BRN Discussion Ongoing

[Baron Von Ricta]

Just hang in there. I learnt my lesson years ago with CUV. Share price hung around the $2 mark for ages so I sold out and bought something else. Few years later it went to $40.
So now if I like my research I hang on and wait...wait... =(sometimes)
Remember, you can't build a skyscraper if you haven't got a strong foundation. 'Pantene'.

 

[Bravo]

Hello all. Have not been here in a while. How's everyone going? Any news of revenue yet? The wife wants to know before we sign the divorce papers. Thanks in advance

Maybe we should turn the BRN thread into a dating site since so many of us are getting ex-communicated by our significant others.

I‘ll start the ball rolling.

I‘m a fun-loving lass with a quirky sense of humour and an even quirkier sense of fashion. I like to practice taekwondo in my spare time and to watch documentaries about true crime and evil psychopaths on Netflix, as well as eating tubs of Connoisseur ice-cream. I’m currently learning how to play the maracas and the bugle . I have 10 cats and a blue-tongued lizard called Gertrude.

I don’t like chewing sounds, so if you’re one of those people who can eat with your mouth closed, then please feel free to call me.

 

[DingoBorat]

Maybe we should turn the BRN thread into a dating site since so many of us are getting ex-communicated by our significant others.

I‘ll start the ball rolling.

I‘m a fun-loving lass with a quirky sense of humour and an even quirkier sense of fashion. I like to practice taekwondo in my spare time and to watch documentaries about true crime and evil psychopaths on Netflix, as well as eating tubs of Connoisseur ice-cream. I’m currently learning how to play the maracas and the bugle . I have 10 cats and a blue-tongued lizard called Gertrude.

I don’t like chewing sounds, so if you’re one of those people who can eat with your mouth closed, then please feel free to call me.

Crazy cat lady.. Great ...

 

[Fullmoonfever]

Crazy cat lady.. Great ...

 

[Fullmoonfever]

Awareness of the Arquimea partnership.

https://www.forwardpathway.us/brain-inspired-ai-predictive-coding-networks-revolutionize-drone-energy-efficiency#

Neuromorphic Computing: Mimicking the Brain for Enhanced Drone Capabilities​

Okay folks, your friendly editor here, ready to dive deeper into this fascinating world of brain-inspired AI. We’ve touched on how traditional AI can be a bit power-hungry for drones, and now we’re going to explore the exciting field of neuromorphic computing, which is all about making AI work more like our own incredible brains.

Think about it: our brains are incredibly efficient. They can process vast amounts of information without needing a massive power source. Neuromorphic computing aims to replicate that structure and function. Instead of just using standard computer chips, researchers are building hardware that mimics the way biological neurons work – they’re like tiny, interconnected processing units that activate only when there’s something important to do. This “activate-only-when-necessary” approach is a huge deal for energy efficiency. Imagine a drone that doesn’t have to constantly power up every single processing unit; it can just focus its energy where and when it’s needed, just like you might focus your attention on a specific conversation in a noisy room. This could mean dramatically increased flying times and a whole host of enhanced operational capabilities, allowing drones to do more complex tasks for longer periods.

The U.S. Air Force is really leaning into this, recognizing the potential. They’re investing in developing these super tiny, almost rice-sized AI chips that are designed to mimic biological neurons. The idea is to create AI that’s not only powerful but also incredibly compact and energy-sipping. One of the materials being explored for this is conducting polymer thin films. These can act like the artificial neurons we were just talking about, firing only when they receive the right kind of input.

This isn’t just theoretical, either. Companies and research institutions are already pushing the boundaries. Intel, for instance, has unveiled its Hala Point neuromorphic computer, which boasts over 1,000 AI chips and offers a significant performance leap over traditional computing. On the government side, the Joint Artificial Intelligence Center is also actively involved in developing both AI software and neuromorphic hardware. Their focus is on systems that can really help with sharing sensor information among networked units, giving drones and other autonomous systems a much better handle on what’s going on around them – improving that all-important situational awareness.

