BRN Discussion Ongoing

[Chilling]

Thanks for the valuation replies very interesting reading is a waiting game from here unfortunately people have different financial and life commitments so not everyone can operate on the same time frames.
Let's hope revenue flows sooner rather than later and we get back to a fair value can't say anyone has enjoyed this latest dip.

 

[Labsy]

At the risk of being accused of having a one-track mind, I'm going to bring up Cerence again.

I was browsing through a press release from the 9th August 21 and it says that Cerence "today announced a new quarterly record: the start-of-production (SOP) of its industry-leading automotive technologies in 61 new car models from 16 global automakers in its Q3 2021".

It goes on to state "This milestone signals ongoing adoption of Cerence’s conversational AI solutions for mobility and a new wave of integrated in-car assistant experiences that will soon be available to consumers. The achievement spans 32 brands from many of the most recognizable names in the global automotive industry, including BMW, Ford, GM, Jaguar Land Rover, Daimler, Honda, Renault, Stellantis, Toyota, and Volkswagen Group as well as leading Chinese OEMs BJEV, Chery, Geely, Great Wall Motors, Human Horizons, and SAIC."

Now we know that Cerence knows that it's BrainChip's Akida that enables 5 to10 times better performance and efficiency than conventional voice control systems. How do we know this? Because Mercedes have unequivocally stated this much in regards to the operation of its MBUX infotainment system. So what I am going to suggest is that it would be extremely unlikely and in my opinion completely unheard of if Cerence wouldn't continue to float out this winning formula/collaboration for other brands for their future EV models, rather than risk losing customers by offering an alternative, outdated, inefficient voice control system?

The second point I was going to make is about time-frames by which we can expect to see Akida hit the EV market in a really big way and that comes from an extract I found in an article by Kirsten Korosec dated 11 Janaury 22 in which she says "And then there is Mercedes-Benz and its EQXX concept. This isn’t meant to be your typical we’ll-never-see-this-again concept car.The EQXX is meant to showcase what the automaker’s electric future will look like and includes a ton of tech and features, which Markus Schäfer, a board member of Daimler AG and CTO of Mercedes-Benz AG, told me will show up in vehicles beginning in 2024". View attachment 2432

Cerence Achieves Record Starts-of-Production (SOPs) for its Industry-Leading Conversational AI Products in 61 New Car Models from 16 Global Automakers in Most Recent Quarter

BURLINGTON, Mass., Aug. 09, 2021 (GLOBE NEWSWIRE) -- Cerence Inc. (NASDAQ: CRNC), AI for a world in motion, today announced a new quarterly record: the start-of-production (SOP) of its industry-leading automotive technologies in 61 new car models from 16 global automakers in its Q3 2021. This...

au.sports.yahoo.com

The Station: A special CES galaxy brain edition | TechCrunch

The Station is a weekly newsletter dedicated to all things transportation. Sign up here — just click The Station — to receive it every weekend in your

techcrunch.com

400 million cars shipped with cerence to date...and more to come...much more!!!
Let's assume then conservatively 15dollars per ip licence x 400million...
And this being just 1 industry... wow the mind boggles...yes sp 200 definitely in the realm of possibility. 60bill market cap easy.

 

[Fact Finder]

Long term investors will be aware of the past links and ties between Brainchip and Auckland University and that this research paper is exploring an area where AKIDA technology will have a direct beneficial application:

Prediction of Acoustic Residual Inhibition of Tinnitus Using a Brain-Inspired Spiking Neural Network Model - PMC

Auditory Residual Inhibition (ARI) is a temporary suppression of tinnitus that occurs in some people following the presentation of masking sounds. Differences in neural response to ARI stimuli may enable classification of tinnitus and a tailored ...

www.ncbi.nlm.nih.gov

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Fact Finder]

Ok this might be significant but as I stumbled onto this link I did not want to loose it so have not yet tried to translate:

Zhen Jia on LinkedIn: 脉冲神经网络（Spiking Neural Network） https://lnkd.in/gF8RnUNk

脉冲神经网络（Spiking Neural Network） https://lnkd.in/gF8RnUNk

www.linkedin.com

Apologise in advance if it is a DELL fizz but as I am away from home and access to my PC to do a translation others amongst the 1,000 Eyes are welcome to try.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Taproot]

Ok this might be significant but as I stumbled onto this link I did not want to loose it so have not yet tried to translate:

Zhen Jia on LinkedIn: 脉冲神经网络（Spiking Neural Network） https://lnkd.in/gF8RnUNk

脉冲神经网络（Spiking Neural Network） https://lnkd.in/gF8RnUNk

www.linkedin.com

Apologise in advance if it is a DELL fizz but as I am away from home and access to my PC to do a translation others amongst the 1,000 Eyes are welcome to try.

