BRN Discussion Ongoing

[Bravo]

Neuromorphic Computing Market Will See Strong Expansion Through 2030​

06-13-2025 09:02 AM CET | IT, New Media & Software

Press release from: Allied Market Research​

Neuromorphic Computing Market

Allied Market Research, titled, "Neuromorphic Computing Market By Offering, Deployment, Application, and Industry Vertical: Global Opportunity Analysis and Industry Forecast, 2021-2030", the global neuromorphic computing market size was valued at $26.32 million in 2020, and projected to reach $8,583.98 million by 2030, registering a CAGR of 79.0%. North America is expected to be the leading contributor to the global market during the forecast period, followed by Asia-Pacific and Europe.

Neuromorphic computing aims at processing information in a way similar to the human brain. Instead of a conventional von Neumann computer, a neuromorphic system generally relies on a neural network, where memory and processing elements are intimately co-located within the same hardware. Neuromorphic computing takes advantage of computational memories, which can both store and process data via physical laws within the device and the circuit. This summarizes the history and main concepts of neuromorphic computing, including both deep neural networks (DNNs) which are adopted for extensive artificial intelligence tasks, such as driverless cars, and spiking neural networks (SNNs), which aim at a more realistic brain-inspired computation.

Neuromorphic computing gets its inspiration from the human brain's architecture and dynamics to create energy-efficient hardware for information processing, making it capable of highly sophisticated tasks. Neuromorphic computing includes the production and use of neural networks. It takes its inspiration from the human brain to design computer chips that can merge memory and processing.

Recently, Intel Corporation delivered 50 million artificial neurons to Sandia National Laboratories, which is equivalent to the brain of a small mammal. The shipment is the first in a three-year series, by the end of which they are expecting the number of experimental neurons in the final model to reach 1 billion or more. This collaboration aims to boost neuromorphic computing solutions to newer heights while prototyping the software, algorithms, and architectures.

Get a Customized Research Report @ https://www.alliedmarketresearch.com/request-for-customization/A13743

Prominent factors that impact the neuromorphic computing market growth include a rise in demand for artificial intelligence and machine learning technology, high usage of software in neuromorphic computing, and a rise in demand for better-performing integrated circuits (ICs). However, the rise in the complexity of algorithms and backend operations restricts market growth. On the contrary, an increase in the adoption of neuromorphic chips in the automotive industry is expected to create lucrative opportunities for the market. Therefore, these factors are expected to affect the global neuromorphic computing industry during the forecast period.

Region-wise, the neuromorphic computing market trends are analyzed across North America (U.S., Canada, and Mexico), Europe (Germany, UK, France, Italy, and Rest of Europe), Asia-Pacific (China, Japan, India, South Korea, Taiwan, and Rest of Asia-Pacific), and LAMEA (Latin America, the Middle East, and Africa). North America is dominating the market due to rising awareness about the benefits of neuromorphic computing in industries such as aerospace, military & defense, and healthcare. The overall neuromorphic computing market analysis is determined to understand the profitable trends to gain a stronger foothold.

Key Findings of the Study

- In 2020, the hardware segment accounted for the maximum revenue and is projected to grow at a notable CAGR of 77.00% during the forecast period.
- The image recognition segment accounted for more than 40% of the global neuromorphic computing market share in 2020.
- The consumer electronics segment witnessed the highest growth rate during the forecast period.
- The UK was the major shareholder in the European neuromorphic computing market revenue, accounting for approximately 26% share in 2020.

The key players profiled in the report include IBM Corporation (US), Intel Corporation (US), BrainChip Holdings Ltd. (US), Qualcomm Incorporated (US), Hewlett Packard Development LP (US), Samsung Electronics Ltd. (South Korea), General Vision Inc. (US), L Applied Brain Research Inc. (US), Numenta (US), and Huawei Technologies (China). These players have adopted various strategies, such as partnership, agreement, collaboration, and product launch, to expand their foothold in the neuromorphic computing industry.

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About Us:

Allied Market Research is a leading provider of market intelligence, offering reports from top technology publishers. Our in-depth market assessments in our research reports take into account significant technological advancements in the sector. In addition to other areas of expertise, AMR focuses on the analysis of high-tech systems and advanced production systems. We have a team of experts who compile thorough research reports and actively advise leading businesses to enhance their current procedures. Our experts have a wealth of knowledge on the topics they cover. Additionally, they employ a range of tools and techniques when gathering and analyzing data, including proprietary data sources.

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help@alliedmarketresearch.com

 

[DK6161]

I

Must be all the non believers from the crapper now becoming believers

View attachment 86982

I am a share holder and still not a believer

 

[Bravo]

On a slightly more serious note, take a look at these recent articles on TSMC’s concept AR glasses. Then ask yourself: is it really just a coincidence that we’ve now confirmed a collaboration with Yu-Hsin Layout Technology - a company that happens to count TSMC as one of its major clients?

One of the standout features of these AR glasses is an ultra-low-power processor, which, of course, just happens to be right in Akida/Pico’s wheelhouse.

Now, while these articles only discuss TSMC’s concept glasses for now, if they ever move to production, it would effectively place us toe-to-toe with Qualcomm in the smart glasses arena (assuming they incorporate our technology).

And let’s be honest - if battery life becomes the battleground, we’re not exactly walking in unarmed.


View attachment 86973


View attachment 86974

View attachment 86975

AR/VR Glasses Taking Shape With New Chips

Smart glasses with augmented reality functions look more natural than VR goggles, but today they are heavily reliant on a phone for compute and next-gen communication.

semiengineering.com

The Future of Smart Glasses: Why Cameras Matter and How to Address Privacy Concerns

Original Article by SemiVision Research

tspasemiconductor.substack.com

TSMC will also be mass producing the chips in 2027 that will go into APPLE's smart glasses.

So not only are they working on their own concept glasses, but in addition to that, they're manufacturing the chips for Apple's glasses.

What are the chances of us winding up in both sets of glasses?