We’re already starting to see some really cool real-world applications popping up. Take water rescues, for example. Companies like BrainChip are integrating their Akida processor, which is designed with neuromorphic principles, onto low-power drones. When paired with event-based cameras from companies like Prophesee, these drones can quickly detect people in distress in aquatic environments. The Akida processor can process visual data directly, cutting down on latency and power usage. This means lifeguards can get alerts faster and potentially save more lives. It’s a fantastic illustration of how these brain-inspired AI systems, when implemented on the edge – meaning right there on the drone itself – can deliver incredibly fast and efficient performance, even in critical, life-or-death situations. It really makes you think about how much further drones can go with this kind of advanced, yet energy-conscious, AI.

ABOUT FORWARD PATHWAY​

Forward Pathway LLC is an educational consultant company established in US and dedicated to international students’ application and transfer to US high schools and colleges. Founded in Pennsylvania, the state rich in educational resources, Forward Pathway takes advantage of nearby renowned universities as University of Pennsylvania, Carnegie Mellon University, University of Pittsburgh, Pennsylvania State University and plenty of top US colleges in neighboring states. Now its headquarter has moved to Los Angeles. Based in LA to serve the entire nation, relying on strong partnerships with local US universities, Forward Pathway is aimed at being students’ personal education specialist, at the first time to update the latest news of studying abroad.

 

[CHIPS]

The Engineer’s Guide to Implementing Practical ML - with Arduino, Edge Impulse (a Qualcomm company) and DigiKey | ipXchange

The Engineer’s Guide to Implementing Practical ML - with Arduino, Edge Impulse (a Qualcomm company) and DigiKey Tired of ML hype and theory? Want to actually get machine learning running on real hardware? Join Elliott, ipX's design engineering host, as he breaks down practical ML use cases with...

www.linkedin.com

 

[CHIPS]

If somebody has the technical background and wants to have a look at Loihi 2

Legendre-SNN on Loihi-2 : Programming Lakemont Cores - ONM Student Talks​

 

[Diogenese]

If somebody has the technical background and wants to have a look at Loihi 2

Legendre-SNN on Loihi-2 : Programming Lakemont Cores - ONM Student Talks​

Legendre gets a mention in:

TENNs-PLEIADES: Building Temporal Kernels with Orthogonal Polynomials​

Yan Ru Pei, Olivier Coenen

https://arxiv.org/html/2405.12179v3

Abstract​

We introduce a neural network named PLEIADES (PoLynomial Expansion In Adaptive Distributed Event-based Systems), belonging to the TENNs (Temporal Neural Networks) architecture. We focus on interfacing these networks with event-based data to perform online spatiotemporal classification and detection with low latency. By virtue of using structured temporal kernels and event-based data, we have the freedom to vary the sample rate of the data along with the discretization step-size of the network without additional finetuning. We experimented with three event-based benchmarks and obtained state-of-the-art results on all three by large margins with significantly smaller memory and compute costs. We achieved: 1) 99.59% accuracy with 192K parameters on the DVS128 hand gesture recognition dataset and 100% with a small additional output filter; 2) 99.58% test accuracy with 277K parameters on the AIS 2024 eye tracking challenge; and 3) 0.556 mAP with 576k parameters on the PROPHESEE 1 Megapixel Automotive Detection Dataset.

1Introduction​

Temporal convolutional networks (TCNs) [18] have been a staple for processing time series data from speech enhancement [22] to action segmentation [17]. However, in most cases, the temporal kernel is very short (usually size of 3), making it difficult for the network to capture long-range temporal correlations. The temporal kernels are intentionally kept short, because keeping a long temporal kernel with a large number of trainable kernel values usually leads to unstable training. In addition, we require a large amount of memory for storing the weights during inference. One popular solution for this has been to parameterize the temporal kernel function with a simple multilayer perceptron (MLP), which promotes stability [28] and more compressed parameters, but it often increases the computational load considerably.

