CHIPS
Regular
Yeah, so I guess that's you and 3 others off of here?
Unless "it's" you, how did you know they are a "she"..
Because I am smart and I looked at her LinkedIn profile
. And no, I do not follow her, but I guess some others here do. 
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
Because I am smart and I looked at her LinkedIn profile
. And no, I do not follow her, but I guess some others here do.
View attachment 71610 View attachment 71611 View attachment 71612 View attachment 71613
Dr. Jerry A. Smith on LinkedIn: The Role of RISC-V in Shaping the Future of AI and Computational…
🚀 How RISC-V is Transforming the Future of AI and Computational Neuroscience 🧠✨ Imagine an open, flexible hardware architecture that powers the next wave of…www.linkedin.com
Home
We have built a global team of subject matter experts and seasoned advisors with hard-earned industry knowledge, primed for this very moment, and for the future, given the disruptions and rapid pace of change that defines the business environment.ankura.com
View attachment 71615
Bang goes another NDA!!!???
View attachment 71610 View attachment 71611 View attachment 71612 View attachment 71613Dr. Jerry A. Smith on LinkedIn: The Role of RISC-V in Shaping the Future of AI and Computational…
🚀 How RISC-V is Transforming the Future of AI and Computational Neuroscience 🧠✨ Imagine an open, flexible hardware architecture that powers the next wave of…
Home
We have built a global team of subject matter experts and seasoned advisors with hard-earned industry knowledge, primed for this very moment, and for the future, given the disruptions and rapid pace of change that defines the business environment.
View attachment 71615
Wow what a nice find!
This Dr Jerry Smith is clearly very knowledgeable on the subject, and I was having a hard time reading his paper, it's over my pay grade, but I understood enough to feel comfortable about my investment here.
He is highlighting us and Tenstorrent and also said their way of working could compliment each other, so not really direct competitors.
Seriously, what does RISC-V have to do with the Akida SoC architecture?
Certainly a partnership was announced with SiFive in April 2022, but that was more about a co-processor arrangement.
https://brainchip.com/brainchip-sifive-partner-deploy-ai-ml-at-edge/
BrainChip and SiFive Partner to Deploy AI/ML Technology at the Edge
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.
RISC-V is 32/64 bits
Still, it's better to be talked about than ignored.
DingoBorat
Slim
I think it's possible, that he's just confused and thinks AKIDA is RISC-V based?
There's not really any other explanation..
Food4 thought
Regular
Tick tock Sean 
it’s almost 5 minutes to midnight
it’s almost 5 minutes to midnight
Food4 thought
Regular
GStocks123
Regular
Worth keeping an eye on TDK 
unfortunately their “spin-memristor” is targeting analog though..
unfortunately their “spin-memristor” is targeting analog though..Attachments
AI Acceleration Co-Processor Claims Lowest Power Operation
The fully digital, event-based, brain-inspired Akida Pico helps usher in compact, ultra-low-power intelligent devices.
Microwaves & RF on LinkedIn: AI Acceleration Co-Processor Claims Lowest Power Operation
The fully digital, event-based, brain-inspired Akida Pico from BrainChip helps usher in compact, ultra-low-power intelligent devices. #AI #ML
View attachment 71610 View attachment 71611 View attachment 71612 View attachment 71613Dr. Jerry A. Smith on LinkedIn: The Role of RISC-V in Shaping the Future of AI and Computational…
🚀 How RISC-V is Transforming the Future of AI and Computational Neuroscience 🧠✨ Imagine an open, flexible hardware architecture that powers the next wave of…
Home
We have built a global team of subject matter experts and seasoned advisors with hard-earned industry knowledge, primed for this very moment, and for the future, given the disruptions and rapid pace of change that defines the business environment.
View attachment 71615
Haha, as a ATH, most in here like myself are expecting ANN every day for the past and future. But never mind!
Rskiff
Regular
I have been expecting an announcement that is material for donkeys, but have been let down by my expectations.
Bravo
If ARM was an arm, BRN would be its biceps💪!
It's interesting because under the heading "Neuromorphic Chip Latest Industry Updates" 3 out of 5 points outlined relate to BrainChip.
Neuromorphic Chip Market
The global neuromorphic chip market size was USD 1.1 Billion in 2023 and is expected to reach a market valuation of USD 1.81 billion by the end of 2024 registering a CAGR of 64.7% during the forecast period. Neuromorphic chips, small semiconductor devices designed to mimic how the human brain processes information, are set to transform various industries with their advanced capabilities. These chips replicate thought processes using artificial neurons and synapses, enabling faster and more efficient data processing. With the ability to learn and adapt in real-time, neuromorphic chips are at the forefront of innovation in artificial intelligence (AI) and machine learning (ML).
