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BrainChip Introduces Energy Efficient and Precise AI Edge Solution at AI Field Day - Gestalt IT

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Artificial Intelligence (AI) is a rapidly growing field. In "The State of AI in 2020" report, McKinsey found that 50% of the organizations surveyed have adopted AI in at least one function within their business. BrainChip developed the Akida Event-Domain Neural Processor to enable AI to run at an organization's edge, a location AI typically couldn't reach. BrainChip introduced and demonstrated the Akida solution at AI Field Day in November. The typical AI system requires thousands of data points to successfully train the algorithm and a powerful system to process the model.


BrainChip Joins tinyML Summit 2021 for Ultra-Low Power Edge Machine Learning Technologies

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WIRE)--BrainChip Holdings Ltd (ASX: BRN), a leading provider of ultra-low power high performance artificial intelligence technology, today announced it is sponsoring and presenting at tinyML Summit, a virtual event March 22-26, 2021. TinyML Summit will feature technical progress and ecosystem development within the "tiny" machine learning industry to enable ultra-low power ML in edge applications. Tiny ML is a growing field of ML technologies including hardware (dedicated integrated circuits), algorithms, and software capable of performing on-device data analytics at extremely low power to enable a range of always-on applications, primarily in battery-operated devices. Tiny ML is common in audio, visual, navigational, biometric, and medical devices as well as other commercial and industrial uses. Kristofor Carlson, BrainChip's Manager of Applied Research, will present a talk "It's an SNN future: Are you ready for it?


Electronic Nose Uses Solid-state Sensors and Neural Processor to "Sniff Out" COVID-19 - News

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A recent partnership between BrainChip Holdings and NaNose Medical has yielded a new COVID-19 testing solution boasting higher accuracy than RT-PCR screening. The Nano Artificial Nose is said to actively analyze patient breath samples while remaining highly portable. How exactly does it work? Officially dubbed the DiaNose, NaNose's technology has actually existed since 2017. Based on the Technion Israeli Institute of Technology's artificial nose, the device has since screened numerous patients for Parkinson's disease, cancer, kidney failure, and MS.


BrainChip Success in 2020 Advances Fields of on-Chip Learning

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BrainChip Holdings Ltd., a leading provider of ultra-low power, high-performance AI technology, ended the 2020 calendar year having made significant strides in the development of its technology backed by the launch of its Early Access Program (EAP), availability of Akida evaluation boards, new partnerships, and expansion of its executive leadership and global facilities. "This past year saw significant progress in the development of the Akida technology in terms of both market readiness and the increase in market possibilities that the solution will provide immediate impact in" The Company's EAP was launched in June targeting specific customers in a diverse set of end markets in order to ensure availability of initial devices and evaluation systems for key applications. Multiple customers have committed to the advanced purchase of evaluation systems for a range of strategic Edge applications including Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles (AV), Unmanned Aerial Vehicles (UAV), Edge vision systems and factory automation. Among those joining the EAP include VORAGO Technologies in a collaboration intended to support a Phase I NASA program for a neuromorphic processor that meets spaceflight requirements. BrainChip is also collaborating with Tier-1 Automotive Supplier Valeo Corporation to develop neural network processing solutions for ADAS and AV.


BrainChip's Success in 2020 Advances Fields of On-Chip Learning and Ultra-Low Power Edge AI

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San Francisco, March 3, 2021 -- BrainChip Holdings Ltd. (ASX: BRN), a leading provider of ultra-low-power, high-performance AI technology, ended the 2020 calendar year having made significant strides in the development of its technology backed by the launch of its Early Access Program (EAP), availability of Akida evaluation boards, new partnerships, and expansion of its executive leadership and global facilities. The Company's EAP was launched in June targeting specific customers in a diverse set of end markets in order to ensure availability of initial devices and evaluation systems for key applications. Multiple customers have committed to the advanced purchase of evaluation systems for a range of strategic Edge applications including Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles (AV), Unmanned Aerial Vehicles (UAV), Edge vision systems and factory automation. Among those joining the EAP include VORAGO Technologies in a collaboration intended to support a Phase I NASA program for a neuromorphic processor that meets spaceflight requirements. BrainChip is also collaborating with Tier-1 Automotive Supplier Valeo Corporation to develop neural network processing solutions for ADAS and AV.