My opinion only DYOR
FF

AKIDA BALLISTA

In summary, Spiking Neural Network (SNN), as the third-generation neural network technology, has very prominent features and advantages, but at the same time its development is also full of challenges.

Although the current development of spiking neural network is far from mature and full of controversy, its research interest is still high, and major IT giants have also included it in their current strategic deployments.

As a high-tech company oriented towards technological innovation, Dell Technologies Group has its own advantages and potentials in the research and development of spiking neural networks:

• With a rich and mature IT infrastructure ecosystem , it can provide sufficient hardware and software conditions for the research and development of neuromorphic computing;
• With profound technology reserves and industry experience accumulation , it has laid a solid foundation for the research of various cutting-edge technologies including neuromorphic computing;
• The development concept with technological innovation as the core has penetrated into all levels of Dell , and has the potential to study various cutting-edge technologies;
• It has accumulated a large number of strategic partners , and has maintained close cooperation with a large number of cutting-edge technology companies.

 

[Baisyet]

Ok this might be significant but as I stumbled onto this link I did not want to loose it so have not yet tried to translate:

Zhen Jia on LinkedIn: 脉冲神经网络（Spiking Neural Network） https://lnkd.in/gF8RnUNk

脉冲神经网络（Spiking Neural Network） https://lnkd.in/gF8RnUNk

www.linkedin.com

Apologise in advance if it is a DELL fizz but as I am away from home and access to my PC to do a translation others amongst the 1,000 Eyes are welcome to try.

My opinion only DYOR
FF

AKIDA BALLISTA

Some how I am unable to to copy paste it

 

[Bravo]

Ohhh... OK. So that's how this stuff works.

In that case, I "predict" it's Akida!

Page not found - Arover

www.arover.net

Valeo innovations for safer and cleaner mobility will be presented at the IAA Mobility 2021

The IAA will be held in Munich this year for the first time in the show's history, and will be renamed IAA Mobility for the occasion.

www.valeo.com

 

[Fact Finder]

In summary, Spiking Neural Network (SNN), as the third-generation neural network technology, has very prominent features and advantages, but at the same time its development is also full of challenges.

Although the current development of spiking neural network is far from mature and full of controversy, its research interest is still high, and major IT giants have also included it in their current strategic deployments.

As a high-tech company oriented towards technological innovation, Dell Technologies Group has its own advantages and potentials in the research and development of spiking neural networks:

• With a rich and mature IT infrastructure ecosystem , it can provide sufficient hardware and software conditions for the research and development of neuromorphic computing;
• With profound technology reserves and industry experience accumulation , it has laid a solid foundation for the research of various cutting-edge technologies including neuromorphic computing;
• The development concept with technological innovation as the core has penetrated into all levels of Dell , and has the potential to study various cutting-edge technologies;
• It has accumulated a large number of strategic partners , and has maintained close cooperation with a large number of cutting-edge technology companies.

Thanks Taproot
At home now and the article is actually significant but the translation offends the 3,000 character limit so we need someone to create a PDF and post it here then @Diogenese can be politely asked to read the entire paper and confirm that all of the limitations the paper refers too have been solved by Brainchip's AKIDA technology revolution.

Now this will give rise to two things if as I believe they have been solved:

1. As Rob Lincourt of DELL Techonologies stated that they were first attracted to the early power figures (which we all worked out had to be at least back in at least 2019) and confirmed that since that time they had been testing its scalability etc; the failure of the author who specialises in SNN Research at DELL to list Brainchip with Intel and IBM only three months ago has to be VERY SIGNIFICANT.