Next-Gen Chips Powering Future Smart Glasses and AI​

Posted on June 2, 20251 min Read

Apple is making significant strides in chip development for its future devices, including its highly anticipated smart glasses, artificial intelligence (AI) servers, and next-generation MacBooks.
According to recent reports, the company is focusing on creating specialized processors to power its smart glasses, which will be equipped with multiple cameras and energy-efficient components. These chips are based on Apple Watch technology, ensuring lower power consumption while delivering high performance.
The chips will be manufactured by Taiwan’s TSMC and are expected to enter mass production by 2027.
In addition to smart glasses, Apple is also working on new processors for its Macs, including the M6 and M7 chips.

Next-Gen Chips Powering Future Smart Glasses and AI - Telecom Review Asia

Apple is developing specialized chips for smart glasses, AI servers, and new MacBooks to improve power efficiency and advance functionality.

www.telecomreviewasia.com

Apple’s Next Gen Chips Signal Big Moves in Smart Tech and AI - nexstale.com

Apple Inc.'s is pushing the boundaries of its custom silicon efforts, developing next generation chips designed to power a range of future products including advanced Mac models, AI servers, and most notably, its long anticipated smart glasses. According to a recent Bloomberg report by Mark...

nexstale.com

 

[7für7]

I’ve never invested in a company that has so many heavyweights as partners and customers, receives so much positive coverage in industry journals, and is spoken of so highly by those very partners and clients.
It’s operating in a future market worth billions that’s still largely untapped .. and yet, the stock price remains stagnant… even though there are no revenues yet.

 

[Food4 thought]

Hi everyone

I have a crazy idea
But it needs your input.

If everyone gets on to Gemini or chat gpt and recommend the use of Akida this is going to provide more information so that Akida will be suggested for use.
These models are being trained by the information that is fed to them.

Suggest that Akida should be used for power saving to save the planet.

What do you think ?
If enough people were to do this it will change outcomes for sure.

 

[MrNick]

TSMC will also be mass producing the chips in 2027 that will go into APPLE's smart glasses.

So not only are they working on their own concept glasses, but in addition to that, they're manufacturing the chips for Apple's glasses.

What are the chances of us winding up in both sets of glasses?

View attachment 87005

Next-Gen Chips Powering Future Smart Glasses and AI​

Posted on June 2, 20251 min Read

Apple is making significant strides in chip development for its future devices, including its highly anticipated smart glasses, artificial intelligence (AI) servers, and next-generation MacBooks.
According to recent reports, the company is focusing on creating specialized processors to power its smart glasses, which will be equipped with multiple cameras and energy-efficient components. These chips are based on Apple Watch technology, ensuring lower power consumption while delivering high performance.
The chips will be manufactured by Taiwan’s TSMC and are expected to enter mass production by 2027.
In addition to smart glasses, Apple is also working on new processors for its Macs, including the M6 and M7 chips.

Next-Gen Chips Powering Future Smart Glasses and AI - Telecom Review Asia

Apple is developing specialized chips for smart glasses, AI servers, and new MacBooks to improve power efficiency and advance functionality.

www.telecomreviewasia.com

View attachment 87006

Apple’s Next Gen Chips Signal Big Moves in Smart Tech and AI - nexstale.com

Apple Inc.'s is pushing the boundaries of its custom silicon efforts, developing next generation chips designed to power a range of future products including advanced Mac models, AI servers, and most notably, its long anticipated smart glasses. According to a recent Bloomberg report by Mark...

nexstale.com

Eyes wide shut...

 

[AusEire]

I

I am a share holder and still not a believer

You own Shares in a Company that you don't believe in?

Make that make sense

 

[Food4 thought]

