BRN Discussion Ongoing

[Fact Finder]

@Fact Finder

Although the listing rule 3.1 mandates us to make continuous disclosures, and having an NDA doesn't excuse us, it appears that if it's considered as a 'trade secret', it can be excluded.

4.20 Commercially sensitive information
Issues can sometimes arise under Listing Rule 3.1 in relation to the disclosure of commercially sensitive matters, such as the pricing given to a major customer or supplier under a material contract. ASX recognises that the disclosure of such information could be used by the entity’s competitors or by other customers or suppliers, to the detriment of the entity and investors in the entity.
Some commercially sensitive information may be a trade secret and therefore protected from disclosure under Listing Rule 3.1A.130 Some commercially sensitive information, however, may be difficult to characterise in that
manner.
ASX has no issue with an entity structuring an announcement about a particular transaction to avoid disclosing
commercially sensitive matters, provided it includes sufficient information in the announcement to enable the market to assess the impact of the transaction on the price or value of the entity’s securities.131
If an announcement is structured in this manner, care must be taken to ensure that it is accurate, includes all material information that would influence investors in deciding whether to buy or sell the entity’s securities and is not misleading. If the announcement is not capable of being drafted to meet these requirements without including the commercially sensitive information, then Listing Rule 3.1 will require the commercially sensitive information to be disclosed. https://www.asx.com.au/documents/rules/gn08_continuous_disclosure.pdf

The risk is in the tail:

“ If the announcement is not capable of being drafted to meet these requirements without including the commercially sensitive information, then Listing Rule 3.1 will require the commercially sensitive information to be disclosed”

The problem with the ASX is they will not give guidance or advice to companies in advance and only step forward to judge after publication when the ASX can direct additional information.

It is a legal nightmare for small growing technology companies on the ASX.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Bravo]

Fact Finder, thank you for graciously coming back into TSE and posting once in a while! As much as I am a hard rusted on LT share holders with a holding timeframe of minimum 2025 it can get dark and gloomy once in a while.

But reading your posts helps me regain perspective and clearing to why I am here and why I have chosen to put my money on Brainchip. The statement that we are only 9 months from the 2023 AGM made my balls skip a beat.

FF for president

I couldn't find any skipping balls, but I found a skipping nut which is pretty close.

 

[Cardpro]

The risk is in the tail:

“ If the announcement is not capable of being drafted to meet these requirements without including the commercially sensitive information, then Listing Rule 3.1 will require the commercially sensitive information to be disclosed”

The problem with the ASX is they will not give guidance or advice to companies in advance and only step forward to judge after publication when the ASX can direct additional information.

It is a legal nightmare for small growing technology companies on the ASX.

My opinion only DYOR
FF

AKIDA BALLISTA

But isn't it saying should the information be considered as a 'trade secret', it can be excluded?

And the above case happened to us for the Megachip agreement

 

[Sirod69]

Global Artificial Intelligence (AI) in Operating Room Market Size, Share | Growth Analysis and Regional Players | 2022-2031​

Global operating room AI market will reach $3,175.4 million by 2031, growing by 41.8% annually over 2021-2031​

New York (US) – Key Companies Covered in the Global Artificial Intelligence (AI) in Operating Room Research are Activ Surgical Inc., Brainomix Limited, Caresyntax Corp, DeepOR S.A.S, ExplORer Surgical Corp., Hanson Meditec Co., Ltd., Holo Surgical Inc., LeanTaaS Inc., Medtronic Plc, Proximie, Scalpel Limited, Theator Inc. and other key market players.

Global Artificial Intelligence (AI) in Operating Room Market Size, Share | Growth Analysis and Regional Players | 2022-2031 - Muleskinner

New York (US) – Key Companies Covered in the Global Artificial Intelligence (AI) in Operating Room R

muleskinner.net

 

[wilzy123]

But reading your posts helps me regain perspective and clearing to why I am here and why I have chosen to put my money on Brainchip.

