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Deena

Regular

Almost $9 billion cybersecurity and intelligence package to be unveiled in federal budget . I wonder if they are astute enough to use Brainchip's cyber security offering. It could save them a lot of money and be far more effective than alternatives!​


 
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davidfitz

Regular

Almost $9 billion cybersecurity and intelligence package to be unveiled in federal budget . I wonder if they are astute enough to use Brainchip's cyber security offering. It could save them a lot of money and be far more effective than alternatives!​


Snap :D
 
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Straw

Guest
Are 4C's normally released in April or May?
Jan/Feb/March reporting period (4C end of April) - sometimes a few days earlier but usually at end of month
 
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Proga

Regular
Well said CEO needs to earn his money not good enough to sit there hoping while shareholders suffer huge losses.
His job is not to concern himself with shareholder value in the short term. He was hired to put the building blocks in place to grow the company exponentially over the mid to long term as BRN transition out of a R&D only into commercialisation.
 
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VictorG

Member
When in doubt!
BRN Protest.jpg
 
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D

Deleted member 118

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AusEire

Founding Member. It's ok to say No to Dot Joining
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Is Neuromorphic Computing Using Edge The Future Of AI?​

By
Victor Dey
-
March 16, 2022
https://www.facebook.com/sharer.php...orphic-computing-using-edge-the-future-of-ai/
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Is-Neuromorphic-Computing-Using-Edge-The-Future-Of-AI

Neuromorphic processors aim to provide vastly more power-efficient operations by modelling the core workings of the brain​

Special Week At The Edge

As artificial intelligence (AI) continues to evolve, it is expected that AI at the edge will become a more significant portion of the current tech market. Known as the AI of Things or AIoT, various processor vendors like Intel and Nvidia have launched AI chips for such lower-power environments, respectively, with their Movidius and Jetson product lines.
Computing at the edge further aids in lower latency than sending information to the cloud. Ten years ago, there were questions about whether software and hardware could be made to work similar to a biological brain, including incredible power efficiency.
Today, the same question has been answered with a yes with advancement in technology, but the challenge now is for the industry to capitalise on neuromorphic technology development and answer tomorrow’s regressive computing challenges.

The Crux Of Neuromorphic Computing​

Neuromorphic computing differs from a classical approach to AI, which is generally based on convolutional neural networks (CNNs), as this technology mimics the brain much more closely through spiking neural networks (SNNs).
Although neuromorphic chips are generally digital, they tend to work based on asynchronous circuits, meaning there is no global clock. Depending upon the specific application, neuromorphic can be ordered to magnitude faster and requires less power. Neuromorphic computing complements CPU, GPU, and FPGA technologies for particular tasks, such as learning, searching and sensing, with extremely low power and high efficiency.
Researchers have lauded neuromorphic computing’s potential, but the most impactful advances to date have occurred in academic, government and private R&D laboratories. That appears to be ready to change.
A report by Sheer Analytics & Insights estimates that the worldwide market for neuromorphic computing will be growing at 50.3 per cent CAGR to $780 million over the next eight years. Mordor Intelligence, on the other hand, aimed lower with $111 million and a 12 per cent CAGR to reach $366 million by 2025.
Forecasts vary, but enormous growth seems likely. The current neuromorphic computing market is majorly driven by increasing demand for AI and brain chips to be used in cognitive and brain robots. These robots can respond like a human brain.
Numerous advanced embedded system providers are developing these brain chips with the help of AI and machine learning (ML) that acts as thinks and responds as the human brain.
This increased demand for neuromorphic chips and software for signal, data, and image processing in automotive, electronics, and robotics verticals is projected to further fuel the market.
The need for potential use cases such as video analysis through machine vision and voice identification has also been projected to aid market growth. Major players for the development include Intel, Samsung, IBM and Qualcomm.
Researchers are still trying to find out where practical neuromorphic computing should go first; vision and speech recognition are the most likely candidates. Autonomous vehicles could also benefit from such human-like learning without human-like distraction or cognitive errors.
BrainChip’s Akida architecture features event-based architecture. It supports on-chip training and inference and various sensor inputs such as vision, audio, olfactory, and innovative transducer applications.
Akida is already featured in a unique product: the Mercedes EQXX concept car, displayed at the CES this year, where it was used for voice control to reduce power consumption by up to 10x. Internet of Things (IoT) and opportunities for Edge range from the factory floor to the battlefield.
Neuromorphic computing will not be directly replacing the modern CPUs and GPUs. Instead, the two types of computing approaches will be complementary, each suited for its sorts of algorithms and applications.