2. If Brainchip's AKIDA technology does not suffer from any of the problems listed by the author many of which have been identified as applicable to Intel and IBM the neuromorphic pretenders then I personally would be comfortable in saying that DELL is in deep stealth mode where Brainchip and AKIDA are concerned and they are working on major projects implementing AKIDA's "cutting edge technology" ahead of all the world or at least all their competitors.

So I await the creation of the PDF and the @Diogenese verdict.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[supersonic001]

Continuing growth of team good to see, could this be for refinement of current tech or toward the nxt gen of Akida series…..

 

[Fact Finder]

Thanks Taproot
At home now and the article is actually significant but the translation offends the 3,000 character limit so we need someone to create a PDF and post it here then @Diogenese can be politely asked to read the entire paper and confirm that all of the limitations the paper refers too have been solved by Brainchip's AKIDA technology revolution.

Now this will give rise to two things if as I believe they have been solved:

1. As Rob Lincourt of DELL Techonologies stated that they were first attracted to the early power figures (which we all worked out had to be at least back in at least 2019) and confirmed that since that time they had been testing its scalability etc; the failure of the author who specialises in SNN Research at DELL to list Brainchip with Intel and IBM only three months ago has to be VERY SIGNIFICANT.

2. If Brainchip's AKIDA technology does not suffer from any of the problems listed by the author many of which have been identified as applicable to Intel and IBM the neuromorphic pretenders then I personally would be comfortable in saying that DELL is in deep stealth mode where Brainchip and AKIDA are concerned and they are working on major projects implementing AKIDA's "cutting edge technology" ahead of all the world or at least all their competitors.

So I await the creation of the PDF and the @Diogenese verdict.

My opinion only DYOR
FF

AKIDA BALLISTA

I have stolen this link from the DELL thread. It was posted by Perhaps from Germany:

https://au.linkedin.com/in/chris-mitre-215176a8

Probably is just a Brainchip shareholder ramping the company - Just reminiscing about HC and thought I would throw in some nostaglia.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Baisyet]

I have stolen this link from the DELL thread. It was posted by Perhaps from Germany:

https://au.linkedin.com/in/chris-mitre-215176a8

Probably is just a Brainchip shareholder ramping the company - Just reminiscing about HC and thought I would throw in some nostaglia.

My opinion only DYOR
FF

AKIDA BALLISTA

Just checked it and looks like he is liking all that Brainchip post hmm

 

[Bravo]

Has anyone else heard of this? A new app has been developed at Princeton University using neural netwroks and edge AI to detect COVID-19 from Smartwatch sensors. Their models are purportedly 98.1% accurate at detecting COVID-19.

AI detects COVID-19 from smartwatch sensors

Combining questions about a person's health with data from smartwatch sensors, a new app developed using research at Princeton University can predict within minutes whether someone is infected with COVID-19.

healthcare-in-europe.com

 

[Deleted member 118]

Bosch

 

[Bravo]

Check out the 17 minute mark where Tanja Ruckert talks about a new Bosch product featuring AI called the Home Connect Fridge "which can identify its contents and suggest recipes based on what's inside."

Either Tanja was following me on Hotcrapper or it's one hell of a coinkidink!

Bosch

 

[Deleted member 118]

Not had a chance to listen to it yet.

 

[Fact Finder]

When you go hunting ARM's website under Ai you will find a section Partner Ecosystem Catalogue.

It is broken up in a number of different ways to search for an ARM partner the one that grabbed my attention was the search for an ARM partner by Industry and I found the following:

Automotive: Edge Impulse, Renesas
Wearables: Edge Impulse, Renesas
Mobile: Edge Impulse, Renesas
Frameworks & Tools: Edge Impulse, Renesas
Industrial: Edge Impulse, Renesas
Healthcare: Edge Impulse, Renesas

Then if you search by Geographic Location:

North America: Edge Impulse, Renesas

Now the interesting thing beyond the obvious at least to me is that the partners under these categories are not listed alphabetically. Edge Impulse has been a partner to ARM for a very long time. Edge Impulse comes up first on all these lists.

Whereas Renesas which is a larger more significant company by a country mile than Edge Impulse is well down the list. Renesas on this basis is a more recent inclusion.