 

[krugerrands]

Listen from about 2:10
Jim Keller apparently is working on the most powerful processor ever that mimics the human brain and stat it will be much more revolutionary then the Internet. Words from Jordan P. I tend to listen to this bloke when he speaks.

Now what is this chip and how does it stack up to Akida? No matter what, it is more validation by industry veterans that we are on the right track!

Well that sent me down a rabbit hole.

What links AMD CPU guru Jim Keller, an AI chip upstart, and SiFive? This vector-crunching 64-bit RISC-V processor

Stressing the ex in x86

www.theregister.com

"Canadian AI chip startup Tenstorrent, which is headed by former top AMD engineers, has picked one of SiFive's latest RISC-V CPU designs for its unconventional machine-learning processors.


Specifically, Tenstorrent will license SiFive's Intelligence X280 processor cores to slot them into its homegrown AI training and inference chips alongside its own Tensix cores."


Forward one year.

BrainChip and SiFive Partner to Deploy AI/ML Technology at the Edge

BrainChip and SiFive partner to combined their respective technologies to offer chip designers optimized AI/ML compute at the edge.

brainchip.com

“Employing Akida, BrainChip’s specialized, differentiated AI engine, with high-performance RISC-V processors such as the SiFive Intelligence Series is a natural choice for companies looking to seamlessly integrate an optimized processor to dedicated ML accelerators that are a must for the demanding requirements of edge AI computing,” said Chris Jones, vice president, products at SiFive. “BrainChip is a valuable addition to our ecosystem portfolio”.

 

[Fact Finder]

But isn't it saying should the information be considered as a 'trade secret', it can be excluded?

Yes it is but even if it is a trade secret the ASX can still compel its disclosure if it determines the information released is not sufficient in the opinion of the ASX for the market to properly value the earlier disclosure.

When you read the cases on disclosure Judges approach the question from the position that the information must be complete and sufficient to allow a level playing field and a fair market for every investor even irrational retail investors (particularly irrational retail).

So if a company wants to announce a contract with “X” they must provide sufficient information to allow the market to correctly value the contract so that an overall valuation of the company can be arrived at even if this means disclosing commercially sensitive information.

The ASX judges the adequacy of the information after the event and could direct a company as it has with Brainchip now on two occasions to provide more information after the first disclosure and thereby force the disclosure of commercially sensitive information against Brainchips and the customers interests.

In doing so a trade secret may be put at risk.

Companies should not take risks that may lead to detriment being suffered by shareholders.

A responsible Board and Management will ensure that these risks are avoided by not taking them in the first place.

I have no idea if Apple is engaged with Brainchip but Apple is famous for dumping small technology companies that breach NDAs to get the word out they are working with Apple and just walking away.

Giving complete confidentiality to potential and actual customers is part of what we as shareholders should expect of Brainchip because this is what customers demand in this space.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Bravo]

Exactly. Nintendo has only the Switch console in program by now. An update is coming 2023. The technical dates of it been leaked earlier this year, no Akida inside. According to the usually well informed games scene a new console will not appear earlier than 2026. When there comes a new console with new in game functionalities, it first needs new games which can handle the new features. Games have a very long development cycle, there is no way to speed this up.
So anything about controller updates is much closer to reality than speculations on a brandnew console coming soon containing Akida IP.

I don't think anyone could say 100% that there won't be Akida inside in the update in 2023. I understand what you're saying about the fact that new games may have to be developed to utilize Akida to the fullest capacity and the development time-frame creating new games is particularly long.

But there's no way of knowing that Akida won't be in the upgrade to assist with other things like AI, self-learnig features, noise reduction, etc, whilst new games are being developed. Just a thought?

 

[Izzzzzzzzzzy]

I DON'T KNOW ABOUT ANYONE ELSE, BUT I"M GETTING VERY EXCITED!!!!!!!

The new Mercedes EQE SUV will make its official world debut on October 16 2022!

