BRN Discussion Ongoing
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RobjHunt
Regular
Just missing the BrainChip logo somewhere, otherwise I’d be happy running alongside Bravo in them
RobjHunt
Regular
Maybe just below BrainChip on the top part of the tongue.Just missing the BrainChip logo somewhere, otherwise I’d be happy running alongside Bravo in them
Pantene Peeps
With 8 unis involved, there could be well above 100 engineers a year emerging with Akida expertise and taking this unique skill to their new employers. The early graduates should be well sought after as the AI snowball gathers momentum.
They are keeping the spikes for the track shoes.Just missing the BrainChip logo somewhere, otherwise I’d be happy running alongside Bravo in them
Fullmoonfever
Top 20
@TheDrooben
Further to your find on the project by the Uni of Virginia, below is some more info from GitHub which appears to be one and the same.
GitHub - hplp/ai-hardware-project-6501-group7: ai-hardware-project-6501-group7 created by GitHub Classroom
ai-hardware-project-6501-group7 created by GitHub Classroom - hplp/ai-hardware-project-6501-group7
github.com
Project Title
Age-Based Recommendation System Using BrainChip Akida (Neuromorphic Architecture)Project Description
This project aims to develop an AI-powered age-based recommendation system leveraging BrainChip Akida, a neuromorphic processor designed for energy-efficient and hardware-optimized inference. The system uses age estimation from facial images as a key input to recommend personalized content, products, or services tailored to specific age groups.Benefits
Energy Efficiency: Neuromorphic inference with low power consumption.Scalability: Adaptable across datasets and industries.
User Experience: Enhanced personalization through robust recommendations.
Conclusion
This project successfully demonstrated the development of an age-based recommendation system by leveraging the BrainChip Akida neuromorphic processor. Through a structured approach combining deep learning, quantization, neuromorphic computing, and efficient deployment techniques, we achieved several key objectives:Accurate Age Prediction:
By training and optimizing a VGG-based model on the UTKFace dataset, we developed a reliable age estimation system with high accuracy and low Mean Absolute Error (MAE). The use of data augmentation, hyperparameter optimization, and quantization further enhanced robustness and generalization across diverse demographics.
Energy-Efficient Inference:
The conversion of the quantized Keras model to the Akida format demonstrated the power and efficiency of neuromorphic computing. Akida's event-driven architecture achieved real-time, low-power inference while maintaining comparable accuracy to traditional AI models.
Seamless Model Conversion:
The integration of the CNN-to-SNN framework allowed for smooth conversion of traditional models to Akida-compatible spiking models, showcasing the practicality of deploying advanced neuromorphic solutions on edge devices.
Real-Time Edge Deployment:
By implementing the system on an edge device, we demonstrated its ability to perform real-time age predictions and generate personalized recommendations dynamically. This highlights the feasibility of deploying AI solutions in resource-constrained environments like IoT devices and embedded systems.
Scalability and Versatility:
The modular design and scalability of the system make it adaptable for various industries, including healthcare, retail, and entertainment. Future extensions could integrate additional features like emotion recognition or gender-based personalization for enhanced user experiences.
As we are cashed up prior to the LDA raise the very worst case scenario is that they are putting in place a safety net against a recession or AI crash that may be coming??
Worst case IMO is safety net.
We have circa 15.5% to 16.5% of SOI as inside holders.
They will ensure that BRN will remain 'safe'.
I think the LDA funding is more likely for something like a deal of some sort given that Sean and Tony V gave been madly accumulating within the rules.
Yes I wanted to but it somehow doesn’t seem to workJust missing the BrainChip logo somewhere, otherwise I’d be happy running alongside Bravo in them
Hi Manny,
Just hoping you could shed some light on Sean + Tony’s accumulation? Where is that disclosed and what are the rules surrounding share purchase internally?
Cheers
This one is also nice … unfortunately again he was not willing to add the logo…Just missing the BrainChip logo somewhere, otherwise I’d be happy running alongside Bravo in them
From the other site:
by FutureCIO Editors
January 10, 2025
Edge AI on-chip processing and learning company BrainChip Holdings Ltd has launched a compact, portable computation device to accelerate AI processing for various sectors such as manufacturing, warehouse, retail, hospitals, energy, automotive, and aviation.