Unlike traditional computers that rely on linear processing, neuromorphic chips allow for parallel processing, enabling simultaneous handling of multiple data streams. This unique architecture supports quick learning and decision-making, making these chips particularly well-suited for applications in robotics, autonomous vehicles, and the Internet of Things (IoT).
To avail Sample Copy of the report @https://www.emergenresearch.com/request-sample/2971
Neuromorphic chips excel at recognizing patterns in large datasets, making them ideal for tasks such as speech and image recognition and natural language processing. Their event-driven approach allows for real-time data analysis, enhancing capabilities in areas like cybersecurity, fraud detection, and critical industrial monitoring.
The demand for neuromorphic chips is rapidly growing across various sectors. In healthcare, these chips are being used for real-time patient monitoring and diagnostics. In finance, they aid in risk assessment and fraud detection. Additionally, their ability to process data quickly is crucial for the automotive industry, particularly in the development of autonomous vehicles, where immediate analysis of sensor data is vital for safety and efficiency.
Market Drivers:
Neuromorphic chips are paving the way for advancements in AI and ML applications due to their adaptability and energy efficiency. They integrate processing and memory functions directly within each neuron, significantly improving speed and reducing latency. Their real-time learning capabilities allow these chips to adapt to changing environments swiftly, making them robust in dynamic settings.
As research into brain functions continues to evolve, neuromorphic technology is poised to revolutionize various industries, enhancing the performance of existing systems and developing new solutions. The growing interest in edge computing, where data is processed closer to the source rather than relying on centralized data centers, is also driving demand for these chips, especially in enterprise applications.
Market Challenges:
Despite their potential, neuromorphic chips face several challenges. As the technology is still in its early stages, questions remain regarding their accuracy compared to traditional computing methods. The high cost and complexity of these chips, coupled with limited software and algorithm development, present hurdles for widespread adoption. Furthermore, ethical considerations regarding privacy and autonomy are increasingly becoming essential as these technologies advance.
Request Customization In The Report @https://www.emergenresearch.com/request-for-customization/2971
Market Segmentation:
Neuromorphic chips can be categorized into various segments based on components, applications, end-use industries, and market verticals.
Component Insights: The hardware segment is projected to lead revenue growth as it forms the backbone of neuromorphic computing. Custom-built processors, such as Intel's Loihi and BrainChip's Akida, are at the forefront of this development.
Application Insights: The robotics and automation segment is anticipated to account for the largest share of the market, driven by the demand for advanced robotics in sectors like manufacturing, logistics, and healthcare.
End-Use Insights: The commercial (enterprise) segment is expected to dominate, with industries like finance, telecommunications, and industrial automation increasingly adopting neuromorphic technology for real-time AI processing.
Industry Vertical Insights: The automotive sector is set to witness significant growth as neuromorphic chips enhance the capabilities of autonomous driving technology, improving real-time decision-making and sensory processing while minimizing power consumption.
Neuromorphic Chip Top Companies and Competitive Landscape
The global neuromorphic chip market is highly competitive with key players such as Intel, IBM, Qualcomm and BrainChip Holdings. Leading companies are investing heavily in R&D to improve chip technology and performance.
Strategic partnerships and collaborations with research institutions and technology companies are common to drive innovation and speed up product development. They are also expanding their market presence through mergers and acquisitions to access new markets and technologies. They are also engaging with customers by offering industry specific solutions to broaden their customer base and strengthen their market presence.
Browse The Full Neuromorphic Chip Market Report Description, Along With The Tocs And List Of Facts And Figures @ https://www.emergenresearch.com/industry-report/neuromorphic-chip-market
Some of the key companies in the Neuromorphic Chip market include:
Intel Corporation
IBM Corporation
Qualcomm Incorporated
BrainChip Holdings Ltd.
Samsung Electronics Co., Ltd.
NVIDIA Corporation
General Vision Inc.
STMicroelectronics N.V.
Infinera Corporation
Huawei Technologies Co., Ltd.
Neuromorphic Chip Latest Industry Updates
BrainChip Holdings Ltd. and NVISO (April 2022): This partnership aims to leverage BrainChip's Akida technology for AI-enabled human behavioral analysis, enhancing neuromorphic computing applications.
BrainChip Holdings Ltd. and Lorser Industries Inc. (June 2023): This collaboration focuses on integrating BrainChip's Akida technology into software-defined radio devices, marking a significant step in expanding practical applications of neuromorphic chips.
Cornell Tech and BrainChip (May 2024): A partnership to introduce a new course in neuromorphic computing as part of Cornell's University AI Accelerator Program, indicating an academic push towards innovation in this field.
In September 2023, the U.S. National Science Foundation announced funding of USD 45.6 million for 24 research initiatives aimed at advancing semiconductor technologies, supported by the CHIPS and Science Act of 2022. This funding is crucial for fostering innovation in neuromorphic computing.
