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I wish I could paint like Vincent
I’ve joined the up coming zoom webinar on the 24th. At 11am American/Canadian pacific time .A Wednesday. I am hopeful that they may say something over that time period of the webinar or I will be asking why they bother to have it .
A little more info for those that may have missed it. Should be a cracker.

 
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KMuzza

Mad Scientist
It's the same old story Xhosa..

Shareholders can be like children, pestering their parents
"Are we there yet?"
"Are we there yet?"
"Are we there yet?"..

Whatever the parents say, they will be asking again, in 5 minutes time.

The Company is busting its balls, to make BrainChip successful, while the shareholders, sit on their asses and complain.

But look at any company forum and you will find the same thing.

People need to grow up.

News will come, when news is available.

We will get there.
Enjoy the journey, instead of just thinking about the destination...
Hi DingoBorat,
there are a lot of "are we there yet" 's expressing displeasure on BRN /Shareprice/Communication/ Announcements - etc .

So as a bit of a ROADMAP- to help everyone understand -How and When will we get there.

1) Edge /Brainchip will be having the Zoom Tech Webinar - on 24th August 2022- USA time


2) The 1st Half 2022 Financials must be released - Tentativly by end of August 2022.

3) Patent Reveals -due soon- possibly giving BRAINCHIP - ASX Announcements.

4) The Edgeimpulse Embedded ML Event of the Year World Wide Webinar - 22-28 Sept 2022.



So - maybe the TSE form members should start a thread - and write down the questions that should be asked, during these free access webinars that are coming up - so as to get the answers that they /everyone wants.


So this sets the perfect opportunity for the scene for reveals- ie- AKIDA additions -1500 or 2000,
Perfect opportunity to -a)ASK deep and hard questions for the zoom BRN representative from participants.
b) wring out the BRN representative to get the answers that you want.




AKIDA BALLISTA UBQTS.
 
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Diogenese

Top 20
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buena suerte :-)

BOB Bank of Brainchip
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robsmark

Regular
My earlier post regarding a conversation I had with Tony a couple of weeks ago was deleted after Tony refuted some of the comments which I made.

I can assure all that the post was made with no bad intentions, and that the conversation was relayed to the best of my ability. As I mentioned in the post - no new information was discussed/released by Tony.

Tony - my apologies if I misquoted or misrepresented you in any way.
 
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alwaysgreen

Top 20
Well today sucks...

Hopefully onwards and upwards for the remainder of the week.
 
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SERA2g

Founding Member
My earlier post regarding a conversation I had with Tony a couple of weeks ago was deleted after Tony refuted some of the comments which I made.

I can assure all that the post was made with no bad intentions, and that the conversation was relayed to the best of my ability. As I mentioned in the post - no new information was discussed/released by Tony.

Tony - my apologies if I misquoted or misrepresented you in any way.
Lesson learned here for everyone. If you're going to quote a 'personal' conversation you've had with anyone from the company it's probably best to check in with the person in question before sharing it here.

Appreciate your efforts though @robsmark, I'm positive your intentions were good!

Cheers mate
 
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Vojnovic

Regular
Germans continue their love affair with our company:
 
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equanimous

Norse clairvoyant shapeshifter goddess
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TheFunkMachine

seeds have the potential to become trees.
Not just any neuromorphic sensor but an Australian neuromorphic sensor.

Not sure how many other Australian Neuromorphic Sensor companies there are?
But Akida is not a sensor rather sensor agnostic, or neuromorphic processor that process sensor input/output.

Not saying it’s not Akida, I’m just saying Akida is not a neuromorphic sensor
 
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Sirod69

bavarian girl ;-)
This is an interesting paper. Does not name BRN or AKIDA but when read you will see why partnering with ARM Cortex M4 is so very exciting:

A Brief Review of Deep Neural Network Implementations for ARM Cortex-M Processor

....System-On-Chip (SoC) devices are an attractive solution that, in addition to high processing capabilities, includes multiple peripheral devices that can be very helpful for the sophisticated requirements of deep-learning applications. Examples of manufacturers that develop AI integrated circuits for edge computing are Samsung, Texas Instruments, Qualcomm, and STM. Some of their recent products are briefly presented below.......