Named Akida Edge AI Box, it claims to mimic the brain's learning ability through event-based neural processing. This approach reduces the need for consistent cloud connectivity, enhancing data security and efficiency while lowering processing costs.
Dual Akida processors enable on-chip learning independent of the cloud, which powers the AI gadget. The design targets enhancing application security, reducing training overhead, and hastening learning.
In partnership with electronics innovation and manufacturing company VVDN Technologies, users can develop custom versions of the product with original equipment manufacturers (OEMs) for large-scale commercial applications.
The Akida Edge AI Box is already being applied in various real-world scenarios such as edge AI model training and development, gesture recognition, climate forecasting, model evaluation, cybersecurity enhancement, and computer vision analysis.
“The Akida Edge Box is a great platform for running AI in standalone edge environments where footprint, cost and efficiency are critical while not compromising performance,” said Sean Hehir, BrainChip CEO.
Hehir expressed his excitement about rolling out even more use cases with other partners who seek to develop edge AI for their customers' specific use cases. He adds that the company looks forward to “the ideas these companies will bring to life with the Akida Edge AI Box.”
futurecio.tech
BrainChip unveils “brain-inspired” AI gadget for real time AI processing
January 10, 2025
Edge AI on-chip processing and learning company BrainChip Holdings Ltd has launched a compact, portable computation device to accelerate AI processing for various sectors such as manufacturing, warehouse, retail, hospitals, energy, automotive, and aviation.
Named Akida Edge AI Box, it claims to mimic the brain's learning ability through event-based neural processing. This approach reduces the need for consistent cloud connectivity, enhancing data security and efficiency while lowering processing costs.
Dual Akida processors enable on-chip learning independent of the cloud, which powers the AI gadget. The design targets enhancing application security, reducing training overhead, and hastening learning.
In partnership with electronics innovation and manufacturing company VVDN Technologies, users can develop custom versions of the product with original equipment manufacturers (OEMs) for large-scale commercial applications.
Real world applications
The Akida Edge AI Box is already being applied in various real-world scenarios such as edge AI model training and development, gesture recognition, climate forecasting, model evaluation, cybersecurity enhancement, and computer vision analysis.
“The Akida Edge Box is a great platform for running AI in standalone edge environments where footprint, cost and efficiency are critical while not compromising performance,” said Sean Hehir, BrainChip CEO.
Hehir expressed his excitement about rolling out even more use cases with other partners who seek to develop edge AI for their customers' specific use cases. He adds that the company looks forward to “the ideas these companies will bring to life with the Akida Edge AI Box.”
BrainChip unveils “brain-inspired” AI gadget for real time AI processing - FutureCIO
Named Akida Edge AI Box, it claims to mimic the brain's learning ability through event-based neural processing. T
futurecio.tech
Pom down under
Top 20
Who was accumulating before Xmas?
FiveBucks
Regular
HopalongPetrovski
I'm Spartacus!
Pom down under
Top 20
Does anyone know if it was retail FOMO or other?Pretty sure Davo was keen.
Think he got a tip from the Flotsey Mules.
HopalongPetrovski
I'm Spartacus!
Dunno Pom.
There was a lot of speculation about expected announcements on all the channels so I recon some retail and perhaps even a bit of soph. FOMO was invoked.
We did wind up getting some good announcements but nothing that shot the share price into the stratosphere and now that CES has come and gone, some reallocation is to be expected I suppose.
I think we are now at the point where it will take a contract with some significant ongoing revenue to really get us moving.
Till then its back to the hurry up and wait.
Hi Plebby, extract from earlier research on this topic.
Fact both Sean and ChaIrman Tony V took circa 81% plus of their real pay in equity in 2023. See the Annual report. Likely similar result in 2024.
They do via conversion of RSU's which avoid insider trading regulations. Smart way to incentivize employees and build insider holdings.
Fact both Sean and Tony V are net accumulating and hold enough to put them in the top 50 holders. See recent Director's notices.
