AI Dataflow Processors tightly integrated with BrainChip’s Akida-S or Akida-P neural processors.”
Phil Dworsky, Global Head of Strategic Alliances, SiFive
“Ai Labs is excited about the introduction of BrainChip’s 2nd generation Akida neuromorphic IP, which will support vision transformers and TENNs. This will enable high-end vision and multi-sensory capability devices to scale rapidly. Together, Ai Labs and BrainChip will support our customers’ needs to address complex problems,” said Bhasker Rao, Founder of Ai Labs. “Improving development and deployment for industries such as manufacturing, oil and gas, power generation, and water treatment, preventing costly failures and reducing machine downtime.”
Bhasker Rao, Founder, Ai Labs
“We see an increasing demand for real-time, on-device, intelligence in AI applications powered by our MCUs and the need to make sensors smarter for industrial and IoT devices,” said Roger Wendelken, Senior Vice President in Renesas’ IoT and Infrastructure Business Unit. “We licensed Akida neural processors because of their unique neuromorphic approach to bring hyper-efficient acceleration for today’s mainstream AI models at the edge. With the addition of advanced temporal convolution and vision transformers, we can see how low-power MCUs can revolutionize vision, perception, and predictive applications in a wide variety of markets like industrial and consumer IoT and personalized healthcare, just to name a few.”
Roger Wendelken, Senior Vice President IoT and Infrastructure Business Unit, Renesas
“We see a growing number of predictive industrial (including HVAC, motor control) or automotive (including fleet maintenance), building automation, remote digital health equipment and other AIoT applications use complex models with minimal impact to product BOM and need faster real-time performance at the Edge” said Nalin Balan, Head of Business Development at Reality ai, a Renesas company. “BrainChip’s ability to efficiently handle streaming high frequency signal data, vision, and other advanced models at the edge can radically improve scale and timely delivery of intelligent services.”
Nalin Balan, Head of Business Development, Reality.ai, a Renesas Company
“Advancements in AI require parallel advancements in on-device learning capabilities while simultaneously overcoming the challenges of efficiency, scalability, and latency,” said Richard Wawrzyniak, Principal Analyst at Semico Research. “BrainChip has demonstrated the ability to create a truly intelligent edge with Akida and moves the needle even more, in terms of how Edge AI solutions are developed and deployed. The benefits of on-chip AI from a performance and cost perspective are hard to deny.”
Richard Wawrzyniak, Principal Analyst, Semico Research
“BrainChip’s cutting-edge neuromorphic technology is paving the way for the future of artificial intelligence, and Drexel University recognizes its immense potential to revolutionize numerous industries. We have experienced that neuromorphic compute is easy to use and addresses real-world applications today. We are proud to partner with BrainChip and advancing their groundbreaking technology, including TENNS and how it handles time series data, which is the basis to address a lot of complex problems and unlocking its full potential for the betterment of society,” said Anup Das, Associate Professor and Nagarajan Kandasamy, Interim Department Head of Electrical and Computer Engineering, Drexel University.
Anup Das, Associate Professor, Drexel University
“Our customers wanted us to enable expanded predictive intelligence, target tracking, object detection, scene segmentation, and advanced vision capabilities. This new generation of Akida allows designers and developers to do things that were not possible before in a low-power edge device,” said Sean Hehir, BrainChip CEO. “By inferring and learning from raw sensor data, removing the need for digital signal pre-processing, we take a substantial step toward providing a cloudless Edge AI experience.”
Sean Hehir, CEO, BrainChip
About BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY)
BrainChip is the worldwide leader in edge AI on-chip processing and learning. The company’s first-to-market, fully digital, event-based AI processor, AkidaTM, uses neuromorphic principles to mimic the human brain, analyzing only essential sensor inputs at the point of acquisition, processing data with unparalleled efficiency, precision, and economy of energy. Akida uniquely enables edge learning local to the chip, independent of the cloud, dramatically reducing latency while improving privacy and data security. Akida Neural processor IP, which can be integrated into SoCs on any process technology, has shown substantial benefits on today’s workloads and networks, and offers a platform for developers to create, tune and run their models using standard AI workflows like TensorFlow/Keras. In enabling effective edge compute to be universally deployable across real world applications such as connected cars, consumer electronics, and industrial IoT, BrainChip is proving that on-chip AI, close to the sensor, is the future, for its customers’ products, as well as the planet. Explore the benefits of Essential AI at
www.brainchip.com.
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https://www.twitter.com/BrainChip_inc
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https://www.linkedin.com/company/7792006
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