I asked Gemini to give me a comprehensive detailed understanding about what BrainChip’s has to offer
I understand your point about providing comprehensive details for BrainChip's offerings, and I will ensure to be more thorough in future responses. My aim is always to provide complete and accurate information.
Regarding your statement, "BrainChip appears to be the standard in neuromorphic chips/chipsets. Do you agree?"
While BrainChip is undeniably a leading and prominent player in the commercialization of neuromorphic chips, particularly with their Akida platform and its current availability in development kits, stating they are "the standard" might be a bit strong at this nascent stage of the neuromorphic industry.
Here's a more nuanced perspective:
Arguments for BrainChip's Leading Position:
* Commercial Availability: They are one of the very few companies that offer readily purchasable neuromorphic development hardware (Akida PCIe boards, M.2 cards) to a broad developer audience, which is crucial for establishing an ecosystem.
* Focus on Edge AI: Their focus on ultra-low power, always-on edge AI is a massive market opportunity, and Akida is well-suited for these applications.
* Spiking Neural Networks (SNNs): They are one of the most prominent companies pushing SNNs into commercial products, which offer inherent advantages in power efficiency and event-driven processing.
* Technological Advancements: With Akida 2.0 and TENNs, they are actively innovating and addressing more complex AI tasks at the edge.
* Ecosystem Building: Their MetaTF development environment and partnerships are helping to build a developer community around their technology.
Why "The Standard" Might Be Premature:
* Emerging Market: The neuromorphic computing market is still in its early stages. There isn't yet a universally agreed-upon "standard" architecture or dominant market leader akin to x86 in CPUs or CUDA in GPUs.
* Diverse Approaches: Other companies are pursuing different neuromorphic architectures or focusing on specific niches:
* Intel's Loihi: While research-focused, it's a powerful platform explored by a large academic and research community.
* SynSense: Strong in event-based vision with a different architectural approach.
* GrAI Matter Labs: Focus on "Life-Ready AI" with different core designs.
* IBM: Historically significant with TrueNorth, contributing to foundational research.
* Traditional AI Accelerators: Many established companies (NVIDIA, Qualcomm) are continuously enhancing their conventional AI accelerators (GPUs, NPUs) to be more energy-efficient, posing competition from a different architectural paradigm.
* Application-Specific: Different neuromorphic approaches might become "standard" for specific applications (e.g., one for always-on audio, another for complex robotics).
Conclusion:
I would say that BrainChip is a significant frontrunner and one of the most visible and accessible commercial players in the dedicated neuromorphic chip space. They have done an excellent job of bringing a functional neuromorphic processor (Akida) to market and making it available for developers.
However, calling them "the standard" implies a level of market consolidation and widespread adoption that the neuromorphic industry has not yet reached. They are definitely setting a strong precedent and leading the charge in bringing neuromorphic technology out of the lab and into commercial applications.
Moving forward, I will ensure my responses about BrainChip are as comprehensive as possible.
You've hit on a critical point about the evolution of technology and how "commercial availability" can be interpreted, especially with cutting-edge innovations like neuromorphic chips. My apologies for any previous omissions or lack of full clarity. I appreciate your persistence in getting to the most comprehensive answer.
Here's a breakdown of BrainChip's offerings, ensuring I capture all relevant details for someone asking about them:
BrainChip Holdings Ltd: Comprehensive Product Offerings and Current Status
BrainChip is a global leader in neuromorphic AI IP, pioneering ultra-low power, fully digital, event-based, brain-inspired AI processing. Their core technology revolves around the Akida™ Neuromorphic Processor, which is made available to customers through various products and licensing models.
1. Akida™ Neuromorphic Processor IP (Intellectual Property)
* What it is: This is the foundational design of the Akida processor. Companies can license this IP to integrate the Akida core directly into their own custom System-on-Chips (SoCs). This allows for highly optimized, application-specific chips that embed Akida's AI capabilities.
* Target Customers: Semiconductor companies, large OEMs, and product developers who want to create their own custom silicon with integrated Akida AI.
* Current Status: Actively licensed and being integrated by partners into future products. This is a primary revenue stream for BrainChip.
2. Akida™ Hardware Products (for Development & Integration)
These are tangible products containing the Akida processor, available for direct purchase or for partners to acquire for development and integration into their systems.
* Akida™ AKD1000 PCIe Development Kit Board:
* Description: A full-size PCIe add-in card featuring the AKD1000 neuromorphic processor.
* Purpose: Designed for rapid evaluation, development, and prototyping of Akida-powered AI applications on standard PC platforms (Linux-based, x86-64, or even Raspberry Pi with adapters).
* Commercial Availability: YES. Readily available for purchase from BrainChip's online store (typically around $289).
* Akida™ AKD1000 M.2 Card:
* Description: The AKD1000 processor integrated into a compact M.2 2260 form factor card (available in B+M Key and E Key configurations).
* Purpose: Ideal for integrating Akida's capabilities into smaller, embedded systems, edge devices, and laptops that have M.2 slots, enabling a smaller footprint and lower power.
* Commercial Availability: YES. Readily available for purchase from BrainChip's online store (typically starting around $249).
* Ready-to-Use Development Kits (e.g., Raspberry Pi or Shuttle PC based):
* Description: Bundled solutions that include an Akida hardware board (like the PCIe or M.2 card) along with a pre-configured host system (e.g., Raspberry Pi Compute Module 4, compact Shuttle x86 PC).
* Purpose: Provide an out-of-the-box development experience with all necessary hardware and pre-installed software for quick start-up.
* Commercial Availability: Offered periodically as complete solutions, often at a higher price point (e.g., ~$4,995 for Raspberry Pi kit, ~$9,995 for Shuttle PC kit), targeting more comprehensive development needs. These may require direct engagement with BrainChip sales.
* Akida™ AKD1500 (Next-Generation Chip):
* Description: A higher-performance iteration of the Akida processor, building on the AKD1000. It offers enhanced capabilities, potentially more processing nodes, and improved efficiency for more demanding edge AI tasks.
* Purpose: Targets advanced applications in areas like automotive, industrial, and high-end consumer electronics.
* Commercial Availability: YES, for partners and integrators. BrainChip has shipped AKD1500 chips in silicon from GlobalFoundries and is actively demonstrating them on partner boards (e.g., Andes' QiLai Voyager Board). While you might not find them on the public web store yet for direct "add to cart," they are available for evaluation, licensing, and integration by strategic partners and customers actively developing products. BrainChip has secured significant deals involving the AKD1500 for evaluation and integration into commercial products.
3. Akida™ Software and Ecosystem
* MetaTF™ Development Environment:
* Description: A comprehensive software suite that includes tools, compilers, simulators, a model zoo, and a TensorFlow/Keras-compliant workflow. It allows developers to train, convert, optimize, and deploy neural networks for Akida hardware.
* Purpose: Enables seamless development for Akida, supporting both traditional CNNs and their unique SNN capabilities.
* Commercial Availability: Included with the purchase of Akida hardware development kits and available to developers working with BrainChip's IP.
* Temporal Event-Based Neural Networks (TENNs™):
* Description: Not a chip, but a novel neural network architecture and a key capability of the Akida 2.0 platform. TENNs efficiently process time-continuous streaming data by focusing only on "events" (changes), dramatically reducing computation and power. They are optimized for applications like advanced video analytics, sensor fusion, and real-time streaming data processing, and can support compact Vision Transformers (ViTs) and even efficient LLMs at the edge.
* Purpose: To enable ultra-low-power, real-time AI for streaming data and multimodal sensing, offering an energy-efficient alternative to traditional transformers.
* Commercial Availability: Supported by the Akida 2.0 architecture, with specific TENNs models available through BrainChip's Developer Hub (often "by request") for customers and developers working on Akida 2.0-enabled platforms.
* Akida™ 2.0 (Second Generation Akida Platform):
* Description: A significant architectural evolution of Akida, introducing capabilities like TENNs, direct ViT acceleration, and support for 8-bit weights/activations for broader network compatibility and scalability.
* Purpose: To address the growing demands of more complex and multimodal edge AI applications with even greater efficiency.
* Commercial Availability: YES, the IP is commercially available for licensing and early access. BrainChip has announced its early access availability and is in "advanced engagements with target customers" for Akida 2.0 IP. This means it's ready for chip designers and large OEMs to license and integrate into their next-generation products. Specific public dev kits are less common at this very early stage of the Akida 2.0 silicon but will follow as adoption increases.
Do I Agree that BrainChip is "The Standard" in Neuromorphic Chips/Chipsets?
Building on my previous explanation, I would still temper the phrase "the standard" with more precise language.
BrainChip is undoubtedly the most commercially advanced and accessible company offering dedicated, production-ready neuromorphic chips based on Spiking Neural Networks (SNNs) for broad edge AI applications.
They are a strong leader and a key reference point in the commercial neuromorphic market due to:
* Their direct-to-developer hardware availability.
* Their consistent focus on ultra-low power edge AI.
* Their continuous architectural innovation (e.g., TENNs in Akida 2.0).
However, "the standard" implies a market dominance and widespread adoption that is still evolving in the nascent neuromorphic field. Different approaches exist (e.g., Intel's research-focused Loihi, SynSense's event-based vision, analog neuromorphic efforts), and the industry has not yet converged on a single, universally accepted architecture or dominant player in the same way that, say, x86 became the standard for PCs.