Fact. Sean has 6 million RSU's which he can elect to take over time instead of cash pay. If he keeps taking equity instead of cash pay he will end up in the top 20.
Fact 15.5% - to 16.6% of SOI are held by insiders. See Yahoo Finance and Simply WS.
Assumption: Sean, Tony and insiders know a lot more about what is to come with BRN than holders and posters.
On top of the above Insiders hold enough to block any unwelcome takeover offers.
Sean hinted on further positive news to come on a recent podcast. Not sure how big the deals will be. Hopefully Tata sign up some time this year as that could be a profitable overnight deal.
Recent Frontgrade and USAF deals give confidence as does our new partners with our Edge Box.
Connection with RTX a huge defense supplier. Bascom Hunter.........................................All adding up.
SERA2g
Founding Member
Hi Manny
I think you are taking a very rose-coloured glasses approach to the way that RSU's work.
Don't quote me on this as I have not looked at the remuneration reports from the latest set of accounts for some time, but Sean's salary is circa gross $400K. On top of this, Sean is eligible to receive performance shares which are issued on meeting KPI's.
We are not provided information surrounding the KPI's that need to be met. Some KPI's might be walk ups such as 'attend all 12 monthly meetings', others will be 'expand ecosystem by x% or 'generate net sales of $500m'.
Some KPI's will be met, some will not. The restricted shares are issued upfront and then ordinary shares are awarded upon KPI's being met, or cancelled at the conclusion of the KPI period set by the board.
You've previously posted the narrative that Sean is accumulating because he is selling 'some' of his shares to cover tax obligations, but not all of them.
Sean's shares are issued to him for FREE. $0. Nothing. He then has to pay tax on the discount (full value of the shares at date of issue). I therefore understand why directors then sell some of those shares to fund their tax obligations.
It is a big reach to then argue Sean is accumulating because his shareholdings have increased.
Sean has no skin in the game with respect to the performance share's he's issued. He isn't buying $50K shares on market like we would have to. He has received them for FREE. He then sells $10K worth of shares to cover an upcoming $10K tax liability in relation to those shares. Ergo, Sean has FREE-CARRIED $40K worth of shares. With tax having been paid by share sales, he's literally out of pocket $0 for the remaining shares.
If he received $50K worth of shares for FREE and then paid the corresponding tax liability from his own cash, it would be fair to argue that he has $10K skin in the game. This simply is not the case. Sean and the other directors always sell shares to cover the tax liability.
As far as I'm aware, Pia is the only director to have purchased shares on market in the last few years.
All of the above aside, we want to attract top talent and it would be fair to say that US based CEO's of tech company's would receive significantly more than $400K for their role, so I do understand the need to include performance shares in the overall salary package. This works well for shareholders as the directors have a long term incentive to increase the value of the company and therefore shareholders capital.
The one painful point for people like Sean is that shareholders tend to jump on them when they sell shares to cover tax, however, there's no announcement when a director chooses not to sell shares and personally wears the tax, leaving the decision a thankless one.
Fullmoonfever
Top 20
Hi Pom,
This is from the other site courtesy of a poster by the name of DimDim.
BRN Broker Data Analysis
First, let me give you a bit of perspective over the year to see where we are now. The yellow line shows the trend of share accumulation by 4 retail brokers combined. As you can see, about 100M shares were accumulated by retail brokers over the year.
Top sellers and their accumulation/distribution trends:
- FinClear Execution
- Bridges
- Barrenjoey
Now, let's have a closer look at broker data since October.
Top buyers:
Top sellers:
Retail broker accumulation on the chart:
What's interesting here is that selling by retail brokers started from Dec 23. This means that pro brokers pushed the price up. Very nice pattern, especially combined with the break of the fallen trendline.
Who pushed the price up:
- Goldman Sachs
- Macquarie Securities
- Morrison
Interesting development. Looks positive. Going to keep an eye on it.
I don't agree that shares that are issued as part of a remuneration package are isued for free. Just like the cash salary, they are issued for services provided by the recipient. In fact they may be tied to specific performance targets.
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