So, we all know that Mercedes-Benz, plans to officially launch MB.OS in 2024. But what is less well-known is that from 2022 to 2023, Mercedes-Benz will be equipped with a lightweight version of the MB.OS operating system on the next generation of new E-class models, before the full version of the MB.OS operating system is launched in 2024.

Here are some snippets from various articles about the EQE SUV which are making me feel obligated to dash off to Dan Murphy's to top-up my diminishing supply of champers!





View attachment 15305




View attachment 15306

View attachment 15307





View attachment 15308

Mercedes EQE SUV: This is the first look into the cabin of the off-road electric 'E'

After the electric Mercedes-Benz EQS SUV, Stuttgart is preparing the premiere of its smaller sibling […]

www.nautiv.com

Set up a team of 10,000 people to challenge the vehicle operating system, what are the odds of Mercedes-Benz?

www.laitimes.com

First Look Review: The Mercedes EQE SUV is the GLE of the future

The Mercedes EQE SUV, the all-rounder model variant of the EQE provides a pure-electric alternative to the Mercedes GLE. Here's our experience with the electric vehicle.

topelectricsuv.com

Rich before 2025, I’ll take it

 

[Fact Finder]

FF.

In reference.

4. Income will eventually be primarily royalties at a factor of at least four to five times any licence fee as a starting point.

I agree it is on record. I never truly understood the true meaning. Did Sean mean return in total or a factor per annum?

What is your interpretation of said statement? I prefer an answer that gives a per annum return

I personally think you can argue two ways:

1. As income is reported quarterly and licence fees are reported on this basis he could mean quarterly, or

2. As the Annual Report is final arbiter of the years performance he could mean annually.

I think 2. because he is American and quarterly reporting is not a thing required by the SEC.

My wild speculation so DYOR
FF

AKIDA BALLISTA

 

[Fullmoonfever]

I personally think you can argue two ways:

1. As income is reported quarterly and licence fees are reported on this basis he could mean quarterly, or

2. As the Annual Report is final arbiter of the years performance he could mean annually.

I think 2. because he is American and quarterly reporting is not a thing required by the SEC.

My wild speculation so DYOR
FF

AKIDA BALLISTA

Think will have to be quarterly as the SEC does require same re unaudited qtrly accounts with clear, comprehensive financial info etc same as ASX.

 

[Fact Finder]

Think will have to be quarterly as the SEC does require same re unaudited qtrly accounts with clear, comprehensive financial info etc same as ASX.

Was not what I read recently but I am an Australian so I will go with your view if you have absolutely no doubt you are correct.
Regards
FF

 

[David holland]

Why anyone would sell their shares is beyond me? One day we'll be traveling to MARS thanks to AKIDA!!!!!!!!

View attachment 15327

Yeah right o mate, at Xmas I'll be very disappointed if where not $2

 

[Foxdog]

SP has bounced of 80c 3 times in the last couple of months. It may get tested again. Hopefully not.

Mi bi maw if it duz

 

[Fullmoonfever]

Was not what I read recently but I am an Australian so I will go with your view if you have absolutely no doubt you are correct.
Regards
FF

Maybe changed last 12 mths?

SEC Form 10-Q: Definition, Deadlines for Filing, and Components

Learn about SEC Form 10-Q, a comprehensive report of a company's business and financial performance submitted to the SEC quarterly by all public companies.

www.investopedia.com

 

[equanimous]

