BRN Discussion Ongoing

IloveLamp

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🤔

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Yes.

I am not married to any investment unlike some who I know who are who may read this post. So sorry in advance if you are married, you may not like it.

Also 'global presence expanded????' Expanded??? In Japan was our bloody previous IP agreements before 2023.
Korea - No announcements about that, so someone correct me if I am wrong. So that is fine.
Israel was NaNose in 2020.
Europe was heaps of stuff before 2023. Valeo, Airbus etc. Our tech team in France? Seriously?
This is all disrespectful to shareholders who have been here since only 2022 and did a little research!

I really don't like our CEO Sean Hehir. He defends himself constantly with the old 'since I was here blah blah blah...', so this Twitter post with another mistake makes my blood boil. Whoever is releasing these announcements on Twitter/ASX needs to go.

But... I don't need to like Hehir as an investor as long as he can be effective. His connections and hirings have been golden so far.
Maybe we are releasing this completely unprofessional content because we are trying to have less leaks around? I don't know. I am very optimistic in nature so I may be making stuff up to validate my investment.

Anyway, quality and management fundamentals need to improve and the clock is ticking as the boom of the liquidity cycle has already started.
Hey GazDix, while your criticism of the flag mix up is warranted (both Koreans and Japanese are proud peoples who've have had friction in the past, so probably don't appreciate, what looks like an "Ahh it's all the same" attitude, in respect to their national flags)..

But your beef about the expanded presence statements, I think is unwarranted.

It's the difference between dealing with customers in these countries and having a "feet on the ground" presence, whether that's actual or not (these days physical presence isn't really necessary, but I think that's what they mean).

The Company does, still have to lift it's game, with any public announcements or communications.

The Whole World sees them.
 
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Just a recent article I was reading summarising BRN a bit by an expert in sustainable urban planning.

DECEMBER 16, 2023 BY SIMON SMITH

Understanding the Functions of BrainChip Technology​


Summary:
BrainChip Holdings Ltd is a leading provider of ultra-low power, high-performance neuromorphic computing technology, also known as artificial intelligence (AI) chips. These chips are designed to function similarly to the human brain’s neural networks, providing a unique approach to machine learning. This article delves into the various applications of BrainChip’s technology, examines its importance, and scrutinizes its potential future impact.
What is BrainChip?
BrainChip Holdings Ltd is an Australian company known for developing and commercializing its unique AI technology called Akida™. The company is a pioneer in the emerging field of neuromorphic computing, which aims to mimic the neural architecture of the human brain to create more efficient and powerful computing systems.
Applications:
BrainChip’s technology is versatile, catering to a multitude of sectors. Here are some of the primary applications:
1. Automotive Industry: BrainChip’s solutions can be integrated into advanced driver-assistance systems (ADAS) for tasks such as object recognition, collision detection, and driver monitoring.
2. Industrial Internet of Things (IIoT): For smart factories, BrainChip’s technology helps in predictive maintenance, anomaly detection, and real-time diagnostics, enhancing efficiency and safety.
3. Cybersecurity: Their chips can process data on-the-fly for instant threat detection, making cybersecurity systems more robust against novel attacks.
4. Financial Technology: BrainChip aids in fraud detection and algorithmic trading by processing large data sets with high speed and accuracy.
5. Consumer Electronics: In smartphones and other devices, BrainChip accelerates voice and image recognition features while consuming less power.
6. Healthcare: BrainChip’s capabilities extend to medical diagnostic imaging and analysis, supporting the early detection of diseases.
Significance:
The significance of BrainChip’s technology lies in its neuromorphic design. Traditional computing systems are limited by the separation of memory and processing units, a constraint known as the von Neumann bottleneck. By contrast, neuromorphic chips process and store information in a manner akin to neurons and synapses, which can massively parallel process information and lead to significant speed and efficiency improvements.
Potential Future Impact:
BrainChip is expected to contribute significantly to the advancement of AI technology. By providing computing solutions that can learn and adapt in real-time, BrainChip’s technology has the potential to revolutionize the way we interact with machines, with implications ranging from personalized user experiences to advancements in robotics and beyond.
FAQ:
What is neuromorphic computing?