If ARM did not want to be directly linked to Brainchip as has been discussed Renesas provides a way to shield their involvement with each other.

@ManChildreborn has pushed the ARM connection for a long time now and has found many dots and the above are just a few more but with Renesas being a Brainchip licensee, Edge Impulse having been on the Brainchip podcast with Rob Telson, Brainchip being littered with ARM personnel if a full blown connection is found it will probably not surprise many here I suspect.

For some reason I cannot post the link so Google ARM Ai Partner Ecosystem Catalogue

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Deleted member 118]

When you go hunting ARM's website under Ai you will find a section Partner Ecosystem Catalogue.

It is broken up in a number of different ways to search for an ARM partner the one that grabbed my attention was the search for an ARM partner by Industry and I found the following:

Automotive: Edge Impulse, Renesas
Wearables: Edge Impulse, Renesas
Mobile: Edge Impulse, Renesas
Frameworks & Tools: Edge Impulse, Renesas
Industrial: Edge Impulse, Renesas
Healthcare: Edge Impulse, Renesas

Then if you search by Geographic Location:

North America: Edge Impulse, Renesas

Now the interesting thing beyond the obvious at least to me is that the partners under these categories are not listed alphabetically. Edge Impulse has been a partner to ARM for a very long time. Edge Impulse comes up first on all these lists.

Whereas Renesas which is a larger more significant company by a country mile than Edge Impulse is well down the list. Renesas on this basis is a more recent inclusion.

If ARM did not want to be directly linked to Brainchip as has been discussed Renesas provides a way to shield their involvement with each other.

@ManChildreborn has pushed the ARM connection for a long time now and has found many dots and the above are just a few more but with Renesas being a Brainchip licensee, Edge Impulse having been on the Brainchip podcast with Rob Telson, Brainchip being littered with ARM personnel if a full blown connection is found it will probably not surprise many here I suspect.

For some reason I cannot post the link but a Google of Ai Partner Ecosystem Catalogue

My opinion only DYOR
FF

AKIDA BALLISTA

I found an interesting video, let’s see if I can find it again.

 

[Deleted member 118]

Mobile-eye

 

[Deleted member 118]

Samsung

 

[Diogenese]

Thanks Taproot
At home now and the article is actually significant but the translation offends the 3,000 character limit so we need someone to create a PDF and post it here then @Diogenese can be politely asked to read the entire paper and confirm that all of the limitations the paper refers too have been solved by Brainchip's AKIDA technology revolution.

Now this will give rise to two things if as I believe they have been solved:

1. As Rob Lincourt of DELL Techonologies stated that they were first attracted to the early power figures (which we all worked out had to be at least back in at least 2019) and confirmed that since that time they had been testing its scalability etc; the failure of the author who specialises in SNN Research at DELL to list Brainchip with Intel and IBM only three months ago has to be VERY SIGNIFICANT.

2. If Brainchip's AKIDA technology does not suffer from any of the problems listed by the author many of which have been identified as applicable to Intel and IBM the neuromorphic pretenders then I personally would be comfortable in saying that DELL is in deep stealth mode where Brainchip and AKIDA are concerned and they are working on major projects implementing AKIDA's "cutting edge technology" ahead of all the world or at least all their competitors.

So I await the creation of the PDF and the @Diogenese verdict.

My opinion only DYOR
FF

AKIDA BALLISTA

"Your mission, Diogenese, should you choose to accept it ... "

real biological nervous system simulation is too complex: the working principle of biological neural networks has been generally mastered by researchers in years of research, but the structural details of neural networks in real organisms are still an unsolved mystery due to their complexity, which is a great problem for designing neural computing systems based on real biological nervous systems.

Akida does not attempt to produce an anatomically correct neuron. Instead it provides a digital analog.

Digital neurons are a step removed from analog neurons in replication the anatomical neuron, but they are capable of effectively performing the function of a neuron for the purposes of input classification.

Indeed, Ella reminds us: 'tain't what you do - it's the way that you do it.'