The Potential Underneath​

Neuromorphic computing came to existence due to the pursuit of using analogue circuits to mimic the synaptic structures found in brains.
Our brain excels at picking out patterns from noise and learning. A neuromorphic edge CPU excels at processing discrete, transparent data. For the same reason, many believe neuromorphic computing can help unlock unknown applications and solve large-scale problems that have put conventional computing systems in trouble for decades. Neuromorphic processors aim to provide vastly more power-efficient operations by modelling the core workings of the brain.
In 2011, HRL announced that it had demonstrated its first “memristor” array, a form of non-volatile memory storage that could be actively applied to neuromorphic computing. Two years later, HRL’s first neuromorphic chip, “Surfrider” was released.
As reported by the MIT Technology Review, Surfrider featured 576 neurons and functions on just 50 mW of power. Researchers tested the built chip by adding it into a sub-100-gram drone aircraft loaded with several optical, infrared, and ultrasound sensors and sent the drone into three rooms.
The drone was observed to have “learned” the entire layout and objects present in the first room through sensory input. Later, using this teaching, it could “learn on the fly”, even if it was in a new room or could recognise having been in the same room before.
unnamed-2.jpg
Image Source: MIT
Today, most neuromorphic computing work is incorporated by using deep learning algorithms that perform processing on CPUs, GPUs, and FPGAs. None of these is optimised for neuromorphic processing. However, next-gen chips such as Intel’s Loihi were designed exactly for these tasks and can achieve similar results on a far smaller energy profile. This efficiency will prove critical for the coming generation of small devices needing AI capabilities.
Deep learning feed-forward neural networks (DNNs) underperform neuromorphic solutions like Loihi. DNNs are linear, with data moving from input to output straight. Recurrent neural networks (RNNs) are more similar to the working of a brain, using feedback loops and exhibiting more dynamic behaviour, and RNN workloads are where chips like Loihi shine.
Samsung also announced that it would expand its neuromorphic processing unit (NPU) division by 10x, growing from 200 employees to 2000 by 2030. Samsung said at the time that it expected the neuromorphic chip market to grow by 52 per cent annually through 2023.
One of the future challenges in the neuromorphic space will be defining standard workloads and methodologies for benchmarking and analysis. Benchmarking analysis applications such as 3DMark and SPECint have played a critical role to understand the technology, aiding adopters match products to their needs.
Currently, Neuromorphic computing remains deep in the R&D stage. There are virtually only a few substantial commercial offerings in the field. Still, it’s becoming clear whether specific applications are well-suited to neuromorphic computing or not. Neuromorphic processors will be faster and more power-efficient for extensive workloads than any modern, conventional alternatives.
CPU and GPU computing, on the other hand, will not be disappearing due to such developments; neuromorphic computing will be beside them to handle challenging roles better, faster, and more efficiently than anything we have seen before.
 