Here, we introduce a method of parameterization of temporal kernels, named PLEIADES (PoLynomial Expansion In Adaptive Distributed Event-based Systems), that can in many cases reduce the memory and computational costs compared to explicit convolutions. The design is fairly modular, and can be used as a drop-in replacement for any 1D-like convolutional layers, allowing them to perform long temporal convolutions effectively. In fact, we augment a previously proposed (1+2)D causal spatiotemporal network [23] by replacing its temporal kernels with this new polynomial parameterization. This new network architecture serves as the backbone for a wide range of online spatiotemporal tasks ranging from action recognition to object detection.This network belong to a broader class of networks named Temporal Neural Networks (TENNs) developed by Brainchip Inc.


...

The seminal work proposing a memory encoding using orthogonal Legendre polynomials in a recurrent state-space model is the Legendre Memory Unit (LMU) [33], where Legendre polynomials (a special case of Jacobi polynomials) are used. The HiPPO formalism [11] then generalized this to other orthogonal functions including Chebyshev polynomials, Laguerre polynomials, and Fourier modes. Later, this sparked a cornucopia of works interfacing with deep state space models including S4 [12], H3 [2], and Mamba [10], achieving impressive results on a wide range of tasks from audio generation to language modeling. There are several common themes among these networks that PLEIADES differ from. First, these models typically only interface with 1D temporal data, and usually try to flatten high dimensional data into 1D data before processing [12, 37], with some exceptions [21]. Second, instead of explicitly performing finite-window temporal convolutions, a running approximation of the effects of such convolutions are performed, essentially yielding a system with infinite impulse responses where the effective polynomial structures are distorted [31, 11]. And in the more recent works, the polynomial structures are tenuously used only for initialization, but then made fully trainable. Finally, these networks mostly use an underlying depthwise structure [14] for long convolutions, which may limit the network capacity, albeit reducing the compute requirement of the network.
[33]↑Aaron Voelker, Ivana Kajić, and Chris Eliasmith.Legendre Memory Units: Continuous-time representation in recurrent neural networks.Advances in neural information processing systems, 32, 2019. [Uni of Waterloo]

 

[Pom down under]

 

[Dallas]

𝗘𝗱𝗴𝗲 𝗔𝗜 𝗖𝗵𝗶𝗽𝘀: 𝗧𝗵𝗲 𝗤𝘂𝗶𝗲𝘁 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗶𝗻 𝗦𝗲𝗺𝗶𝗰𝗼𝗻𝗱𝘂𝗰𝘁𝗼𝗿𝘀 | Dinesh Tyagi

𝗘𝗱𝗴𝗲 𝗔𝗜 𝗖𝗵𝗶𝗽𝘀: 𝗧𝗵𝗲 𝗤𝘂𝗶𝗲𝘁 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗶𝗻 𝗦𝗲𝗺𝗶𝗰𝗼𝗻𝗱𝘂𝗰𝘁𝗼𝗿𝘀 As the semiconductor world chases ever-larger datacenter chips to power LLMs and generative AI, a quiet but equally transformative shift is unfolding: AI at the edge. According to a recent report by MarketsandMarkets, the edge AI hardware...

www.linkedin.com

 

[Pom down under]

Maybe we should turn the BRN thread into a dating site since so many of us are getting ex-communicated by our significant others.

I‘ll start the ball rolling.

I‘m a fun-loving lass with a quirky sense of humour and an even quirkier sense of fashion. I like to practice taekwondo in my spare time and to watch documentaries about true crime and evil psychopaths on Netflix, as well as eating tubs of Connoisseur ice-cream. I’m currently learning how to play the maracas and the bugle . I have 10 cats and a blue-tongued lizard called Gertrude.

I don’t like chewing sounds, so if you’re one of those people who can eat with your mouth closed, then please feel free to call me.

 

[MegaportX]

Maybe we should turn the BRN thread into a dating site since so many of us are getting ex-communicated by our significant others.

I‘ll start the ball rolling.