​

DPSNN: A Differentially Private Spiking Neural Network​

Privacy-preserving is a key problem for the machine learning algorithm. Spiking neural network (SNN) plays an important role in many domains, such as image classification, object detection, and speech recognition, but the study on the privacy protection of SNN is urgently needed. This study combines the differential privacy (DP) algorithm and SNN and proposes differentially private spiking neural network (DPSNN). DP injects noise into the gradient, and SNN transmits information in discrete spike trains so that our differentially private SNN can maintain strong privacy protection while still ensuring high accuracy. We conducted experiments on MNIST, Fashion-MNIST, and the face recognition dataset Extended YaleB. When the privacy protection is improved, the accuracy of the artificial neural network(ANN) drops significantly, but our algorithm shows little change in performance. Meanwhile, we analyzed different factors that affect the privacy protection of SNN. Firstly, the less precise the surrogate gradient is, the better the privacy protection of the SNN. Secondly, the Integrate-And-Fire (IF) neurons perform better than leaky Integrate-And-Fire (LIF) neurons. Thirdly, a large time window contributes more to privacy protection and performance.

PDF Paper record
Table 1: The test accuracy of Net2-SNN and Net2-ANN with same privacy bound on MNIST dataset.

σ	SNN-Accuracy(%)	ANN-Accuracy(%)	MA-ε	CLT-ε	CLT-μ
1.6	97.96	95.35	1.46	1.32	0.35
1.3	98.19	96.57	1.93	1.74	0.44
1.0	98.36	97.31	2.93	2.60	0.63
0.7	98.55	97.95	6.55	5.31	1.18
0.5	98.63	98.45	23.20	21.65	3.66

Table 2: The test accuracy of Net2-SNN and Net2-ANN with same privacy bound on Fashion-MNIST dataset.

σ	SNN-Accuracy(%)	ANN-Accuracy(%)	MA-ε	CLT-ε	CLT-μ
1.6	87.31	83.82	1.61	1.46	0.38
1.3	87.51	84.75	2.23	2.02	0.51
1.0	87.93	85.90	3.55	3.18	0.76
0.7	88.34	87.72	8.28	7.02	1.49
0.5	88.37	88.33	24.98	23.77	3.93

Table 3: The best test accuracy in 80 epochs under different noise scale on Extended YaleB dataset.

σ	Accuracy(%)	MA-ε	CLT-ε	CLT-μ
2.5	99.30	2.21	1.96	0.49
2.0	99.58	3.05	2.71	0.66
1.5	99.55	4.42	3.89	0.9

Table 4: The accuracy and privacy bound of differentially private spiking neural network (DPSNN) under different time windows

	Accuracy(%)	MA-ε	CLT-ε	CLT-μ
Time Window T	5	87.93	3.55	3.18	0.76
Time Window T	10	88.49	3.43	3.06	0.73
Time Window T	15	89.0	3.45	3.09	0.74

https://paperswithcode.com/paper/dpsnn-a-differentially-private-spiking-neural/review/

 

[Cardpro]

Just a quick question, from the half yearly report, it says that "Increase in revenue is a result of the partnership with MegaChips and predominantly comprised licensing revenues of Akida recognised in the current period." <- does that mean the revenue is from MegaChips + Licensing Revenues of Akida (possibly from other companies?) or is it saying it's from MegaChips (which includes the licensing revenue from them)?

 

[Fact Finder]

Where I picked up this idea was looking at the idea of a Nasdaq listing and I read about special provisions for Emerging Growth Companies which would cover at face value Brainchip if it chose to move to the Nasdaq.

My first reading indicated that reporting conditions were greatly reduced and now on a second reading it seems that the level and type of reporting is determine on a case by case basis so I am unable to say if my first impression was correct. It does seem that annual reporting requires full disclosure.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Fact Finder]

Where I picked up this idea was looking at the idea of a Nasdaq listing and I read about special provisions for Emerging Growth Companies which would cover at face value Brainchip if it chose to move to the Nasdaq.

My first reading indicated that reporting conditions were greatly reduced and now on a second reading it seems that the level and type of reporting is determine on a case by case basis so I am unable to say if my first impression was correct. It does seem that annual reporting requires full disclosure.

My opinion only DYOR
FF

AKIDA BALLISTA

@Fullmoonfever above was for you I did not attach it properly.