The Canadian government introduced the Artificial Intelligence and Data Act (AIDA) in June 2023 to promote responsible AI development, further enhancing the growth environment for neuromorphic technologies.
Neuromorphic Chips: Revolutionizing Technology with Brain-Like Processing Power
10-22-2024 03:10 PM CET | Business, Economy, Finances, Banking & InsurancePress release from: Emergen Research
Neuromorphic Chip Market
The global neuromorphic chip market size was USD 1.1 Billion in 2023 and is expected to reach a market valuation of USD 1.81 billion by the end of 2024 registering a CAGR of 64.7% during the forecast period. Neuromorphic chips, small semiconductor devices designed to mimic how the human brain processes information, are set to transform various industries with their advanced capabilities. These chips replicate thought processes using artificial neurons and synapses, enabling faster and more efficient data processing. With the ability to learn and adapt in real-time, neuromorphic chips are at the forefront of innovation in artificial intelligence (AI) and machine learning (ML).
Unlike traditional computers that rely on linear processing, neuromorphic chips allow for parallel processing, enabling simultaneous handling of multiple data streams. This unique architecture supports quick learning and decision-making, making these chips particularly well-suited for applications in robotics, autonomous vehicles, and the Internet of Things (IoT).
To avail Sample Copy of the report @https://www.emergenresearch.com/request-sample/2971
Neuromorphic chips excel at recognizing patterns in large datasets, making them ideal for tasks such as speech and image recognition and natural language processing. Their event-driven approach allows for real-time data analysis, enhancing capabilities in areas like cybersecurity, fraud detection, and critical industrial monitoring.
The demand for neuromorphic chips is rapidly growing across various sectors. In healthcare, these chips are being used for real-time patient monitoring and diagnostics. In finance, they aid in risk assessment and fraud detection. Additionally, their ability to process data quickly is crucial for the automotive industry, particularly in the development of autonomous vehicles, where immediate analysis of sensor data is vital for safety and efficiency.
Market Drivers:
Neuromorphic chips are paving the way for advancements in AI and ML applications due to their adaptability and energy efficiency. They integrate processing and memory functions directly within each neuron, significantly improving speed and reducing latency. Their real-time learning capabilities allow these chips to adapt to changing environments swiftly, making them robust in dynamic settings.
As research into brain functions continues to evolve, neuromorphic technology is poised to revolutionize various industries, enhancing the performance of existing systems and developing new solutions. The growing interest in edge computing, where data is processed closer to the source rather than relying on centralized data centers, is also driving demand for these chips, especially in enterprise applications.
Market Challenges:
Despite their potential, neuromorphic chips face several challenges. As the technology is still in its early stages, questions remain regarding their accuracy compared to traditional computing methods. The high cost and complexity of these chips, coupled with limited software and algorithm development, present hurdles for widespread adoption. Furthermore, ethical considerations regarding privacy and autonomy are increasingly becoming essential as these technologies advance.
Request Customization In The Report @https://www.emergenresearch.com/request-for-customization/2971
Market Segmentation:
Neuromorphic chips can be categorized into various segments based on components, applications, end-use industries, and market verticals.
Component Insights: The hardware segment is projected to lead revenue growth as it forms the backbone of neuromorphic computing. Custom-built processors, such as Intel's Loihi and BrainChip's Akida, are at the forefront of this development.
Application Insights: The robotics and automation segment is anticipated to account for the largest share of the market, driven by the demand for advanced robotics in sectors like manufacturing, logistics, and healthcare.
End-Use Insights: The commercial (enterprise) segment is expected to dominate, with industries like finance, telecommunications, and industrial automation increasingly adopting neuromorphic technology for real-time AI processing.
Industry Vertical Insights: The automotive sector is set to witness significant growth as neuromorphic chips enhance the capabilities of autonomous driving technology, improving real-time decision-making and sensory processing while minimizing power consumption.
Neuromorphic Chip Top Companies and Competitive Landscape
The global neuromorphic chip market is highly competitive with key players such as Intel, IBM, Qualcomm and BrainChip Holdings. Leading companies are investing heavily in R&D to improve chip technology and performance.
Strategic partnerships and collaborations with research institutions and technology companies are common to drive innovation and speed up product development. They are also expanding their market presence through mergers and acquisitions to access new markets and technologies. They are also engaging with customers by offering industry specific solutions to broaden their customer base and strengthen their market presence.
Browse The Full Neuromorphic Chip Market Report Description, Along With The Tocs And List Of Facts And Figures @ https://www.emergenresearch.com/industry-report/neuromorphic-chip-market
Some of the key companies in the Neuromorphic Chip market include:
Intel Corporation
IBM Corporation
Qualcomm Incorporated
BrainChip Holdings Ltd.