I‘m a fun-loving lass with a quirky sense of humour and an even quirkier sense of fashion. I like to practice taekwondo in my spare time and to watch documentaries about true crime and evil psychopaths on Netflix, as well as eating tubs of Connoisseur ice-cream. I’m currently learning how to play the maracas and the bugle . I have 10 cats and a blue-tongued lizard called Gertrude.

I don’t like chewing sounds, so if you’re one of those people who can eat with your mouth closed, then please feel free to call me.

 

[7für7]

𝗘𝗱𝗴𝗲 𝗔𝗜 𝗖𝗵𝗶𝗽𝘀: 𝗧𝗵𝗲 𝗤𝘂𝗶𝗲𝘁 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗶𝗻 𝗦𝗲𝗺𝗶𝗰𝗼𝗻𝗱𝘂𝗰𝘁𝗼𝗿𝘀 | Dinesh Tyagi

𝗘𝗱𝗴𝗲 𝗔𝗜 𝗖𝗵𝗶𝗽𝘀: 𝗧𝗵𝗲 𝗤𝘂𝗶𝗲𝘁 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗶𝗻 𝗦𝗲𝗺𝗶𝗰𝗼𝗻𝗱𝘂𝗰𝘁𝗼𝗿𝘀 As the semiconductor world chases ever-larger datacenter chips to power LLMs and generative AI, a quiet but equally transformative shift is unfolding: AI at the edge. According to a recent report by MarketsandMarkets, the edge AI hardware...

www.linkedin.com

Ladies and gentlemen, we have a Karen on board. Mimimimi

 

[Andy38]

1.3m in engineering revenue from 3 CUSTOMERS!!! I like.
Now to see Sean and his 9 million to start rolling in!

 

[Esq.111]

Good Morning Chippers,

Quarterly is out , though i have not read it yet......



Regards,
Esq.

 

[7für7]

Here you can read it

https://cdn-api.markitdigital.com/apiman-gateway/ASX/asx-research/1.0/file/2924-02972446-2A1610569&v=4a466cc3f899e00730cfbfcd5ab8940c41f474b6

 

[DK6161]

Wow! Over 1 mill revenue! This will go to 50 cents today for sure. Not advice

 

[Mccabe84]

Wow! Over 1 mill revenue! This will go to 50 cents today for sure. Not advice

Its better than the last one..

 

[7für7]

Its better than the last one..

You still read his comments? Respect

 

[7für7]

In short



Sydney - 30 July 2025 - BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, BCHPY) (Company), the world's first commercial producer of neuromorphic artificial intelligence technology, today provides the Quarterly Activities Report in conjunction with its Appendix 4C lodged for the quarter ending 30 June 2025.


Key Highlights

• Cash balance of US$13.5M provides sufficient capital for growth and investment in research and development of new and existing products.
• Evaluation of redomiciling Company listing has been completed with input from a range of domestic and international advisors, including legal, investment banking groups, and shareholders. After detailed evaluation and analysis, the Board made the decision that shareholder value is best achieved by remaining listed on the ASX.
• Cash inflow from customers in the current quarter of US$1.4M was higher than the prior quarter (US$0.14M).
• Total payments to suppliers and employees of US$4.4M in the current quarter were lower than the prior quarter (US$4.9M).
• Collaboration with multiple high-quality companies during the quarter further demonstrates the commercial application of BrainChip's technology.
• Continued expansion of global intellectual property portfolio, now comprising 55 issued and pending patents across the United States, Europe, and APAC regions.

Redomicile Update


On 27 February 2025, the Company announced it was evaluating the possibility of redomiciling to an alternative stock exchange with a focus on the US. Post an extensive review that included input and advice from a range of experts, including foreign and domestic legal advisors, investment banks and feedback from shareholders, the Board has made the decision that shareholder value is best achieved by remaining listed on the ASX.


BrainChip remains committed to the ASX listing and ensuring that the Company continues its path to commercial success. The Board acknowledges and appreciates the ongoing commitment of shareholders. This sustained support is instrumental to the Company's progress and underpins its pursuit of long-term growth.