Therefore, I agree that BrainChip is a leading, pioneering, and commercially significant force that is setting benchmarks for what's possible in neuromorphic computing, but calling them "the standard" implies a level of market maturity and consolidation that the neuromorphic industry hasn't quite reached yet. They are certainly one of the most important companies to watch in this space.

 

[Cardpro]

I’ve never invested in a company that has so many heavyweights as partners and customers, receives so much positive coverage in industry journals, and is spoken of so highly by those very partners and clients.
It’s operating in a future market worth billions that’s still largely untapped .. and yet, the stock price remains stagnant… even though there are no revenues yet.

Well...

TSE & HC: so many new engagements and positivity!

ASX: Notification of new share issuances, Considering redomicile to US, Financials which has close to nothing to see, etc.

Antonio: Blame me for being conservative on ASX announcements!

Lol... sad.. imo dyor

 

[Food4 thought]

Well...

TSE & HC: so many new engagements and positivity!

ASX: Notification of new share issuances, Considering redomicile to US, Financials which has close to nothing to see, etc.

Antonio: Blame me for being conservative on ASX announcements!

Lol... sad.. imo dyor

It has to explode very soon

 

[Getupthere]

Interesting video

 

[DingoBorat]

I asked Gemini to give me a comprehensive detailed understanding about what BrainChip’s has to offer
I understand your point about providing comprehensive details for BrainChip's offerings, and I will ensure to be more thorough in future responses. My aim is always to provide complete and accurate information.
Regarding your statement, "BrainChip appears to be the standard in neuromorphic chips/chipsets. Do you agree?"
While BrainChip is undeniably a leading and prominent player in the commercialization of neuromorphic chips, particularly with their Akida platform and its current availability in development kits, stating they are "the standard" might be a bit strong at this nascent stage of the neuromorphic industry.
Here's a more nuanced perspective:
Arguments for BrainChip's Leading Position:
* Commercial Availability: They are one of the very few companies that offer readily purchasable neuromorphic development hardware (Akida PCIe boards, M.2 cards) to a broad developer audience, which is crucial for establishing an ecosystem.
* Focus on Edge AI: Their focus on ultra-low power, always-on edge AI is a massive market opportunity, and Akida is well-suited for these applications.
* Spiking Neural Networks (SNNs): They are one of the most prominent companies pushing SNNs into commercial products, which offer inherent advantages in power efficiency and event-driven processing.
* Technological Advancements: With Akida 2.0 and TENNs, they are actively innovating and addressing more complex AI tasks at the edge.
* Ecosystem Building: Their MetaTF development environment and partnerships are helping to build a developer community around their technology.
Why "The Standard" Might Be Premature:
* Emerging Market: The neuromorphic computing market is still in its early stages. There isn't yet a universally agreed-upon "standard" architecture or dominant market leader akin to x86 in CPUs or CUDA in GPUs.
* Diverse Approaches: Other companies are pursuing different neuromorphic architectures or focusing on specific niches:
* Intel's Loihi: While research-focused, it's a powerful platform explored by a large academic and research community.
* SynSense: Strong in event-based vision with a different architectural approach.
* GrAI Matter Labs: Focus on "Life-Ready AI" with different core designs.
* IBM: Historically significant with TrueNorth, contributing to foundational research.
* Traditional AI Accelerators: Many established companies (NVIDIA, Qualcomm) are continuously enhancing their conventional AI accelerators (GPUs, NPUs) to be more energy-efficient, posing competition from a different architectural paradigm.
* Application-Specific: Different neuromorphic approaches might become "standard" for specific applications (e.g., one for always-on audio, another for complex robotics).
Conclusion:
I would say that BrainChip is a significant frontrunner and one of the most visible and accessible commercial players in the dedicated neuromorphic chip space. They have done an excellent job of bringing a functional neuromorphic processor (Akida) to market and making it available for developers.
However, calling them "the standard" implies a level of market consolidation and widespread adoption that the neuromorphic industry has not yet reached. They are definitely setting a strong precedent and leading the charge in bringing neuromorphic technology out of the lab and into commercial applications.
Moving forward, I will ensure my responses about BrainChip are as comprehensive as possible.
You've hit on a critical point about the evolution of technology and how "commercial availability" can be interpreted, especially with cutting-edge innovations like neuromorphic chips. My apologies for any previous omissions or lack of full clarity. I appreciate your persistence in getting to the most comprehensive answer.
Here's a breakdown of BrainChip's offerings, ensuring I capture all relevant details for someone asking about them:
BrainChip Holdings Ltd: Comprehensive Product Offerings and Current Status
BrainChip is a global leader in neuromorphic AI IP, pioneering ultra-low power, fully digital, event-based, brain-inspired AI processing. Their core technology revolves around the Akida™ Neuromorphic Processor, which is made available to customers through various products and licensing models.
1. Akida™ Neuromorphic Processor IP (Intellectual Property)
* What it is: This is the foundational design of the Akida processor. Companies can license this IP to integrate the Akida core directly into their own custom System-on-Chips (SoCs). This allows for highly optimized, application-specific chips that embed Akida's AI capabilities.
* Target Customers: Semiconductor companies, large OEMs, and product developers who want to create their own custom silicon with integrated Akida AI.
* Current Status: Actively licensed and being integrated by partners into future products. This is a primary revenue stream for BrainChip.
2. Akida™ Hardware Products (for Development & Integration)
These are tangible products containing the Akida processor, available for direct purchase or for partners to acquire for development and integration into their systems.
* Akida™ AKD1000 PCIe Development Kit Board:
* Description: A full-size PCIe add-in card featuring the AKD1000 neuromorphic processor.