Samsung Electronics Co., Ltd.
NVIDIA Corporation
General Vision Inc.
STMicroelectronics N.V.
Infinera Corporation
Huawei Technologies Co., Ltd.
Neuromorphic Chip Latest Industry Updates
BrainChip Holdings Ltd. and NVISO (April 2022): This partnership aims to leverage BrainChip's Akida technology for AI-enabled human behavioral analysis, enhancing neuromorphic computing applications.
BrainChip Holdings Ltd. and Lorser Industries Inc. (June 2023): This collaboration focuses on integrating BrainChip's Akida technology into software-defined radio devices, marking a significant step in expanding practical applications of neuromorphic chips.
Cornell Tech and BrainChip (May 2024): A partnership to introduce a new course in neuromorphic computing as part of Cornell's University AI Accelerator Program, indicating an academic push towards innovation in this field.
In September 2023, the U.S. National Science Foundation announced funding of USD 45.6 million for 24 research initiatives aimed at advancing semiconductor technologies, supported by the CHIPS and Science Act of 2022. This funding is crucial for fostering innovation in neuromorphic computing.
The Canadian government introduced the Artificial Intelligence and Data Act (AIDA) in June 2023 to promote responsible AI development, further enhancing the growth environment for neuromorphic technologies.
Bravo
If ARM was an arm, BRN would be its biceps💪!
Reading though an article on Qualcomm's brand new Snapdragon 8 Elite, it mentions that it has an "enhanced Qualcomm Hexagon NPU".
It makes me wonder how we would ever know if Qualcomm decided to add a little bit of Pico sauce into their recipe? Pico can be a co-processor to any NPU or MCU after-all.
View attachment 71555
Qualcomm's Snapdragon 8 Elite is Now World's Fastest Mobile CPU, Designed for On-Device Generative AI and Gaming
Qualcomm's new Snapdragon 8 Elite is now the world's fastest mobile CPU, and also the first Snapdragon Mobile Platform to feature the company's next-generation custom Oryon CPU. Not only does it power on-device generative AI, but the CPU is also built to handle next level gaming, super-fast web...www.techeblog.com
OK Brain Fam!
So, hopefully this might add a little more substance to my speculation yesterday.
I ruddy well hope so!
Qualcomm, Alphabet team up for automotive AI; Mercedes inks chip deal
By Stephen NellisOctober 23, 20246:05 AM GMT+11Updated 3 hours ago
[1/2]A smartphone with a displayed Qualcomm logo is placed on a computer motherboard in this illustration taken March 6, 2023.
Oct 22 (Reuters) - Qualcomm (QCOM.O), opens new tab on Tuesday said it was teaming up with Alphabet's (GOOGL.O), opens new tab Google to offer a combination of chips and software that will let automakers develop their own AI voice assistants using technology from the two firms.
Qualcomm's chips have long powered mobile phones with Google's Android operating system and the company has expanded into the automotive business, with chips that can power both a car's dashboard and automated driving systems that are used by General Motors (GM.N), opens new tab and others. On Tuesday, Qualcomm said it is working with Google to create a version of the company's Android Automotive OS that will run smoothly on Qualcomm chips.
Advertisement · Scroll to continue
Report this ad
While many consumers are familiar with Google's Android Auto and Apple CarPlay that display apps from a phone when plugged into a vehicle, Google's Android Automotive OS is an offering that automakers use behind the scenes to power a vehicle computing systems. Qualcomm and Google said automakers will be able to use the joint offering and Google's AI technology to create voice assistants that are unique to an automaker and can work without relying on a driver's phone.
Advertisement · Scroll to continue
Report this ad
"Typically, we have operated together, but independently - we plan a lot of things together, but we go to customers separately," Nakul Duggal, group manager for automotive at Qualcomm, said of the Qualcomm-Google relationship. "We decided we should think about this differently because it will reduce a lot of friction and confusion."
Qualcomm on Tuesday also rolled out two new chips, one called Snapdragon Cockpit Elite to power dashboards and another called Snapdragon Ride Elite for self-driving features. The company said Mercedes-Benz Group (MBGn.DE), opens new tab plans to use the Snapdragon Elite Cockpit chip in future vehicles, though the two companies did not specify when or in which vehicles the chip will appear.
Last edited:
Hi @Rskiff same here been too long for any dream to come true right, every day hoping there ill be some news all we get is no news lol
7für7
Top 20
Lucid vision and prophesee
www.linkedin.com
PROPHESEE on LinkedIn: #eventbasedcamera #metavision #metavisiontechnologies #research…
[Breaking] LUCID Vision Labs, Inc., a leading designer and manufacturer of industrial cameras, today announced the launch of the new Triton2 EVS event-based…
Similar threads