 

[equanimous]

[AI Seminar] Limitations of Neuro AI​

Aug 9, 2021
In the fifth AI seminar, we had the opportunity to listen to a lecture on the 'Limitations of Neuro AI' given by senior researchers from LG Electronics AI Research Center, Kim Ko-keun and Kim Jae-hong. The lecture was divided into two sessions. The first session introduced Neuromorphic and Neuro-symbolic AIs, and the second session dealt with some research cases in the field of Neuro-symbolic AI.

Session 1: Neuromorphic AI and Neuro-symbolic AI​

Over the past few years, the field of AI made a big leap forward with great improvements in processing capacity and computational efficiency as well as new insight in deep learning. Despite the developments, AI still has limitations. How can these limitations be overcome?
There are many ways to approach them, but in this session, we took a look at "Hyperscale AI", "Neuromorphic AI", and "Neuro-symbolic AI."

3 ways to overcome the limitations of Neuro AI

1. Hyperscale AI​

'Hyperscale AI' uses computing infrastructure with high computation speed to learn large volumes of data.
LG Electronics plans to invest at least 100 million dollars in AI computing infrastructure over the next three years to develop Hyperscale AI that thinks, learns and makes decisions on its own. That is a huge investment, right? It will be the first investment of this scale in this field made by a global manufacturing company. LG Electronics will continue its efforts to improve customer values through Hyperscale AI, by enhancing service quality, shortening product development process, and more.

2. Neuromorphic AI​

The human brain has more than 150 trillion neuronal junctions called synapses, which are used by neurons to exchange signals with other neurons, and processes information in a split second. The high computational and decision-making speeds of a human brain cannot yet be matched by the highest-quality AI there is. The trend now is to mimic the human brain to achieve a higher processing speed, and a synaptic information transfer system called the spiking neural network is emerging as a new key in AI. AI that mimics the neural structure of the human body is called “Neuromorphic AI.”
Neuromorphic AI lets the computer imitate the parallel processing of the human brain rather than use serial processing in order to remember and compute large amounts of data simultaneously. Many efforts are currently being made to narrow the gap between the human brain and AI.

Comparison of human neural networks and AI computational processing methods

3. Neuro-symbolic AI​

Do you remember that the title of the fourth AI seminar was “Can deep learning teach rationality, ethics and philosophy from real life?” We had already dealt with "Neuro-symbolic AI" in that seminar, and we re-visited the subject in this lecture. Certainly, this tells us how hot this topic is in the field of AI at the moment.
Neuro-symbolic AI combines deep learning with reasoning and application capabilities. It enables the computer to understand human languages and dialogs better and is being used as an important measure of development in the field of natural language processing. If the development of Neuro-symbolic AI can be accelerated, we will soon be able to see our voice assistants and chatbots giving us helpful answers to most of our questions rather than nonsense ones.

Session 2: Neuro-symbolic AI research cases​

Neuro-symbolic AI is categorized into six types as illustrated in the figure below.
The most prominent of these at the moment is the third one, which uses a neural model to sense objects and a symbolic model to reason. In the second session, we looked at research cases on this particular type of neuro-symbolic AI, focusing on formula and research trends.

6 Types of Neuro-Symbolic Systems

Although AI technology is growing at a rapid pace, it has not yet reached a level comparable to human intelligence. However, as the gap between humans and AI gets narrower and the AI technology more sophisticated, the AI will be able to better understand our thoughts and communicate with us more smoothly.
Let’s hope that the "Hyperscale AI", "Neuromorphic AI" and "Neuro-symbolic AI" technologies can enable the AI to more deeply understand humans and provide more beneficial answers to human society.

Overcoming the limitations of Neuro AI by Hyperscale AI, Neuromorphic AI, and Neuro-symbolic AI.

ThinQ.AI is also making strides to reach a point where it does not need any human intervention to function.
This September, LG Electronics will be releasing the knowledge-based ThinQ.AI 5.0 to offer real values to customers. Please look forward to experiencing this product.