5. Conclusions
Deep learning and deep neural networks are emerging as promising solutions for solving complex problems. Solving complex problems requires high computational capabilities and memory resources, so are traditionally designed to run on a large computer system around specialized hardware. However, recent research shows that simple applications can benefit from the deep learning paradigm and their edge computing implementation as well. Edge computing is the solution to many real-world problems that need to be solved soon. For instance, the automotive industry is using and developing prototypes using state-of-the-art hardware and software solutions for autonomous driving. Once these prototypes prove their ability to solve problems, the systems will have to run on real-world cars. At that stage, cost is necessary to be competitive in the market, and, using high performance computing solutions, the cost is high. The edge computing paradigm must be prepared with efficient and low-cost solutions while meeting specific requirements such as functional safety. In this work, we provide a summary of what edge computing means in the context of low-cost/low-power applications. Here, the ARM Cortex-M processor represents one of the best possible candidates. More specifically, we summarize deep neural network implementations using ARM Cortex-M core-based microcontrollers. From the software perspective, the STM32Cube.AI support package, made available by STMicroelectronics for its 32-bit microcontroller series, represents one of the best freely available tools. Implementing deep neural networks on embedded devices, such as microcontrollers, is a difficult task. This is mainly due to the computation and memory footprint constrains. For this reason, it is observed that developers are forced to customize existing architectures or even develop from scratch innovative models that better suit embedded processors. Optimization techniques such as quantization, pruning, and distillation are constantly evolving to achieve higher performance, and they are enabling developers to introduce state-of-the-art models of increasing complexity to the embedded domain. Ultimately, using an optimized hardware combined with optimized deep neural network architectures leads to maximum energy efficient systems. Electronics 2022, 11, 2545 19 of 21 Future work proposes to extend the study to a wider family of ARM cores, including, for example, deep learning applications running on Cortex-A type processors or even specialized Arm Ethos-N series processors for machine learning

https://www.mdpi.com/2079-9292/11/16/2545/pdf?version=1660467458
 
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Onboard21

Member

Onboard21

Member

projection

Member
^^ It was a 4ds reference
 
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langeo

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CeeMite

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Sirod69

bavarian girl ;-)
Deutsche setzen ihre Liebesaffäre mit unserem Unternehmen fort:
BRAINCHIP: THESE CHIPS ARE UNIQUE
Away from operational worries and hardships, the BrainChip stock is being traded very briskly these days - within a month it was up 16%. BrainChip relies on a revolutionary chip architecture that is based on the human brain and is designed to use extremely little energy. The self-learning chips should therefore be used for many future tasks, such as autonomous driving. In the past, BrainChip caused a sensation when the technology was tried out in the voice control of Daimler cars, among other things, and provided outstanding results.

A few weeks ago, the authorities in Australia, where BrainChip has its home stock exchange, published the twenty largest shareholders of the up-and-coming company. Including such illustrious names as Citicorp, HSBC, BNP Paribas, Merrill Lynch and several other asset managers and family offices. Since BrainChip offers convincing solutions for everything to do with AI and the price has fallen significantly in recent months, investors could make a note of the value. Although there will be no dividends in the foreseeable future, the patented architecture could prevail. Earlier this year, the market ran through this scenario once before, sending the stock to levels more than 100% above its current price.

The boom in electric mobility is causing the shares of growth companies and industry giants to rise. The only difference is in intensity. Smaller companies in particular, which are still fighting for market share or who want to bring their products to market first, could have great potential in the medium term. Examples are BYD, which has already jumped in, and the AI chip pioneer BrainChip. The downside is a higher risk. Those who shy away from this should better orientate themselves in the direction of Infineon and Volkswagen.
 
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Townyj

Ermahgerd
Yes it was in reference to 4DS... Not Akida. lol i can imagine the heart rate after reading it.

This is how i feel...

Fran Healy Reaction GIF by Travis
 
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Dhm

Regular
I emailed Prof Greg Cohen to see if he can confirm BrainChip’s involvement in the Jarli mission. I will report in if Greg responds.

Meanwhile, I think we all need our tyres pumped up a little. Please remember we have over 100 NDAs in progress. Mercedes Benz was one of them. Just imagine what other BIG NAMES may in the future (hopefully soon!) declare their partnership with us. There comes a stage within a NDA that the client will want to boast about their ability to wipe their competitors away with a strategic boast that they are faster, cheaper, safer than any rival. Mercedes happened out of the blue. Something else could drop tomorrow and away we go again.

Just listen to Tim Llewellyn wax lyrical about us. He sees magic with us that a large amount of his marketing to clients is what WE can achieve.

Likewise with ARM. We have been accepted into ARMs partner program. This is a big deal. We are wedding an industry leader with many clients, and they see the absolute advantage we provide them. This happening out there now. We won’t know who, but we will see the revenue.

Likewise with SiFive. They are becoming market leader with RISC-V. Read below.
View attachment 14235
MegaChips. Renesas. Qualcomm. NASA. Nvidia. Socionext. Edge Impulse. All these companies partner us, acknowledge us and market to their clients the outstanding benefits that Akida brings them. Who cares if a few EAP’s drop off. I don’t care because I see the future. And it is ubiquitously Brainchip. And WE are on board.
Greg Cohen replied and Akida is not in the current mission, but Greg is aware of us and potentially may use Brainchip In future projects.

949493EC-70CA-4E89-9731-809A7F1F4737.jpeg
 
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RobjHunt

Regular
Mark my words. It’ll happen!

Pantene.
 
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