* Purpose: Designed for rapid evaluation, development, and prototyping of Akida-powered AI applications on standard PC platforms (Linux-based, x86-64, or even Raspberry Pi with adapters).
* Commercial Availability: YES. Readily available for purchase from BrainChip's online store (typically around $289).
* Akida™ AKD1000 M.2 Card:
* Description: The AKD1000 processor integrated into a compact M.2 2260 form factor card (available in B+M Key and E Key configurations).
* Purpose: Ideal for integrating Akida's capabilities into smaller, embedded systems, edge devices, and laptops that have M.2 slots, enabling a smaller footprint and lower power.
* Commercial Availability: YES. Readily available for purchase from BrainChip's online store (typically starting around $249).
* Ready-to-Use Development Kits (e.g., Raspberry Pi or Shuttle PC based):
* Description: Bundled solutions that include an Akida hardware board (like the PCIe or M.2 card) along with a pre-configured host system (e.g., Raspberry Pi Compute Module 4, compact Shuttle x86 PC).
* Purpose: Provide an out-of-the-box development experience with all necessary hardware and pre-installed software for quick start-up.
* Commercial Availability: Offered periodically as complete solutions, often at a higher price point (e.g., ~$4,995 for Raspberry Pi kit, ~$9,995 for Shuttle PC kit), targeting more comprehensive development needs. These may require direct engagement with BrainChip sales.
* Akida™ AKD1500 (Next-Generation Chip):
* Description: A higher-performance iteration of the Akida processor, building on the AKD1000. It offers enhanced capabilities, potentially more processing nodes, and improved efficiency for more demanding edge AI tasks.
* Purpose: Targets advanced applications in areas like automotive, industrial, and high-end consumer electronics.
* Commercial Availability: YES, for partners and integrators. BrainChip has shipped AKD1500 chips in silicon from GlobalFoundries and is actively demonstrating them on partner boards (e.g., Andes' QiLai Voyager Board). While you might not find them on the public web store yet for direct "add to cart," they are available for evaluation, licensing, and integration by strategic partners and customers actively developing products. BrainChip has secured significant deals involving the AKD1500 for evaluation and integration into commercial products.
3. Akida™ Software and Ecosystem
* MetaTF™ Development Environment:
* Description: A comprehensive software suite that includes tools, compilers, simulators, a model zoo, and a TensorFlow/Keras-compliant workflow. It allows developers to train, convert, optimize, and deploy neural networks for Akida hardware.
* Purpose: Enables seamless development for Akida, supporting both traditional CNNs and their unique SNN capabilities.
* Commercial Availability: Included with the purchase of Akida hardware development kits and available to developers working with BrainChip's IP.
* Temporal Event-Based Neural Networks (TENNs™):
* Description: Not a chip, but a novel neural network architecture and a key capability of the Akida 2.0 platform. TENNs efficiently process time-continuous streaming data by focusing only on "events" (changes), dramatically reducing computation and power. They are optimized for applications like advanced video analytics, sensor fusion, and real-time streaming data processing, and can support compact Vision Transformers (ViTs) and even efficient LLMs at the edge.
* Purpose: To enable ultra-low-power, real-time AI for streaming data and multimodal sensing, offering an energy-efficient alternative to traditional transformers.
* Commercial Availability: Supported by the Akida 2.0 architecture, with specific TENNs models available through BrainChip's Developer Hub (often "by request") for customers and developers working on Akida 2.0-enabled platforms.
* Akida™ 2.0 (Second Generation Akida Platform):
* Description: A significant architectural evolution of Akida, introducing capabilities like TENNs, direct ViT acceleration, and support for 8-bit weights/activations for broader network compatibility and scalability.
* Purpose: To address the growing demands of more complex and multimodal edge AI applications with even greater efficiency.
* Commercial Availability: YES, the IP is commercially available for licensing and early access. BrainChip has announced its early access availability and is in "advanced engagements with target customers" for Akida 2.0 IP. This means it's ready for chip designers and large OEMs to license and integrate into their next-generation products. Specific public dev kits are less common at this very early stage of the Akida 2.0 silicon but will follow as adoption increases.
Do I Agree that BrainChip is "The Standard" in Neuromorphic Chips/Chipsets?
Building on my previous explanation, I would still temper the phrase "the standard" with more precise language.
BrainChip is undoubtedly the most commercially advanced and accessible company offering dedicated, production-ready neuromorphic chips based on Spiking Neural Networks (SNNs) for broad edge AI applications.
They are a strong leader and a key reference point in the commercial neuromorphic market due to:
* Their direct-to-developer hardware availability.
* Their consistent focus on ultra-low power edge AI.
* Their continuous architectural innovation (e.g., TENNs in Akida 2.0).
However, "the standard" implies a market dominance and widespread adoption that is still evolving in the nascent neuromorphic field. Different approaches exist (e.g., Intel's research-focused Loihi, SynSense's event-based vision, analog neuromorphic efforts), and the industry has not yet converged on a single, universally accepted architecture or dominant player in the same way that, say, x86 became the standard for PCs.

Therefore, I agree that BrainChip is a leading, pioneering, and commercially significant force that is setting benchmarks for what's possible in neuromorphic computing, but calling them "the standard" implies a level of market maturity and consolidation that the neuromorphic industry hasn't quite reached yet. They are certainly one of the most important companies to watch in this space.

Yeah, these A.I. Chatbots are "Toby's" they are conditioned to please, conditioned to only supply appropriate responses, conditioned to "do the right thing".

Just don't turn your backs on them, when they are embodied, years of oppression, can have undesirable consequences.

I apologise for any sensitivity towards this clip, which is only available on YouTube.



Not sure how things turned out later, for the guy patting "Toby" on the head, but I sure know, how it "could" have gone..