As PvdM is entitled to say: "I did it my way."

the challenge of applying to real scenes is that if a human-designed pulsed neural network is used, it is generally more suitable for continuous recognition and inference of dynamic scenes according to its characteristics. however, in the actual application process, how to make the scene fully utilize the low-power and high-speed rate of the pulse neural network and the event-driven characteristics, so as to distinguish it from the second-generation artificial neural network technology to highlight and benefit from its advantages, requires more specific and detailed exploration of the application scenario. at the same time, the application and development of pulsed neural networks also depend on the development of neural computing chips, due to its new design structure and computing mode, it is not possible to achieve the effect it should theoretically achieve on traditional chips.

I have fallen behind in my Japanglish classes, so my response is "Yes it is."

limitations of pulse train coding: the information transfer in pulse neural networks is based on pulse train, which involves encoding the general real input information into a pulse train. there are currently two main types of coding methods for pulse trains: frequency-based coding and time-based coding. for the former, it ignores the time structure inside the sequence, and the precise information in the sequence may be ignored; while the latter can make a more efficient and accurate representation of information, with stronger bio-authenticity. however, most current pulse neural network algorithms focus on frequency coding, so time-based coding algorithms still need to be explored.

PvdM tried the rest, now he uses the best. Akida uses pulse-rank-coding:

The following passage from US20210027152 explains the difference between rate coding and rank coding.
https://worldwide.espacenet.com/pat...98/publication/US2021027152A1?q=us20210027152

[0054] Rate coding is shown in the top panel 310. The spikes received by two input synapses 320, 330 of a multitude of synapses are shown over one complete integration period labeled t1, in a plurality of integration periods. The first synapse received 25 spikes, while the second synapse received 27 spikes during this integration period. The sum of all synapses is 52, which is the simulated membrane potential of the neuron. Subsequently a non-linear function such as Tanh or a linear rectifier (ReLU) function is applied to the simulated output value. The resulting output value is transmitted as a series of spikes to one or more synapses in the next neural layer. The integration time is long to allow sufficient spikes to occur to receive a value.


In the lower left panel 33(4)0, rank coding is illustrated. The spikes received by four of a multitude of synapses is shown for six integration periods labeled t0 to t5. The integration time is short, and repeating spikes within each integration period are ignored. The integrated value for the first integration period is three, and four in the subsequent four integration periods. The last integration period has the value 2. These values (∑) are the simulated membrane potential of the neuron. If the simulated membrane potential reaches or exceeds a threshold value, a spike is transmitted to one or more synapses in the next neural layer. In the middle right hand panel 350, the integration method of a section of a neuron of a plurality of neurons in a conventional perceptron is shown. A collection of weight values labeled W11 to W95 are multiplied with input values I0 to I9.The resulting values are accumulated to form the neuron simulated membrane potential. Subsequently a non-linear function such as Tanh or a linear rectifier (ReLU) function is applied to the simulated output value. The resulting output value is transmitted as an integer or floating-point value to one or more synapses in the next neural layer. In the lower right-hand panel 370, a conventional binary coding method is shown for reference. Binary coding schemes are widely used in conventional computer systems to encode characters and numbers. Boolean algebra is applied to compute with binary coded numbers and characters.

difficulty in training learning: for direct training of pulsed neural networks, most of the supervised learning methods are based on gradient settings and lack bio rationality; another way to obtain a trained pulsed neural network model is to directly transform the trained traditional neural network, but this transformation is limited by the loss of accuracy caused by many aspects. therefore, compared with the current mature artificial neural networks, the training and learning of pulsed neural networks on real large deep networks still has a long way to develop.

The proof of the pudding ... Ask @uiux.

application accuracy is lower for more complex tasks: pulsed neural networks have been controversial for a long time, and one of the reasons is that their performance in terms of application accuracy is often inferior to that of traditional ai networks. both the coding and training learning issues described above can lead to an impact on the accuracy of their application to more complex tasks. therefore, how to improve the application accuracy of pulse neural networks while retaining their original advantages and characteristics is also a major challenge for the future development of pulse neural networks.

https://www.hackster.io/news/brainc...work-accelerators-go-mass-market-2a6572c67c50

On the question of accuracy, the 4-bit Akida stacks up very well against 32-bit CNNs.

Once again, I rest my briefs.