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Great positive recent article on Android Guides (translated from Italian) outlining Pico benefits, workings and potential.

If the below is achievable with Pico you'd like to believe the company have a competitive product here that they absolutely should be able to get some sort of market penetration sooner than later.



Akida Pico: The NPU that powers artificial intelligence in battery-powered, low-power devices​

  • Akida Pico integrates advanced artificial intelligence into ultra-low power consumption devices, such as wearables and medical sensors.
  • Its scalable and modular architecture allows you to adapt performance and energy consumption to the application.
  • The MetaTF development environment facilitates the rapid implementation of AI models with full support for TensorFlow and PyTorch.

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Isaac10/05/2025 05:19Updated on 10/05/2025 07:06

The progressive technological transformation driven by the’ artificial intelligence it is achieving unprecedented levels of efficiency and adaptability, especially in the low-power device industry. One of the great drivers of this revolution is BrainChip, a manufacturer that changed the rules of the game with Akida Pico, One ultra-low power NPU designed to bring AI to battery-powered devices and without constant access to traditional electricity networks.

Akida Pico: the revolution of ultra-efficient artificial intelligence for wearable devices​


Akida Pico stands out for its unique ability to perform AI tasks with power consumption less than one milliwatté. This level of efficiency leads to an unprecedented reduction in the typical power consumption of neural processing chips, allowing artificial intelligence to always be active even on devices with extremely low energy requirements.

Thanks to this innovation it is possible to integrate advanced artificial intelligence into Smart headphones, smartwatches, health bracelets, autonomous sensors, small household appliances and medical devicesé. Artificial intelligence is therefore no longer exclusive to complex and connected systems, but is now present in a discreet and continuous in the user's daily life through compact gadgets and wearable devices.

A big advantage of this NPU is that It does not require external server support or constant Internet connectivity., freeing the device from dependence on other larger systems or the cloud. This guarantees real edge processing (edge AI), fundamental for applications where latency, privacy and power consumption are determining factors.

El autonomous design The Akida Pico's capabilities allow it to function both as a standalone chip and as an integrated module into existing hardware platforms. His minimum size of only 0.12 mm² it facilitates implementation even in smaller devices or whose architecture requires maximum compactness.

Versatility of design, manufacturing and integration​


El Akida Pico It is produced with technology FDSOI at 22 nm (22FDX) by GlobalFoundries, one of the most efficient and convenient processes for chip manufacturing. Its architecture also allows it to be easily adapted or resized to even more advanced manufacturing processes, such as 12 nm and also 3 nm, depending on the needs of the supplements or the specific application for which the device is intended.

This degree of flexibility makes the NPU a perfect solution for both mass-produced products and high-end applications, allowing manufacturers to choose the ideal balance between cost and performance.


In its structure, the following are distinguished 150,000 transistors, which allow the execution of complex neural tasks such as Voice activation, keyword recognition, noise suppression, presence detection, personal assistants and much moreé. All this without requiring large amounts of internal memory, as it can be completed with chips SRAM external if the application requires it, going from the initial 0.12 mm² to just 0.18 mm² with 50 additional KB of memory.

For connection to the rest of the system components, Akida Pico incorporates a DMA and an AXI bus matrix, allowing direct integration with microcontrollers, main processors and other functional units of the device. Its ability to directly access memory via interfaces such as AHB, eMMC and GPIO increases its adaptability in ultra-low power consumption and mixed architecture environments.

For all these reasons, Akida Pico is not only small and efficient: it is also incredibly modular, which opens the door to its use in future intelligent devices which, for now, are still being conceptualized.

Main technical characteristics of the Akida Pico​


  • Consumption less than 1 milliwatt: guarantees continuous operation with batteries of at least 10 mAh, allowing the autonomy of sensors and equipment without the need for frequent recharging.
  • Minimum total area: 0.12 mm² in basic configuration, expandable to 0.18 mm² by adding SRAM memory.
  • Scalable production: Designed for 22nm lithographic processes, but adaptable to 12nm or more advanced technologies, even reaching 3nm for premium chips.
  • Pure digital architecture: Allows the acceleration of specific models of neural networks, facilitating real-time and low-latency responses to key events and signal processing at the edge.
  • Advanced interfaces: DMA connection, AXI bus, access to AHB and eMMC memories and easy integration with GPIO.
  • Complete scalability: It can adapt to the energy and computing needs of any device, from simple home automation sensors to smart home appliances and advanced wearable medical devices.
This combination of technical benefits makes Akida Pico a true benchmark for the next generation of smart devices, promoting the democratization of integrated artificial intelligence where it was previously impractical due to energy or space limitations.