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@Fact Finder @Diogenese
Did you guys take a look at this article?
Yes but it was all about the software so I did not take it any further as they did not seem to be claiming a victory over the need for connection and power use. @Diogenese might have found a patent but it could be too early to have surfaced yet.
FF
 
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miaeffect

Oat latte lover
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Yes, I wouldn't want our CEO spending too much time concerning himself with shareholder's concerns. However, I do think that someone at BrainChip needs to be appointed to manage shareholder relations. I think its a mistake in this day and age to think that the quarterlys and an AGM are enough to address the needs of the shareholders. I might be missing something and if I am please let me have it. Don't hold back.
Well you asked for it there is Tony Dawe, Investor Relations, specially appointed to attend to your every shareholder need, in fact they even gave him that title so he could not hide from shareholders. tdawe@brainchip.com

Not only that but they have a firm specifically appointed to deal with US Investors so he has plenty of spare time. Lucky US shareholders.

Why don’t you contact Tony Dawe and ask him to tell you what Brainchip staff do when they are not having short weeks and sickies.

He might have a couple of price sensitive announcements he didn’t think shareholders would be interested in at the moment with all that is going on in Ukraine and the Solomons that he will release if you ask nicely. Tell him FF sent you. LOL

My opinion only DYOR
FF

AKIDA BALLISTA
 
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YLJ

Swing/Position Trader
Where do i listen to the interview , was out and about today with work and so much is happening here dont know where to pick up thank you :p
It is available to Strawman (paid) members only, unfortunately. I do not believe it will be made public.
 
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Violin1

Regular
Yes, I wouldn't want our CEO spending too much time concerning himself with shareholder's concerns. However, I do think that someone at BrainChip needs to be appointed to manage shareholder relations. I think its a mistake in this day and age to think that the quarterlys and an AGM are enough to address the needs of the shareholders. I might be missing something and if I am please let me have it. Don't hold back.
Slade - hope all is good over there. Tony Dawe was appointed for just that. He's very responsive and attended the WA shareholders get together, I'm pretty sure. His contact is tdawe@brainchip.com

I think one issue is that he is also bound by the NDAs of the company and so while we all want lots of news now and maybe think that certain info can't possibly be secret the company is quite conservative about absolutely maintaining the confidence of our customers and potential customers. So Tony will be too. It drives our 1000 eyes crazy but the lack of info makes me even more confident that we are on a winner.
 
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Violin1

Regular
See FF beat me to it!!
 
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Diogenese

Top 20
Hi AusEire,

I did draft a response but it seems to have fallen down the back of the filing cabinet.

"We fully utilised the NPU and AI models for the 16-bit RAW files. A snap will collect twenty shots of the background and users can use up to four cameras for the Ultra model simultaneously," the VP said.

DSLR cameras have large sensors that allow them to take RAW images without noise, but up to now, for smartphones cameras, this has been difficult to emulate in low-light settings as they pack smaller sensors. But with the computational power offered from the NPU on the Galaxy S22 series, their 16-bit RAW files match those taken by DSLR cameras, according to Cho.

"Professionals today want RAW files from their smartphones
.

Akida can utilize up tp 4-bit weights (derived from the library models) and actuations (derived from the camera pixels). It would need a major rejigging of the NPU architecture to include a 16-bit MAC capability, and would significantly diminish speed and power advantages.
#################################################################

We looked at Samsung on 12 March (@Rocket77) #5,093

This related to their 3D tech where they are building the neuron equivalent of the human brain. Their 3D tech is interesting as they stack MemRistors vertically on top of each other.

Hi Rocket577,

The video refers to memRistors a few times.

I looked at Samsung in October last year in the other place:

"Samsung appear to be using memristors in their 3-D NN:

US2021319293A1 NEUROMORPHIC DEVICE AND OPERATING METHOD OF THE SAME
https://worldwide.espacenet.com/pat...456/publication/US2021319293A1?q=US2021319293

an operating method of a neuromorphic device including at least one three-dimensional synaptic array having a plurality of layers, the operating method comprises upon receiving a plurality of input signals independent of each other, performing an artificial neural network computation on the input signals in a plurality of resistive memristor elements of a layer corresponding to a word line selection signal, as a result of the artificial neural network computation, outputting a plurality of output currents to neuron circuits through bit lines, summing the output currents to output a summed output current as an output voltage when it is more than a predetermined threshold and wherein the three-dimensional synaptic array performs an artificial neural network computation independently for each layer activated by the word line selection signal.

