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BRN Discussion Ongoing
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equanimous
Norse clairvoyant shapeshifter goddess
Fact Finder
Top 20
Well we will be right here in Sydney the Brush Turkey numbers are back to where they were during the Great Depression so we will all have something to eat.
Not as many rabbits as back then but we now have more vegetarians so probably evens out.
A recession can even be technical a depression never.
Relax the Markets will calm. These sort of reactions are fuelled by opportunistic traders and institutions and are what some build great wealth upon. Next week the only retail who remember will be those who panicked.
My opinion only DYOR
FF
AKIDA BALLISTA
Not as many rabbits as back then but we now have more vegetarians so probably evens out.
A recession can even be technical a depression never.
Relax the Markets will calm. These sort of reactions are fuelled by opportunistic traders and institutions and are what some build great wealth upon. Next week the only retail who remember will be those who panicked.
My opinion only DYOR
FF
AKIDA BALLISTA
Cyw
Regular
Not if Brainchip announces a $50M deal.
alwaysgreen
Top 20
You're going all in and Brainchip are going all out! They've even added an LED light strip. I think they are honestly taking the piss out of those who were complaining about the wrinkled tablecloth.
Last edited:
equanimous
Norse clairvoyant shapeshifter goddess
BRCHF closed .05% down. pretty good to hold up well
Fact Finder
Top 20
It’s great to see that:
1. Mercedes Benz use ultrasound sensors;
2. Valeo makes ultrasound sensors;
3. Brainchip’s AKIDA makes ultrasound sensors smart;
4. Brainchip is trusted by Valeo;
5. Brainchip is trusted by Mercedes Benz.
My opinion only DYOR
FF
AKIDA BALLISTA
Steve10
Regular
Didn't shelter go up 0.7%??
Housing Measure In CPI Jumps By Most In One Month Since 1991 | Entrepreneur
The consumer price index, which was updated Tuesday, showed that inflation is still going strong, with "shelter" price increases standing out.www.entrepreneur.com
These are the rental numbers. Must have two sets of numbers.
Fact Finder
Top 20
I am extremely sad about human behaviour and am definitely not a war monger but putting on my lay economists hat Ukraine has been supplied with US48 billion dollars of armaments so far in its war against Russian invasion.
That is US48 billion dollars of extra demand from military forces around the globe and the US is a global defence powerhouse.
The behaviour of China has seen a pull out of US industries back to the US.
Europe is looking to the US to help meet their energy demands as they turn away willingly or not from Russia.
The economic powerhouse that the US can be is being stoked at the moment and those that can sit tight will be overly rewarded.
My opinion only DYOR
FF
AKIDA BALLISTA
That is US48 billion dollars of extra demand from military forces around the globe and the US is a global defence powerhouse.
The behaviour of China has seen a pull out of US industries back to the US.
Europe is looking to the US to help meet their energy demands as they turn away willingly or not from Russia.
The economic powerhouse that the US can be is being stoked at the moment and those that can sit tight will be overly rewarded.
My opinion only DYOR
FF
AKIDA BALLISTA
True... even if its 2 dollar today I wont he selling... but it would make me feel good hahahaha
Fact Finder
Top 20
Just looking for creases in the table cloth and I have found something strange. Remember last time the secret clue was the toy stag well this time in front of the screen to the right of the photo is a small brown block.
Could this be a clue?
What could the hidden meaning of a block possibly be???
Are there other clues to be found in the chain of lights around the table?
A block and a chain what can it mean???
No opinion just a bit of fun so DYOR
FF
AKIDA BALLISTA
Could this be a clue?
What could the hidden meaning of a block possibly be???
Are there other clues to be found in the chain of lights around the table?
A block and a chain what can it mean???
No opinion just a bit of fun so DYOR
FF
AKIDA BALLISTA
VictorG
Member
This will take deciphering by a surrealist.Just looking for creases in the table cloth and I have found something strange. Remember last time the secret clue was the toy stag well this time in front of the screen to the right of the photo is a small brown block.
Could this be a clue?
What could the hidden meaning of a block possibly be???
Are there other clues to be found in the chain of lights around the table?
A block and a chain what can it mean???
No opinion just a bit of fun so DYOR
FF
AKIDA BALLISTA
For starters a surrealists definition of Brown Block is Fish. That's all I got!!!
Bravo
If ARM was an arm, BRN would be its biceps💪!
Interesting...
Valeo and the French Alternative Energies and Atomic Energy Commission (CEA) signed an agreement to collaborate on the next generations of
Power electronics are key to motor control, energy management and charging speed in electric vehicles. Valeo and the CEA’s teams will work together on advanced research into innovative electronic technologies with the aim of improving electric vehicle efficiency (increasing driving range), optimizing the powertrain and reducing the weight of onboard power electronics.
As a champion of electrification, Valeo will contribute its expertise in power electronics, an area in which it has a leading position.
Xavier Dupont, President of Valeo’s Powertrain Systems Business Group, said: “The world of mobility is undergoing an unprecedented transformation, leading to a significant acceleration in electrification. Valeo is at the heart of this transformation, and this new collaboration with the CEA in the field of power electronics will enable us to further accelerate in electrification, offering the best technologies while at the same time addressing the challenge of carbon neutrality.“
The CEA will contribute its expertise in the fields of microelectronics and materials, as well as in the definition and design of digital twins to optimize the conversion systems being researched.
