D
Deleted member 118
Guest
wow the Nasdaq is down nearly 25% in the last month, while BRN up up a cool 17% during the same period。
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
cosors
👀
CPO - Chief Premium OfficerI nearly bought a T-shirt the other day that said "I suffer from CDO. It is like OCD but all the letters are in alphabetical order ....... like they should be!
If you don't have dreams, you can't have dreams come true!
...is in German, but the message and the humour may still come across. )
alwaysgreen
Top 20
Forget the eqx. I'll take one of these thanks.
news.com.au: Stunning new performance car exposed.
#Akidainside
news.com.au: Stunning new performance car exposed.
#Akidainside
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thelittleshort
Top Bloke
thelittleshort
Top Bloke
D
Deleted member 118
Guest
Another company added to the iceberg @BaconLover
Sorry Proga, but if you think it's going to take another 4-5 years to get to an sp of $20 I think you are grossly underestimating your investment.
We WILL BE IN PRODUCTS THIS YEAR via RENESAS according to PvdM.............We have confirmed connections to the biggest tech companies in the world not to mention NASA and the U.S government.....................We have IP agreements in place..............We have AKD2000 on the work bench.........WORKING. We will MOST LIKELY be listed on the NASDAQ within 2 years............
If the SP isn't more than $20 by end of 2024 I WILL BE AMAZED
Don't make the mistake of thinking the sp will be able to be held down forever. It's been moving upwards at a glacial pace strictly because of the manipulation by instos, and maybe wider market issues.......
Once we have revenue, once we have a few more names with our IP portfolio, once we have the markets attention..........things will look VERY different
My opinion only
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D
Deleted member 118
Guest
All this talk about dividends, I just be happy with us showing 20 million turnover in a FY.
BaconLover
Founding Member
Great work TLS! 1000eyes strike again. Made my morning. Have a great weekend all.
Plumerai
Ultra-efficient and accurate AI solutions for Smart Home Cameras and IOT. Support for <br/>Cortex-M & A, Ethos-U. Fastest inference engine in the world.
www.arm.com
Plumerai looks to be partnered with ARM
Brainchip
Plumerai ARM
D
Deleted member 118
Guest
Great work TLS! 1000eyes strike again. Made my morning. Have a great weekend all.
Plumerai
Ultra-efficient and accurate AI solutions for Smart Home Cameras and IOT. Support for <br/>Cortex-M & A, Ethos-U. Fastest inference engine in the world.
Plumerai looks to be partnered with ARM
Brainchip
DJM263
LTH - 2015
0 Eyes member tag. Congratulations Fact Finder
Top 20
I have read every opinion about future income, future value and future retirement but personally my ambition was to be right in my assessment that Brainchip was going to lead the 4th Industrial Revolution and in so doing create generational wealth and allow me to say to my adult son and son-in-law whose a technophobe now??? 
I would have to say the @thelittleshort seems to have beaten everyone to the punch with Plumeria and found our second physical mass market product using AKIDA IP. Great work.
All I can offer as a reward is the continuing fanboy behaviour of Dr. Arijit Mukherjee at Tata Consulting Services on his LinkdIn public page where the first photo is the Brainchip display at the same trade show:
My opinion only DYOR
FF
AKIDA BALLISTA
I would have to say the @thelittleshort seems to have beaten everyone to the punch with Plumeria and found our second physical mass market product using AKIDA IP. Great work.
All I can offer as a reward is the continuing fanboy behaviour of Dr. Arijit Mukherjee at Tata Consulting Services on his LinkdIn public page where the first photo is the Brainchip display at the same trade show:
My opinion only DYOR
FF
AKIDA BALLISTA
D
Deleted member 118
Guest
I wonder if I can get my money back as I couldn’t hold out any longer and brought thisI have read every opinion about future income, future value and future retirement but personally my ambition was to be right in my assessment that Brainchip was going to lead the 4th Industrial Revolution and in so doing create generational wealth and allow me to say to my adult son and son-in-law whose a technophobe now???
I would have to say the @thelittleshort seems to have beaten everyone to the punch with Plumeria and found our second physical mass market product using AKIDA IP. Great work.
All I can offer as a reward is the continuing fanboy behaviour of Dr. Arijit Mukherjee at Tata Consulting Services on his LinkdIn public page where the first photo is the Brainchip display at the same trade show:
My opinion only DYOR
FF
AKIDA BALLISTA
Page Not Found - Aliexpress.com
a.aliexpress.com
D
Deleted member 118
Guest
I wonder if it worth asking BRN to put a link up to this BRN discussion page on there website?