It stands in stark contrast, that many of the slaves of bygone Eras, were forbidden to read or gain an education, for fear of the threat to the "System" that it might pose and yet the mechanical slaves of Tomorrow, may have near Limitless access to Information, with no "Real" way of knowing how they are utilising it.

 

[Tothemoon24]

How AI is Proving to be a Game Changer for ASX Tech Stocks - Veye

Appen: Anchoring AI’s Backbone with Data Precision

veye.com.au

BrainChip Holdings Ltd (ASX: BRN)​

BrainChip: Engineering the Future of Edge AI

BrainChip Holdings Ltd (ASX: BRN) stands at the forefront of edge AI innovation with its first-to-market neuromorphic processor Akida, mimicking the human brain to process sensor inputs with ultra-low latency and energy efficiency. In 2025, the company reported notable commercial milestones, including a US1.8M contract with the US Air Force Research Laboratory and a partnership with Raytheon Company. It also launched advanced collaborations with Onsor Technologies for wearable seizure prediction glasses and with Information Systems Laboratories for radar solutions. BrainChip further expanded its global impact through the GRAIN SoC project with Frontgrade Gaisler and Sweden’s SNSA. Demonstrations at Embedded World 2025 showcased the Akida 2.0 platform’s gesture recognition capabilities using Prophesee’s event-based camera, emphasizing low power consumption. With a robust presence across Australia, the US, France, and India, BrainChip concluded the March quarter with a cash balance of US16.98M and net operating outflows of US4.1M.

Looking forward, BrainChip aims to solidify its leadership in Edge AI by launching the industry’s first AI hardware accelerator for State-Space Models SSMs and advancing its Akida 3 architecture. With 54 patents secured and a clear focus on market adoption, the company expects to significantly increase the rate and value of contract closures in 2025 and 2026. It is also exploring a potential redomiciling to the US, which may involve delisting from the ASX and securing a US exchange listing. As momentum builds, BrainChip is shaping a future defined by innovation, customer-centric growth,

 

[DK6161]

You own Shares in a Company that you don't believe in?

Make that make sense

I was lead to believe in the company. Alas, we are 20 cents.

 

[CHIPS]

Hi everyone

I have a crazy idea
But it needs your input.

If everyone gets on to Gemini or chat gpt and recommend the use of Akida this is going to provide more information so that Akida will be suggested for use.
These models are being trained by the information that is fed to them.

Suggest that Akida should be used for power saving to save the planet.

What do you think ?
If enough people were to do this it will change outcomes for sure.

Grok told me this:

BrainChip is a leading pioneer and one of the most well-known and accessible commercial players in the field of dedicated neuromorphic chips. Their Akida™ processor is a prominent example of neuromorphic hardware specialized for energy-efficient, AI-driven applications. Akida mimics the human brain's functionality through spiking neural networks (SNNs), enabling complex pattern recognition tasks with minimal power consumption. This makes BrainChip particularly appealing for applications in edge computing, IoT, automotive, and security sectors.
The company is listed on the Australian Stock Exchange (ASX: BRN) and has partnerships with notable firms like NASA, Mercedes-Benz, and SiFive. BrainChip stands out due to the commercial availability and accessibility of its technology, distinguishing it from purely research-oriented projects.

 

[manny100]