Neuromorphic computing is an area of technology that designs computer chips to mimic the neural structure of the human brain. This approach to computing focuses on pattern recognition and sensory processing with high efficiency.
How does BrainChip’s Akida AI processor work?
The Akida AI processor is an example of neuromorphic computing. It processes information using spiking neural networks (SNNs), which consume very little power and are capable of learning and making decisions from incoming data in real time.
What is the advantage of BrainChip technology over traditional computing?
BrainChip’s neuromorphic computing offers several advantages, including reduced power consumption, real-time learning, lower latency, and the ability to process information in a decentralized manner, without the need for cloud connectivity.
Is BrainChip technology already in use?
Yes, BrainChip’s technology is currently being implemented in various industries, reflecting the company’s partnerships with manufacturers and software developers seeking to enhance their products with AI capabilities.
Where can I find more information on BrainChip?
For more information on BrainChip Holdings Ltd and its technology, visit the company’s official website at brainchip.com.


mfts2.space_09174_realistic_portrait_of_man_normal_people_in_th_3ca1f3c3-67d3-4bfb-a457-4b23e53f7b72.jpeg

Simon Smith
Simon Smith is a renowned expert in the field of sustainable urban development. His work focuses on creating eco-friendly and efficient urban landscapes, incorporating green building practices and sustainable design principles. Smith’s approach to urban planning emphasizes the importance of environmental stewardship while meeting the growing demands of urban populations. His innovative strategies in sustainable city design have influenced how urban areas globally address challenges like climate change, resource management, and ecological conservation, making him a leading voice in shaping the future of sustainable urban living.

 
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Tothemoon24

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Nice publicity​

IMG_8022.jpeg


Businesswire
ByBusinesswire
December 28, 2023
BrainChip Holdings Ltd, the world’s first commercial producer of ultra-low power, fully digital, event-based, neuromorphic AI IP, was issued its latest U.S. patent, further strengthening its IP portfolio related to sustainable and efficient AI technologies.
Patent US 11,853,862, “Method, Digital Electronic Circuit and System for Unsupervised Detection of Repeating Patterns in a Series of Events,” facilitates learning in a digital hardware implementation of a spiking network. A key aspect of this unique approach is its effectiveness in performing accurate unsupervised detection or learning of repeating patterns, even when these patterns are embedded in high levels of noise, while being extremely efficient in reducing computing time, energy consumption and silicon footprint.
BrainChip’s AkidaTM IP and MetaTFTM tools seamlessly transform contemporary neural networks into event-based or spiking networks. This patented technology uniquely synergizes with the converted spiking networks, enabling the streamlined deployment of edge learning algorithms and unlocking use cases that conventional AI tools or solutions cannot attain.
“While we push the bounds with our innovative neuromorphic technology, preserving its integrity is paramount,” said Sean Hehir, CEO of BrainChip. “With 13 patents issued in the U.S. alone, we stand as leaders in developing and implementing next generation AI technologies for intelligent Edge devices and on-chip processing.”
BrainChip’s portfolio now comprises 19 issued patents (13x US, 4x AU, 1x EP, 1x CN). In addition, there are nearly 30 pending patent applications across the US, Europe, Australia, Canada, Japan, Korea, India, Brazil, Russia, Mexico, and Israel.
 
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MDhere

Regular
2 yrs ago weren't Brainchip mentioned with Mercedes
They still are. Go to brainchip investor page on their website. Here in case u can't find it
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IloveLamp

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IloveLamp

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IloveLamp

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3rd like in last couple of days by this loser 😜

View attachment 52944 View attachment 52945
Hi Ilovelamp

It is interesting that he studied at the Moscow State University and that the following paper was published by that same university in 2022 wherein amongst other things it was stated:

“3.8. Akida​

Akida (Vanarse et al., 2019) is the first commercial neuromorphic processor, commercially available since August 2021. It has been developed by Australian BrainChip since 2013. Fifteen companies, including NASA, joined the early access program. In addition to Akida System on Chip (SoC), BrainChip also offers licensing of their technologies, providing chip manufacturers a license to build custom solutions.

The chip is marketed as a power efficient event-based processor for edge computing, not requiring an external CPU. Power consumption for various tasks may range from 100 μW to 300 mW. For example, Akida is capable of processing at 1,000 frames/Watt (compare to TrueNorth with 6,000 frames/Watt). The first generation chip supports operations with convolutional and fully connected networks, with the prospect to add support of LSTM, transformers, capsule networks, recurrent and cortical neural networks. ANN network can be transformed into SNN and executed on the chip.