What differentiates Akida Pico from other NPUs?​


In a context where artificial intelligence is often associated with large data centers or expensive hardware, Akida Pico represents a radical changeé. Its low power consumption and high performance make it particularly attractive for manufacturers and developers looking for Offer intelligent functionality in low-cost stand-alone devices or with extreme range requirements. which use low energy consumption components.

With Akida Pico it is possible for a remote control, motion detector, environmental sensor or small IoT device they have advanced artificial intelligence capabilities, such as pattern recognition, noise filtering and intelligent responses to events, without increasing weight, complexity or production costs.

Thanks to event-based architecture, the chip is able to filter false alarms, activating the host only when it detects a real event, significantly extending battery life and reducing the need to recharge or replace it.

This results in tangible benefits for the end user: more durable devices, less maintenance, greater privacy by no longer having to send data to servers, and a consistently smooth and reliable user experience.

Software development and compatibility platform​


Development on Akida Pico is supported by BrainChip's exclusive MetaTF software environment, which allows engineers to optimize and compile their own Temporal neural networks (TENN) directly to the NPU ecosystem.

One of the great advantages is the compatibility of MetaTF with TensorFlow, Keras and PyTorch, the most popular frameworks in the machine learning community. This means that developers can transfer their pre-trained models and deploy them to Akida Pico without having to learn new languages or methodologies, thus driving the rapid adoption and deployment of edge artificial intelligence projects.

The development environment offers:

  • Easy model compilation and optimization for ultra-efficient hardware.
  • Support for debugging, testing and training neural networks in real time.
  • Documentation and examples to facilitate the inclusion of both artificial intelligence beginners and embedded systems experts.
  • Ability to implement multimodal functions, which include vision, audio, presence detection and response to complex events.

Real and potential applications of the Akida Pico NPU​


The capabilities of the Akida Pico allow it to be used in a number of solutions that were previously not equipped with artificial intelligence due to technical limitations. Among its most notable applications are

  • Wearable devices and smart bracelets: Continuous health monitoring with real-time analysis and extended battery life.
  • Device medicos: monitoring of vital signs, detection of abnormal events, warning systems and reduction of the number of recharges or battery replacements.
  • Smart appliances: Refrigerators that recognize food, identify products close to the expiration date or detect the opening of doors using sensors and cameras integrated with local artificial intelligence.
  • Environmental and home automation sensors: Home or building automation with pattern recognition, presence detection, event response and false alarm filtering.
  • Personal headphones and speakers: Voice activation without Internet addiction, advanced noise suppression and personal assistants that work without latency or delay.
  • Industrial and defense systems: Remote equipment monitoring, local data analysis, early fault detection and multimodal processing for critical applications.
  • Robotics, drones and automotive: Quick responses, autonomous navigation, low latency and integrated processing without large on-board computers.
  • New emerging devices: Technologies not yet developed will benefit from ultra-compact and efficient local AI, opening the door to innovation in the IoT and wearable markets.
Thanks to its insignificant consumption, it is possible to implement artificial intelligence functions in small sensor hubs, alarm clocks, automatic doorbells, remote controls and other devices powered by batteries or even conventional batteries, where artificial intelligence was previously unthinkable.

Benefits for developers, integrators and users​

  • desarrolladores: Reduced learning curve thanks to the compatibility of MetaTF with standard ecosystems, simulators and rapid debugging tools.
  • Supplements: Maximum flexibility to scale performance, combine it with other chips and choose the best balance between cost, performance and power consumption.
  • Users: Smarter and more reliable devices, with greater autonomy and without the need to transfer sensitive data to the cloud, improving privacy and the overall experience.
The scalability Another key point is the performance of artificial intelligence, as it allows you to modulate power and consumption based on the actual use and operating conditions of the device, maximizing battery life.

BrainChip's commitment to edge computing and integrated artificial intelligence is reflected in a roadmap that includes both proprietary hardware integration and software development, promoting a robust and collaborative ecosystem to expand artificial intelligence across devices of all types and functions.

The arrival of Akida Pico marks a turning point in the ability to transform any battery-powered device into an intelligent, autonomous device equipped with native artificial intelligence. All this without giving up autonomy, space or budget, and offering new opportunities both in the domestic sector and in professional, industrial and healthcare applications, laying the foundations for a new generation of connected and intelligent products.
 