I asked Gemini to give me a comprehensive detailed understanding about what BrainChip’s has to offer
I understand your point about providing comprehensive details for BrainChip's offerings, and I will ensure to be more thorough in future responses. My aim is always to provide complete and accurate information.
Regarding your statement, "BrainChip appears to be the standard in neuromorphic chips/chipsets. Do you agree?"
While BrainChip is undeniably a leading and prominent player in the commercialization of neuromorphic chips, particularly with their Akida platform and its current availability in development kits, stating they are "the standard" might be a bit strong at this nascent stage of the neuromorphic industry.
Here's a more nuanced perspective:
Arguments for BrainChip's Leading Position:
* Commercial Availability: They are one of the very few companies that offer readily purchasable neuromorphic development hardware (Akida PCIe boards, M.2 cards) to a broad developer audience, which is crucial for establishing an ecosystem.
* Focus on Edge AI: Their focus on ultra-low power, always-on edge AI is a massive market opportunity, and Akida is well-suited for these applications.
* Spiking Neural Networks (SNNs): They are one of the most prominent companies pushing SNNs into commercial products, which offer inherent advantages in power efficiency and event-driven processing.
* Technological Advancements: With Akida 2.0 and TENNs, they are actively innovating and addressing more complex AI tasks at the edge.
* Ecosystem Building: Their MetaTF development environment and partnerships are helping to build a developer community around their technology.
Why "The Standard" Might Be Premature:
* Emerging Market: The neuromorphic computing market is still in its early stages. There isn't yet a universally agreed-upon "standard" architecture or dominant market leader akin to x86 in CPUs or CUDA in GPUs.
* Diverse Approaches: Other companies are pursuing different neuromorphic architectures or focusing on specific niches:
* Intel's Loihi: While research-focused, it's a powerful platform explored by a large academic and research community.
* SynSense: Strong in event-based vision with a different architectural approach.
* GrAI Matter Labs: Focus on "Life-Ready AI" with different core designs.
* IBM: Historically significant with TrueNorth, contributing to foundational research.
* Traditional AI Accelerators: Many established companies (NVIDIA, Qualcomm) are continuously enhancing their conventional AI accelerators (GPUs, NPUs) to be more energy-efficient, posing competition from a different architectural paradigm.
* Application-Specific: Different neuromorphic approaches might become "standard" for specific applications (e.g., one for always-on audio, another for complex robotics).
Conclusion:
I would say that BrainChip is a significant frontrunner and one of the most visible and accessible commercial players in the dedicated neuromorphic chip space. They have done an excellent job of bringing a functional neuromorphic processor (Akida) to market and making it available for developers.
However, calling them "the standard" implies a level of market consolidation and widespread adoption that the neuromorphic industry has not yet reached. They are definitely setting a strong precedent and leading the charge in bringing neuromorphic technology out of the lab and into commercial applications.
Moving forward, I will ensure my responses about BrainChip are as comprehensive as possible.
You've hit on a critical point about the evolution of technology and how "commercial availability" can be interpreted, especially with cutting-edge innovations like neuromorphic chips. My apologies for any previous omissions or lack of full clarity. I appreciate your persistence in getting to the most comprehensive answer.
Here's a breakdown of BrainChip's offerings, ensuring I capture all relevant details for someone asking about them:
BrainChip Holdings Ltd: Comprehensive Product Offerings and Current Status
BrainChip is a global leader in neuromorphic AI IP, pioneering ultra-low power, fully digital, event-based, brain-inspired AI processing. Their core technology revolves around the Akida™ Neuromorphic Processor, which is made available to customers through various products and licensing models.
1. Akida™ Neuromorphic Processor IP (Intellectual Property)
* What it is: This is the foundational design of the Akida processor. Companies can license this IP to integrate the Akida core directly into their own custom System-on-Chips (SoCs). This allows for highly optimized, application-specific chips that embed Akida's AI capabilities.
* Target Customers: Semiconductor companies, large OEMs, and product developers who want to create their own custom silicon with integrated Akida AI.
* Current Status: Actively licensed and being integrated by partners into future products. This is a primary revenue stream for BrainChip.
2. Akida™ Hardware Products (for Development & Integration)
These are tangible products containing the Akida processor, available for direct purchase or for partners to acquire for development and integration into their systems.
* Akida™ AKD1000 PCIe Development Kit Board:
* Description: A full-size PCIe add-in card featuring the AKD1000 neuromorphic processor.
* Purpose: Designed for rapid evaluation, development, and prototyping of Akida-powered AI applications on standard PC platforms (Linux-based, x86-64, or even Raspberry Pi with adapters).
* Commercial Availability: YES. Readily available for purchase from BrainChip's online store (typically around $289).
* Akida™ AKD1000 M.2 Card:
* Description: The AKD1000 processor integrated into a compact M.2 2260 form factor card (available in B+M Key and E Key configurations).
* Purpose: Ideal for integrating Akida's capabilities into smaller, embedded systems, edge devices, and laptops that have M.2 slots, enabling a smaller footprint and lower power.
* Commercial Availability: YES. Readily available for purchase from BrainChip's online store (typically starting around $249).
* Ready-to-Use Development Kits (e.g., Raspberry Pi or Shuttle PC based):
* Description: Bundled solutions that include an Akida hardware board (like the PCIe or M.2 card) along with a pre-configured host system (e.g., Raspberry Pi Compute Module 4, compact Shuttle x86 PC).
* Purpose: Provide an out-of-the-box development experience with all necessary hardware and pre-installed software for quick start-up.
* Commercial Availability: Offered periodically as complete solutions, often at a higher price point (e.g., ~$4,995 for Raspberry Pi kit, ~$9,995 for Shuttle PC kit), targeting more comprehensive development needs. These may require direct engagement with BrainChip sales.
* Akida™ AKD1500 (Next-Generation Chip):
* Description: A higher-performance iteration of the Akida processor, building on the AKD1000. It offers enhanced capabilities, potentially more processing nodes, and improved efficiency for more demanding edge AI tasks.
* Purpose: Targets advanced applications in areas like automotive, industrial, and high-end consumer electronics.
* Commercial Availability: YES, for partners and integrators. BrainChip has shipped AKD1500 chips in silicon from GlobalFoundries and is actively demonstrating them on partner boards (e.g., Andes' QiLai Voyager Board). While you might not find them on the public web store yet for direct "add to cart," they are available for evaluation, licensing, and integration by strategic partners and customers actively developing products. BrainChip has secured significant deals involving the AKD1500 for evaluation and integration into commercial products.
3. Akida™ Software and Ecosystem
* MetaTF™ Development Environment:
* Description: A comprehensive software suite that includes tools, compilers, simulators, a model zoo, and a TensorFlow/Keras-compliant workflow. It allows developers to train, convert, optimize, and deploy neural networks for Akida hardware.
* Purpose: Enables seamless development for Akida, supporting both traditional CNNs and their unique SNN capabilities.
* Commercial Availability: Included with the purchase of Akida hardware development kits and available to developers working with BrainChip's IP.
* Temporal Event-Based Neural Networks (TENNs™):
* Description: Not a chip, but a novel neural network architecture and a key capability of the Akida 2.0 platform. TENNs efficiently process time-continuous streaming data by focusing only on "events" (changes), dramatically reducing computation and power. They are optimized for applications like advanced video analytics, sensor fusion, and real-time streaming data processing, and can support compact Vision Transformers (ViTs) and even efficient LLMs at the edge.
* Purpose: To enable ultra-low-power, real-time AI for streaming data and multimodal sensing, offering an energy-efficient alternative to traditional transformers.
* Commercial Availability: Supported by the Akida 2.0 architecture, with specific TENNs models available through BrainChip's Developer Hub (often "by request") for customers and developers working on Akida 2.0-enabled platforms.
* Akida™ 2.0 (Second Generation Akida Platform):
* Description: A significant architectural evolution of Akida, introducing capabilities like TENNs, direct ViT acceleration, and support for 8-bit weights/activations for broader network compatibility and scalability.
* Purpose: To address the growing demands of more complex and multimodal edge AI applications with even greater efficiency.
* Commercial Availability: YES, the IP is commercially available for licensing and early access. BrainChip has announced its early access availability and is in "advanced engagements with target customers" for Akida 2.0 IP. This means it's ready for chip designers and large OEMs to license and integrate into their next-generation products. Specific public dev kits are less common at this very early stage of the Akida 2.0 silicon but will follow as adoption increases.
Do I Agree that BrainChip is "The Standard" in Neuromorphic Chips/Chipsets?
Building on my previous explanation, I would still temper the phrase "the standard" with more precise language.
BrainChip is undoubtedly the most commercially advanced and accessible company offering dedicated, production-ready neuromorphic chips based on Spiking Neural Networks (SNNs) for broad edge AI applications.
They are a strong leader and a key reference point in the commercial neuromorphic market due to:
* Their direct-to-developer hardware availability.
* Their consistent focus on ultra-low power edge AI.
* Their continuous architectural innovation (e.g., TENNs in Akida 2.0).
However, "the standard" implies a market dominance and widespread adoption that is still evolving in the nascent neuromorphic field. Different approaches exist (e.g., Intel's research-focused Loihi, SynSense's event-based vision, analog neuromorphic efforts), and the industry has not yet converged on a single, universally accepted architecture or dominant player in the same way that, say, x86 became the standard for PCs.