Deep Learning Chipsets Market – increasing demand with Industry Professionals: Google, BrainChip, Intel – TechnoWeekly

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JCMR recently Announced Deep Learning Chipsets study with 200 market data Tables and Figures spread through Pages and easy to understand detailed TOC on "Global Deep Learning Chipsets Market. Global Deep Learning Chipsets Market allows you to get different methods for maximizing your profit. The research study provides estimates for Deep Learning Chipsets Forecast till 2028*. Some of the Leading key Company's Covered for this Research are Google, BrainChip, Intel, AMD, NVIDIA, Xilinx, IBM, ARM, Graphcore, Qualcomm, Amazon, Facebook, Cerebras Systems, Mobileye, Movidius, CEVA, Nervana Systems, Wave Computing Our report will be revised to address COVID-19 effects on the Global Deep Learning Chipsets Market. Global Deep Learning Chipsets Market for a Leading company is an intelligent process of gathering and analyzing the numerical data related to services and products. This Research Give idea to aims at your targeted customer's understanding, needs and wants.


BrainChip Brings AI to the Edge and Beyond - Gestalt IT

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Until now, Artificial Intelligence processing has been a centralized function. It featured massive systems with thousands of processors working in parallel. But researchers have discovered that lower-precision operations work just as well for popular applications like speech and image processing. This opens the door to a new generation of cheap and low-power machine learning chips from companies like BrainChip. Machine learning is incredibly challenging, with massive data sets and power-hungry processors.


BrainChip Presents on AI in Edge Devices at Linley Fall Processor Conference 2020

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WIRE)--BrainChip Holdings Ltd. (ASX: BRN), a leading provider of ultra-low power high performance AI technology, today announced that Chief Development Officer Anil Mankar will present "A Neuromorphic Processor for Power Efficient Edge AI Applications" at the Linley Fall Processor Conference 2020 October 20 at 9:30 a.m. BrainChip's presentation is part of the conference's first-day session "AI in Edge Devices." As part of the presentation, Mankar will provide an update on the AKD1000, BrainChip's first Neural network SoC (NSoC), and describe the advantages of processing information in the event-domain. A 10-minute Q&A session will immediately follow the conclusion of his speech. "Many edge-AI processors take advantage of the spatial sparsity in neural network models to eliminate unnecessary computations and save power," said Mankar.


Spiking Neural Networks: Research Projects or Commercial Products?

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Spiking neural networks (SNNs) often are touted as a way to get close to the power efficiency of the brain, but there is widespread confusion about what exactly that means. In fact, there is disagreement about how the brain actually works. Some SNN implementations are less brain-like than others. Depending on whom you talk to, SNNs are either a long way away or close to commercialization. The varying definitions of SNNs leads to differences in how the industry is seen. "A few startups are doing their own SNNs," said Ron Lowman, strategic marketing manager of IP at Synopsys. "It's being driven by guys that have expertise in how to train, optimize, and write software for them." On the other hand, Flex Logix Inference Technical Marketing Manager Vinay Mehta said that, "SNNs are out further than reinforcement learning," referring to a machine-learning concept that's still largely in the research phase. The entire notion of a "neural network" is motivated by attempts to model how the brain works.


BrainChip Launches the Akida Early Access Program

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ALISO VIEJO, Calif., June 15, 2020 -- BrainChip Holdings Ltd announced an Early Access Program (EAP) for the Akida neural processor System-on-Chip (SoC). The EAP has been targeted at specific customers in a diversity of end markets for early adoption of the Akida device. Since announcing the start of wafer fabrication in April 2020, the demand for evaluation systems, including engineering prototypes, has been significant. In response to this demand, BrainChip has established an EAP for select partners to ensure availability of initial devices and evaluation systems for key applications. Multiple customers have committed to the advanced purchase of evaluation systems for a range of strategic Edge applications including ADAS/AV, Unmanned Aerial Vehicles (UAV), Edge vision systems and factory automation.