1 . A neuromorphic device, comprising:

at least one synaptic array,

wherein the synaptic array includes:

a plurality of input lines extending in a first direction and receiving input signals independently of each other from a plurality of axon circuits connected respectively thereto;

a plurality of bit lines extending in a second direction orthogonal to the first direction and outputting output signals independently of each other;

a plurality of cell strings, each including at least two resistive memristor elements and a string select transistor connected in series in a third direction between any one of the plurality of input lines and any one of the plurality of bit lines;

a plurality of electrode pads stacked while being spaced apart from each other in the third direction between the plurality of input lines and the plurality of bit lines, and connected to the string select transistor and the at least two resistive memristor elements;

a decoder configured to apply a string selection signal or a word line selection signal to each of the plurality of electrode pads; and

a plurality of neuron circuits, each being connected to one of the bit lines connected to one of the cell strings, summing the output signals, converting, and outputting a summed signal when it is more than a predetermined threshold,

wherein the synaptic array performs an artificial neural network computation on the input signals in the resistive memristor elements of a layer activated by the word line selection signal in at least one cell string to which the string selection signal is applied.


1648534970412.png





1648534999197.png

1648535053026.png




1648535083110.png



And they've got a natty arrangement for the synaptic array string (see Fig 6)

Opinions and research expressed are my own as an unlicensed individual. External links are not endorsed. Do your own research or consult a licensed financial advisor.
 
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Build-it

Regular

Almost $9 billion cybersecurity and intelligence package to be unveiled in federal budget . I wonder if they are astute enough to use Brainchip's cyber security offering. It could save them a lot of money and be far more effective than alternatives!​



Josh,
Don't mention Brainchip our partnership has a supertight NDA wrapped around it.

I know you would love to mention how the Gov is collaborating with a unique Australian company that is 3-5 years ahead of the pack.🤪

Edge Compute.
 

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Proga

Regular
I have been hesitant to guess/speculate on the likely sales (to date) as really it is just a guessing game. The use of the word 'mass' production of chips caused a lot of angst amongst holders as to what this actually meant. It was a shame we never got any concrete figures on this!

However, I have to hope that if that number was in the vicinity of 7,000 as previously discussed that this resulted in a similar number of products i.e. Raspberry Pi and later the PCIe Boards. Also there was a mention of production slots being booked for further chips, whatever that really meant is anyone's guess? Did we produce more or were we just waiting for a customer to come on board with an order?? Why book the production slots at all if we were not anticipating a need for them???

So I want to believe that the company would not have hesitated to produce a large number of their products in anticipation of a huge uptake considering they are the first to market in this area. It is then realistic, in my opinion, that the quarterly sales will be much higher than some are thinking.

Of course I base all of this on my assumption on how our company wanted to be perceived by it's likely competitors and the market place in general. A few hundred sales is not what I am expecting, I am hoping to see thousands. The fact that they sold out of the Raspberry Pi indicates a genuine desire for such a product in the market and is encouraging that the demand is there.

If I am right then revenue for this quarter should be up to $5 million but of course you will notice that I use the word 'guess' a lot so I will just wait and see.
I have been hesitant to guess/speculate on the likely sales (to date) as really it is just a guessing game. The use of the word 'mass' production of chips caused a lot of angst amongst holders as to what this actually meant. It was a shame we never got any concrete figures on this!

It was a shame you missed my post
. I said +100k (number of chips for each application sold using Akida technology). I'm hoping quite a few will be in millions. It was in reference of how BRN will generate significant revenue and make a profit. Not just keep the lights on.
 
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Diogenese

Top 20
Josh,
Don't mention Brainchip our partnership has a supertight NDA wrapped around it.