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7für7

Top 20
Catched it up at by FF


Thoughts?
 
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Mccabe84

Regular
Catched it up at by FF


Thoughts?
Turns out i was wrong in my thoughts on Tony's position moving to the US.
 
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7für7

Top 20
Turns out i was wrong in my thoughts on Tony's position moving to the US.


No worries… we were all wrong! Most of us in assuming we’d finally see the $2–3 range this year.
So yeah… let’s just wipe the slate clean!

It’s just funny that you have to go to the website to read about it Lol
 
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Esq.111

Fascinatingly Intuitive.
Morning Chippers ,

Interesting ..


Again , nothing about their ability to produce ASX announcements.

Esq.
 
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Mccabe84

Regular
No worries… we were all wrong! Most of us in assuming we’d finally see the $2–3 range this year.
So yeah… let’s just wipe the slate clean!

It’s just funny that you have to go to the website to read about it Lol
It seems that the company doesn't really like announcing anything on the ASX anymore.
 
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equanimous

Norse clairvoyant shapeshifter goddess
Trevor's first day as BRN IR

Screenshot_20250606_114046_Brave.jpg
 
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Guzzi62

Regular
Slightly off-topic, but very interesting nevertheless.


In a highly secured lab in the Netherlands, ASML spent a decade developing a $400 million machine that’s transforming how microchips are made. High NA is the latest generation of EUV, the only machines in the world that can etch nanoscopic blueprints on advanced chips for giants like Intel, TSMC and Samsung. The size of a double-decker bus, only five of these machines have been shipped so far. It’s unclear how Trump’s tariffs will impact the complex global supply chain for the lithography machines. But without them, no advanced chips can be made by the likes of Nvidia, Apple and AMD. No filming of High NA has ever been allowed until CNBC went to the Netherlands for this exclusive first look.


 
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Catched it up at by FF


Thoughts?
Thank you God
 
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Let’s see if the brainchip shareprice reacts to the Trump–Musk drama too… I still can’t wrap my head around how something so childish can have such a drastic impact. It really says a lot about the quality of today’s investors.
Back in the day, markets dropped because of global economic shifts, oil crises, and wars.
Today? Because two guys can’t control themselves…
“Mom, he stuck his tongue out at me!” – “No, youuu did!”….. they know exactly what they are doing… and the people tap into the trap!

What’s left?
Market psychology at kindergarten level – backed by hedge fund money.
Welcome to the year 2025.
Trump and Elon are at it pumping and dumping the stocks
 
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Bravo

If ARM was an arm, BRN would be its biceps💪!

Sandia Deploys SpiNNaker2 Neuromorphic System from SpiNNcloud​

June 5, 2025

DRESDEN, Germany, June 5, 2025 — SpiNNcloud today announced that Sandia National Laboratories has deployed a SpiNNaker2-based neuromorphic computing system to explore energy-efficient architectures for artificial intelligence and national security applications.
SpiNNaker2 Installation at Sandia National Labs. Photo credit: Craig Fritz, Sandia National Labs.
Developed by SpiNNcloud and based on research led by Steve Furber, designer of the original ARM architecture, SpiNNaker2 uses a large number of low-power processors to simulate spiking neural networks and support AI workloads.
The deployment supports Sandia’s broader efforts to investigate alternative computing architectures that reduce energy consumption while advancing capabilities in areas such as nuclear deterrence and AI research.
“Although GPU-based systems can boost the efficiency of supercomputers by processing highly parallel and math-intensive workloads much faster than CPUs, brain-inspired systems, like the SpiNNaker2 system, offer an enticing alternative,” said Craig M. Vineyard, Ph.D., research scientist at Sandia National Laboratories. “The new system delivers both impressive performance and substantial efficiency gains concurrently to Sandia’s neuromorphic capabilities.”
The SpiNNaker2 system employs a highly parallel architecture consisting of 48 SpiNNaker2 chips per server board, each containing 152 Arm-based cores and specialized accelerators. This design enables efficient, event-driven computation, allowing the system to perform complex simulations at a lower energy profile compared to traditional GPU-based systems. Such energy efficiency is crucial for applications where power consumption and cooling are limiting factors.
“Our vision is to pioneer the future of artificial intelligence through brain-inspired supercomputer technology for next-generation defense and beyond,” said Hector A. Gonzalez, co-founder and CEO of SpiNNcloud. “The SpiNNaker2’s efficiency gains make it particularly well-suited for the demanding computational needs of national security applications. We’re thrilled to partner with Sandia on this venture, and to see the system being brought to life first-hand.”
Looking ahead, SpiNNcloud is supporting emerging generative AI algorithms by enabling more efficient machine learning through dynamic sparsity. Rather than relying on dense models that activate all neural pathways, dynamic sparsity selectively engages only relevant subsets of neurons based on the input. This shift supports the development of new, more efficient AI architectures and offers a potential path to mitigating the growing energy demands associated with large-scale model training and inference.