One Akida chip in a mesh network incorporates 80 Neural Processing Units, which enables modeling 1,200,000 neurons and 10,000,000,000 synapses. The chip is built at TSMC 28 nm. In 2022, BrainChip announced the second generation chip at 16 nm.

Akida's ecosystem provides a free chip emulator, TensorFlow compatible framework MetaTF for the transformation of convolutional and fully connected neural networks into SNN, and a set of pre-trained models. When designing a neural network architecture for execution at Akida, one should take into account a number of additional limitations concerning the layer parameters (e.g., maximum convolution size is 7, while stride 2 is supported for convolution size 3 only) and their sequence.

The major distinctive feature is that incremental, one-shot and continuous learning are supported straight at the chip. At the AI Hardware Summit 2021 BrainChip showed the solution capable of identifying a human in other contexts after having seen him or her only once. Another product by BrainChip is a smart speaker, that on having heard a new voice asks the speaker to identify and after that calls the person by their name. There results are achieved with help of a proprietary local training algorithm on the basis of homeostatic STDP. Only the last fully connected layer supports synaptic plasticity and is involved in learning.

Another instructive case from the AI Hardware Summit 2021 was a classification of fast-moving objects (for example, a race car). Usually, such objects are off the frame center and significantly blurred but they can be detected using an event-based approach.”


Probably means nothing but might provide background to his sudden interest.

My opinion only DYOR
Fact Finder
 
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IloveLamp

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Hi Ilovelamp

It is interesting that he studied at the Moscow State University and that the following paper was published by that same university in 2022 wherein amongst other things it was stated:

“3.8. Akida​

Akida (Vanarse et al., 2019) is the first commercial neuromorphic processor, commercially available since August 2021. It has been developed by Australian BrainChip since 2013. Fifteen companies, including NASA, joined the early access program. In addition to Akida System on Chip (SoC), BrainChip also offers licensing of their technologies, providing chip manufacturers a license to build custom solutions.

The chip is marketed as a power efficient event-based processor for edge computing, not requiring an external CPU. Power consumption for various tasks may range from 100 μW to 300 mW. For example, Akida is capable of processing at 1,000 frames/Watt (compare to TrueNorth with 6,000 frames/Watt). The first generation chip supports operations with convolutional and fully connected networks, with the prospect to add support of LSTM, transformers, capsule networks, recurrent and cortical neural networks. ANN network can be transformed into SNN and executed on the chip.

One Akida chip in a mesh network incorporates 80 Neural Processing Units, which enables modeling 1,200,000 neurons and 10,000,000,000 synapses. The chip is built at TSMC 28 nm. In 2022, BrainChip announced the second generation chip at 16 nm.

Akida's ecosystem provides a free chip emulator, TensorFlow compatible framework MetaTF for the transformation of convolutional and fully connected neural networks into SNN, and a set of pre-trained models. When designing a neural network architecture for execution at Akida, one should take into account a number of additional limitations concerning the layer parameters (e.g., maximum convolution size is 7, while stride 2 is supported for convolution size 3 only) and their sequence.

The major distinctive feature is that incremental, one-shot and continuous learning are supported straight at the chip. At the AI Hardware Summit 2021 BrainChip showed the solution capable of identifying a human in other contexts after having seen him or her only once. Another product by BrainChip is a smart speaker, that on having heard a new voice asks the speaker to identify and after that calls the person by their name. There results are achieved with help of a proprietary local training algorithm on the basis of homeostatic STDP. Only the last fully connected layer supports synaptic plasticity and is involved in learning.

Another instructive case from the AI Hardware Summit 2021 was a classification of fast-moving objects (for example, a race car). Usually, such objects are off the frame center and significantly blurred but they can be detected using an event-based approach.”


Probably means nothing but might provide background to his sudden interest.

My opinion only DYOR
Fact Finder
You're blowing my mind ff

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IloveLamp

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BRN / CARNEGIE

 
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COYI
 
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Worker122

Regular
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buena suerte :-)

BOB Bank of Brainchip
Hmmmnnnnn ok!

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HopalongPetrovski

I'm Spartacus!
Tis but a $66,270 scratch! 🤣

Now,

 
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buena suerte :-)

BOB Bank of Brainchip
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