I know you would love to mention how the Gov is collaborating with a unique Australian company that is 3-5 years ahead of the pack.🤪

Edge Compute.
At $20 per chip, that's 450,000,000 chips.
 
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Diogenese

Top 20
Hi AusEire,

I did draft a response but it seems to have fallen down the back of the filing cabinet.

"We fully utilised the NPU and AI models for the 16-bit RAW files. A snap will collect twenty shots of the background and users can use up to four cameras for the Ultra model simultaneously," the VP said.

DSLR cameras have large sensors that allow them to take RAW images without noise, but up to now, for smartphones cameras, this has been difficult to emulate in low-light settings as they pack smaller sensors. But with the computational power offered from the NPU on the Galaxy S22 series, their 16-bit RAW files match those taken by DSLR cameras, according to Cho.

"Professionals today want RAW files from their smartphones
.

Akida can utilize up tp 4-bit weights (derived from the library models) and actuations (derived from the camera pixels). It would need a major rejigging of the NPU architecture to include a 16-bit MAC capability, and would significantly diminish speed and power advantages.
#################################################################

We looked at Samsung on 12 March (@Rocket77) #5,093

This related to their 3D tech where they are building the neuron equivalent of the human brain. Their 3D tech is interesting as they stack MemRistors vertically on top of each other.

Hi Rocket577,

The video refers to memRistors a few times.

I looked at Samsung in October last year in the other place:

"Samsung appear to be using memristors in their 3-D NN:

US2021319293A1 NEUROMORPHIC DEVICE AND OPERATING METHOD OF THE SAME
https://worldwide.espacenet.com/pat...456/publication/US2021319293A1?q=US2021319293

an operating method of a neuromorphic device including at least one three-dimensional synaptic array having a plurality of layers, the operating method comprises upon receiving a plurality of input signals independent of each other, performing an artificial neural network computation on the input signals in a plurality of resistive memristor elements of a layer corresponding to a word line selection signal, as a result of the artificial neural network computation, outputting a plurality of output currents to neuron circuits through bit lines, summing the output currents to output a summed output current as an output voltage when it is more than a predetermined threshold and wherein the three-dimensional synaptic array performs an artificial neural network computation independently for each layer activated by the word line selection signal.

1 . A neuromorphic device, comprising:

at least one synaptic array,

wherein the synaptic array includes:

a plurality of input lines extending in a first direction and receiving input signals independently of each other from a plurality of axon circuits connected respectively thereto;

a plurality of bit lines extending in a second direction orthogonal to the first direction and outputting output signals independently of each other;

a plurality of cell strings, each including at least two resistive memristor elements and a string select transistor connected in series in a third direction between any one of the plurality of input lines and any one of the plurality of bit lines;

a plurality of electrode pads stacked while being spaced apart from each other in the third direction between the plurality of input lines and the plurality of bit lines, and connected to the string select transistor and the at least two resistive memristor elements;

a decoder configured to apply a string selection signal or a word line selection signal to each of the plurality of electrode pads; and

a plurality of neuron circuits, each being connected to one of the bit lines connected to one of the cell strings, summing the output signals, converting, and outputting a summed signal when it is more than a predetermined threshold,

wherein the synaptic array performs an artificial neural network computation on the input signals in the resistive memristor elements of a layer activated by the word line selection signal in at least one cell string to which the string selection signal is applied.


View attachment 3390




View attachment 3391
View attachment 3392



View attachment 3393


And they've got a natty arrangement for the synaptic array string (see Fig 6)

Opinions and research expressed are my own as an unlicensed individual. External links are not endorsed. Do your own research or consult a licensed financial advisor.
AusEire,

I distracted myself when I saw the 16-bit business by drafting an email to Tony asking if a node (4*NPUs) could be configured to handle 16-bit inputs, but then I realized that it's a 16*16 problem, not 16*4, so I did not send the email. Akida 1000 has 80 NPUs.
 
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