 
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Bravo

If ARM was an arm, BRN would be its biceps💪!
Screenshot 2025-06-06 at 1.32.34 pm.png
 
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Bravo

If ARM was an arm, BRN would be its biceps💪!
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Bravo

If ARM was an arm, BRN would be its biceps💪!

The Pope

Regular
Even $2 USD would be a great outcome!

Interesting outcome for that AI company


The primary difference between BrainChip's and Untether AI's approaches to "copilot" AI lies in their underlying technology and focus. BrainChip focuses on developing edge AI chips, while Untether AI appears to be using LLMs (Large Language Models) for their copilot-like features. This distinction influences how each company's AI systems function, their capabilities, and their target use cases.

Here's a more detailed breakdown:

BrainChip's Approach:
  • Focus:
    Developing AI chips that can run edge AI models on limited power devices according to AI chip makers.
  • Technology:
    Neuromorphic computing, which aims to mimic the human brain's structure and function.
  • Copilot Features:
    While not explicitly a "copilot" in the same way as software tools, BrainChip's chip technology enables edge AI, which can be used for a range of tasks like:
    • Real-time data processing on devices.
    • Predictive maintenance in industrial settings.
    • Autonomous vehicles, etc.
  • Target Audience:
    Companies looking to deploy AI at the edge of their network, in devices like sensors, drones, or smart cameras.
Untether AI's Approach:

  • Focus:
    Using LLMs to provide intelligent insights and support to users.
  • Technology:
    Primarily relies on Large Language Models (LLMs) to process and generate text-based information.
  • Copilot Features:
    Untether AI's copilot-like features likely involve:
    • Providing context-aware information based on user queries.
    • Generating summaries of content.
    • Assisting with tasks like writing, brainstorming, or research.
  • Target Audience:
    Users looking for AI-powered assistance in tasks like content creation, research, and general productivity.
Key Differences Summarized:

Feature BrainChip Untether AI
Technology Edge AI Chips (Neuromorphic) LLMs (Large Language Models)
Focus AI at the edge of devices AI-powered assistance and insights
Copilot Role Enabling AI for various edge-based applications Providing AI-generated insights and support

In essence, BrainChip is focused on the hardware infrastructure for AI, while Untether AI (and other AI tools) use software (LLMs) to provide AI capabilities to users. Both approaches play a vital role in the broader landscape of AI development, with BrainChip's focus on edge AI and Untether AI's focus on AI-driven assistance in various tasks.
 
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The Pope

Regular
It seems that the company doesn't really like announcing anything on the ASX anymore.
Do you blame them when they can’t get many of the announcements right when then do announce on ASX.
 
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Bravo

If ARM was an arm, BRN would be its biceps💪!
Even $2 USD would be a great outcome!

I think we can rule out the prospect of getting acquired anytime soon.

If a takeover were just around the corner, I doubt the Board would be spending time hiring a swanky new IR firm, unless they thought the acquirer needed help explaining what they just bought.

bbt-shldpnny-explain.gif
 
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HopalongPetrovski

I'm Spartacus!
I think we can rule out the prospect of getting acquired anytime soon.

If a takeover were just around the corner, I doubt the Board would be spending time hiring a swanky new IR firm, unless they thought the acquirer needed help explaining what they just bought.

View attachment 86353
Maybe they just wanna get a betta class of investors.....

Unknown-1.jpeg


.....rather than, the usual crew they've gotten used to. 🤣

 
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FJ-215

Regular
I think we can rule out the prospect of getting acquired anytime soon.

If a takeover were just around the corner, I doubt the Board would be spending time hiring a swanky new IR firm, unless they thought the acquirer needed help explaining what they just bought.

View attachment 86353
Hi Bravo,
Just because it's Friday and not much is happening in BRNworld. I had a poke around Antonio's Linkedin page. Here is one of the 15+ skills he lists in relation to his role as Chairman of BRN........

1749190213707.png
 
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