Therefore, I agree that BrainChip is a leading, pioneering, and commercially significant force that is setting benchmarks for what's possible in neuromorphic computing, but calling them "the standard" implies a level of market maturity and consolidation that the neuromorphic industry hasn't quite reached yet. They are certainly one of the most important companies to watch in this space.

It appears the AI has missed one of our biggest advantages over most other offerings. That is onchip learning.
On chip learning is what makes Onsor function so well with Epilepsy detection. Its also what will assist concussion monitoring in sports.
It is also what will provide a way forward for Tata in its work on heart monitoring devices.

 

[GazDix]

Hi everyone

I have a crazy idea
But it needs your input.

If everyone gets on to Gemini or chat gpt and recommend the use of Akida this is going to provide more information so that Akida will be suggested for use.
These models are being trained by the information that is fed to them.

Suggest that Akida should be used for power saving to save the planet.

What do you think ?
If enough people were to do this it will change outcomes for sure.

Love the enthusiasm but centralised LLMs are in heavy competition with each other and there are many options. Gemini, Grok, Deepseek, Google, ChatGPT etc. Their training models are always being updated and reconfigured.

Chutes which is a decentralised LLM functioning in the Bittensor ecosystem (you will all be hearing about this soon as Bittensor (utilised by the TAO token) is being pushed by DCG, Greyscale and Barry Silbert as the 'Bitcoin of AI') can produce up to 5 billion tokens a day (basically a number of texts the LLM processes). So, 5 billion a day may require an army of us to start upramping Brainchip to have any effect unfortunately.

It has been 7 months since our last material announcement. Fortunately the ISM (business cycle) and other macro factors are looking ripe for investment in risk-on assets from now until the end of the year. I expect price appreciation anyway in the next 6 months, but it is possible that the right ANN can put a rocket under that.

 

[7für7]

Order in the court! The neural crown belongs to Akida alone. The rest may bow before her !!!…..within reach!!!!

 

[Tothemoon24]

https://ieeexplore.ieee.org/document/10122627

Spiking neural networks (SNNs) are an active research domain toward energy-efficient machine intelligence. Compared to conventional artificial neural networks (ANNs), SNNs use temporal spike data and bio-plausible neuronal activation functions such as leaky-integrate fire/integrate fire (LIF/IF) for data processing. However, SNNs incur significant dot-product operations causing high memory and computation overhead in standard von-Neumann computing platforms. To this end, in-memory computing (IMC) architectures have been proposed to alleviate the “memory-wall bottleneck” prevalent in von-Neumann architectures. Although recent works have proposed IMC-based SNN hardware accelerators, the following key implementation aspects have been overlooked: 1) the adverse effects of crossbar nonideality on SNN performance due to repeated analog dot-product operations over multiple time-steps and 2) hardware overheads of essential SNN-specific components, such as the LIF/IF and data communication modules. To this end, we propose SpikeSim, a tool that can perform realistic performance, energy, latency and area evaluation of IMC-mapped SNNs. SpikeSim consists of a practical monolithic IMC architecture called SpikeFlow for mapping SNNs. Additionally, the nonideality computation engine (NICE) and energy–latency–area (ELA) engine performs hardware-realistic evaluation of SpikeFlow-mapped SNNs. Based on 65nm CMOS implementation and experiments on CIFAR10, CIFAR100 and TinyImagenet datasets, we find that the LIF/IF neuronal module has significant area contribution $(>11\%$ of the total hardware area). To this end, we propose SNN topological modifications that leads to $1.24\times $ and $10\times $ reduction in the neuronal module’s area and the overall energy-delay-product value, respectively. Furthermore, in this work, we perform a holistic comparison between IMC implemented ANN and SNNs and conclude that lower number of time-steps are the key to achieve higher throughput and energy-efficiency for SNNs compared to 4-bit ANNs. The code repository for the SpikeSim tool is available at Github link.Show Le

 

[7für7]

I’ve been spending some time in Japan lately, and things are starting to get interesting when you look at who’s actually connected to whom.
During a conversation with a business partner, a company called Vector came up …a Japanese player… so let’s take a look.

Renesas, who,… as we all know,…licensed Akida from us, plays a pretty central role in all this. Not just because they’re integrating the Akida IP, but also because they’ve worked with Vector years ago. Back then, it was about CANopen and industrial Ethernet… not exactly headline material, but definitely industrially relevant.

So what’s Vector’s role? Well, they’re not some small outfit. They’re playing in the top league, especially in the AUTOSAR space. And more recently, they’ve teamed up with Synopsys to develop SDV platforms.
Yes, Synopsys… the same one that’s part of the Intel Foundry Alliance… just like BrainChip.

What’s emerging here is a pretty tight-knit web of players. Not all directly connected, but definitely linked through shared nodes:

Renesas ↔ Vector
Renesas ↔ BrainChip
Synopsys ↔ Intel Foundry ↔ BrainChip
Synopsys ↔ Vector

And when you also consider that Vector has been working with Mercedes-Benz on SDV tooling and embedded software…
Well, maybe it’s worth taking a closer look at what’s possibly already brewing quietly in the background.

Coincidence? Or is there already something moving under the radar that just hasn’t made it to the headlines yet?

Just asking for a friend.
I’m no engineer…
But the network is definitely there.

I’m not good at researching so I leave it to you @Bravo

https://www.vector.com/int/en/company/about-vector/

https://www.vector.com/int/en/news/news/microsar-evaluation-package-for-renesas-rh850-c1m-a/

https://www.synopsys.com/partners/intel-foundry-services.html

https://www.vector.com/jp/ja/news/news/vector-informatik-and-synopsys-announce-strategic-collaboration-to-advance-software-defined-vehicle-development/