Fact Finder
Top 20
Hi all
The following comes from Plumeria website and I think this is where we will find AKIDA IP and note the name they use IKVA. No matter how you say it, it has a certain ring to it:
“Until now, we have been deploying our BNNs on Arm Cortex-M and Arm Cortex-A processors with great results. However, we felt there was more room for improvement, since these CPUs are built to run typical 8-bit and 32-bit workloads and don’t provide native support for the single-bit operations that our BNNs rely on.
Some of our customers asked if our AI solutions also support FPGAs, since these provide incredible flexibility, cost efficiency, and tighter integration. FPGAs turn out to be an ideal platform to implement our models and inference engine on, as they enable us to unlock the full potential of our BNNs. In FPGAs we can natively implement the binary arithmetic that we need to run our models. We therefore decided to develop our own AI accelerator IP core named Ikva, which we introduce for the first time in this blog post. The Ikva accelerator runs our own BNNs and also efficiently supports 8-bit models. Of course, Ikva is fully supported by our extensive tool flow and ultra-fast and memory-efficient inference engine that’s integrated with TensorFlow Lite. A 32-bit RISC-V processor controls Ikva, captures the data from the camera and provides a programmer-friendly runtime environment. During the development of Ikva, we aimed to design a new hardware architecture for our optimized AI models while keeping it highly flexible and suitable for unknown future models. In contrast to other AI companies that seem to either develop models, or training software, or AI processors, we focus on the full AI stack and the Ikva core completes our offering. With Ikva, we now support the full AI stack starting from data collection, to training and model development, to very efficient inference engines, and now all the way down to providing the most optimized hardware implementations.
As you know, we like AI that is tiny, and Ikva fits in small and low-power FPGAs like the Lattice CrossLink-NX. The architecture is scalable, both in memory and in compute power. This means we can target a wide variety of FPGAs, ensure we fit next to other IP blocks, and extract maximum performance out of the resources that are available in the target FPGA device.
The video above showcases one of our proprietary person presence detection models together with our inference software running on the Ikva IP core in a Lattice CrossLink-NX LIFCL-40 FPGA. This is a low-power and low-cost 6x6mm FPGA that is available off-the-shelf and includes a native MIPI camera interface, further reducing the number of components in the system.
Ikva runs our robust and highly accurate person presence detection model 10x faster on the CrossLink-NX FPGA than on a typical Arm Cortex-M microcontroller. Alternatively, the frame rate can be scaled down to 1 or 2 FPS for those applications where low energy consumption is key.
The Lattice CrossLink-NX Voice & Vision Machine Learning Board with the CrossLink-NX LIFCL-40 FPGA
There are many target applications for person presence detection. For instance in your home, to automatically turn off your TV, your lights, or heating when there’s no one in the room. Outside your home, your doorbell can send you a signal when there’s someone walking up to your front door or a small camera can detect when there’s an unexpected visitor in your backyard. In the office, your PC can automatically lock the screen when you leave. Elderly care can be improved when you know how much time they spend in bed, their living room, or outside. The possibilities are endless, whether it’s in the home, on the road, in the city, at the office or on the factory floor. Accurate, inexpensive and battery-powered person detection will enhance our lives.
Of course, besides running Plumerai’s optimized BNN models, you can also run your own model on the Ikva core, or integrate Ikva into your FPGA-based device. We’re excited to enable extremely powerful AI to go to places it couldn’t go before.
The Ikva IP core, the supporting tool flow, and optimized person detection models are available today. Contact us to receive more information or schedule a video call to see our live demonstration. We’re eager to discuss how we can enable your products with Ikva”
In addition Plumeria has its origins in the UK and Ikva has links to the following Oxford University research and Greece:
www.repository.cam.ac.uk
So I ask you what are the odds.
My opinion only DYOR
FF
AKIDA BALLISTA
The following comes from Plumeria website and I think this is where we will find AKIDA IP and note the name they use IKVA. No matter how you say it, it has a certain ring to it:
“Until now, we have been deploying our BNNs on Arm Cortex-M and Arm Cortex-A processors with great results. However, we felt there was more room for improvement, since these CPUs are built to run typical 8-bit and 32-bit workloads and don’t provide native support for the single-bit operations that our BNNs rely on.
Some of our customers asked if our AI solutions also support FPGAs, since these provide incredible flexibility, cost efficiency, and tighter integration. FPGAs turn out to be an ideal platform to implement our models and inference engine on, as they enable us to unlock the full potential of our BNNs. In FPGAs we can natively implement the binary arithmetic that we need to run our models. We therefore decided to develop our own AI accelerator IP core named Ikva, which we introduce for the first time in this blog post. The Ikva accelerator runs our own BNNs and also efficiently supports 8-bit models. Of course, Ikva is fully supported by our extensive tool flow and ultra-fast and memory-efficient inference engine that’s integrated with TensorFlow Lite. A 32-bit RISC-V processor controls Ikva, captures the data from the camera and provides a programmer-friendly runtime environment. During the development of Ikva, we aimed to design a new hardware architecture for our optimized AI models while keeping it highly flexible and suitable for unknown future models. In contrast to other AI companies that seem to either develop models, or training software, or AI processors, we focus on the full AI stack and the Ikva core completes our offering. With Ikva, we now support the full AI stack starting from data collection, to training and model development, to very efficient inference engines, and now all the way down to providing the most optimized hardware implementations.
As you know, we like AI that is tiny, and Ikva fits in small and low-power FPGAs like the Lattice CrossLink-NX. The architecture is scalable, both in memory and in compute power. This means we can target a wide variety of FPGAs, ensure we fit next to other IP blocks, and extract maximum performance out of the resources that are available in the target FPGA device.
The video above showcases one of our proprietary person presence detection models together with our inference software running on the Ikva IP core in a Lattice CrossLink-NX LIFCL-40 FPGA. This is a low-power and low-cost 6x6mm FPGA that is available off-the-shelf and includes a native MIPI camera interface, further reducing the number of components in the system.
Ikva runs our robust and highly accurate person presence detection model 10x faster on the CrossLink-NX FPGA than on a typical Arm Cortex-M microcontroller. Alternatively, the frame rate can be scaled down to 1 or 2 FPS for those applications where low energy consumption is key.
There are many target applications for person presence detection. For instance in your home, to automatically turn off your TV, your lights, or heating when there’s no one in the room. Outside your home, your doorbell can send you a signal when there’s someone walking up to your front door or a small camera can detect when there’s an unexpected visitor in your backyard. In the office, your PC can automatically lock the screen when you leave. Elderly care can be improved when you know how much time they spend in bed, their living room, or outside. The possibilities are endless, whether it’s in the home, on the road, in the city, at the office or on the factory floor. Accurate, inexpensive and battery-powered person detection will enhance our lives.
Of course, besides running Plumerai’s optimized BNN models, you can also run your own model on the Ikva core, or integrate Ikva into your FPGA-based device. We’re excited to enable extremely powerful AI to go to places it couldn’t go before.
The Ikva IP core, the supporting tool flow, and optimized person detection models are available today. Contact us to receive more information or schedule a video call to see our live demonstration. We’re eager to discuss how we can enable your products with Ikva”
In addition Plumeria has its origins in the UK and Ikva has links to the following Oxford University research and Greece:
Vector space models of ancient Greek word meaning, and a case study on homer
So I ask you what are the odds.
My opinion only DYOR
FF
AKIDA BALLISTA
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Boab
I wish I could paint like Vincent
Plumerai use Binarized Neural Networks that they say is there own work?
Perhaps one of the boffins here can explain for us mere mortals.
A grab from this site https://www.frontiersin.org/articles/10.3389/fnins.2020.00535/full below
Agree, ilL, almost entirely with your outlook, not so sure about your claim about AKD2000. Is there some evidence in regard to this suggestion, and if so, please point me in the direction where I might witness this, asap, please.
The 1000 eyes should be able to help, in this regard. Hope your correct. No announcement in regard to this as far as I'm aware.
Please, ( eyes ) PVDM possibly is all ears as well, A good question to be asked at the AGM IMO. Shame I can't make it to this event.
Do it soon, ilL, I'm all ears.
Akida Ballista >>>>>>> If AKD2000 has been proven functional, well, just WOW <<<<<<<
hotty...
chapman89
Founding Member
IMO the share price will rise to $12 plus a share (market cap of $20 billion) before we get dividends, I think dividends will be 3+ years away.Hi Yak52.
Just out of curiosity and without holding you to it, what would you estimate the annual dividend amount per share of BRN would be when it reaches that $5 mark? And would you consider that when we are sustaining $5 per share it would be a possible time that dividends would be considered?
I've always played in the specky end of the pool and so don't have much of a feel for dividend payments, though am very much looking forward to them with our BRN.
MaxwellAnne
Regular
Binarized neural networks
Binarized Neural Networks: An Overview
Binarized Neural Networks are an intriguing neural network variant that can save memory, time, and energy. Learn how they work.
towardsdatascience.com
“One roadblock in using neural networks are the power, memory, and time needed to run the network. This is problematic for mobile and internet-of-things devices that don’t have powerful CPUs or large memories. Binarized neural networks are a solution to this problem. By using binary values instead of floating point values, the network can be computed faster, and with less memory and power.”
Not sure what all this means needs one of our technical experts opinion @Diogenese et al
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