Sébastien Dauvé, Chief Executive Officer of CEA-Leti, commented, “This agreement demonstrates CEA’s commitment to the key challenges related to vehicle electrification. The partnership aligns perfectly with our mission to support the industry, which focuses on the design of innovative power components all the way through to the development of high-performance conversion systems. We are delighted to support Valeo’s strategy and our teams are highly motivated by the challenge of reducing greenhouse gas emissions.“
This agreement is part of the IPCEI (Important Projects of Common European Interest) dedicated to electronics, which aims to promote innovation in strategic and forward-looking industrial fields (France 2030) through transnational European projects.
Innovation is central to Valeo’s growth strategy. The Group has been ranked as the world’s leading French patent applicant, with 1,777 patents filed in one year (2020), according to the list published by France’s INPI intellectual property institute on June 14, 2022. Last year, 45% of its order intake was for technologies that didn’t exist three years prior. The agreement signed with the CEA further illustrates Valeo’s commitment to innovation.
SOURCE: Valeo
www.automotiveworld.com
Valeo and the CEA to collaborate on advanced research in power electronics to prepare for tomorrow’s electric mobility
September 13, 2022Valeo and the French Alternative Energies and Atomic Energy Commission (CEA) signed an agreement to collaborate on the next generations of
Power electronics are key to motor control, energy management and charging speed in electric vehicles. Valeo and the CEA’s teams will work together on advanced research into innovative electronic technologies with the aim of improving electric vehicle efficiency (increasing driving range), optimizing the powertrain and reducing the weight of onboard power electronics.
As a champion of electrification, Valeo will contribute its expertise in power electronics, an area in which it has a leading position.
Xavier Dupont, President of Valeo’s Powertrain Systems Business Group, said: “The world of mobility is undergoing an unprecedented transformation, leading to a significant acceleration in electrification. Valeo is at the heart of this transformation, and this new collaboration with the CEA in the field of power electronics will enable us to further accelerate in electrification, offering the best technologies while at the same time addressing the challenge of carbon neutrality.“
The CEA will contribute its expertise in the fields of microelectronics and materials, as well as in the definition and design of digital twins to optimize the conversion systems being researched.
Sébastien Dauvé, Chief Executive Officer of CEA-Leti, commented, “This agreement demonstrates CEA’s commitment to the key challenges related to vehicle electrification. The partnership aligns perfectly with our mission to support the industry, which focuses on the design of innovative power components all the way through to the development of high-performance conversion systems. We are delighted to support Valeo’s strategy and our teams are highly motivated by the challenge of reducing greenhouse gas emissions.“
This agreement is part of the IPCEI (Important Projects of Common European Interest) dedicated to electronics, which aims to promote innovation in strategic and forward-looking industrial fields (France 2030) through transnational European projects.
Innovation is central to Valeo’s growth strategy. The Group has been ranked as the world’s leading French patent applicant, with 1,777 patents filed in one year (2020), according to the list published by France’s INPI intellectual property institute on June 14, 2022. Last year, 45% of its order intake was for technologies that didn’t exist three years prior. The agreement signed with the CEA further illustrates Valeo’s commitment to innovation.
SOURCE: Valeo
Valeo and the CEA to collaborate on advanced research in power electronics to prepare for tomorrow’s electric mobility | Automotive World
Valeo and the French Alternative Energies and Atomic Energy Commission (CEA) signed an agreement to collaborate on the next generations of power electronics, which are at the heart of the challenges facing tomorrow’s electric mobility.
www.automotiveworld.com
SiDEvans
Regular
Perhaps the number 15 directly under the chip is trying to tell us they have 15 clients signed up to IP licenses?Just looking for creases in the table cloth and I have found something strange. Remember last time the secret clue was the toy stag well this time in front of the screen to the right of the photo is a small brown block.
Could this be a clue?
What could the hidden meaning of a block possibly be???
Are there other clues to be found in the chain of lights around the table?
A block and a chain what can it mean???
No opinion just a bit of fun so DYOR
FF
AKIDA BALLISTA
Fact Finder
Top 20
Thanks @Bravo I just love this paragraph:
“Innovation is central to Valeo’s growth strategy. The Group has been ranked as the world’s leading French patent applicant, with 1,777 patents filed in one year (2020), according to the list published by France’s INPI intellectual property institute on June 14, 2022. Last year, 45% of its order intake was for technologies that didn’t exist three years prior. The agreement signed with the CEA further illustrates Valeo’s commitment to innovation”
Wow 45% of Valeo’s order book was for technologies that did not exist three years ago.
I think it was Ken Scarince who said AKIDA was disrupting industries that do not exist and he said this in 2021???
The timing was probably a complete coincidence.
My opinion only DYOR
FF
AKIDA BALLISTA
“Innovation is central to Valeo’s growth strategy. The Group has been ranked as the world’s leading French patent applicant, with 1,777 patents filed in one year (2020), according to the list published by France’s INPI intellectual property institute on June 14, 2022. Last year, 45% of its order intake was for technologies that didn’t exist three years prior. The agreement signed with the CEA further illustrates Valeo’s commitment to innovation”
Wow 45% of Valeo’s order book was for technologies that did not exist three years ago.
I think it was Ken Scarince who said AKIDA was disrupting industries that do not exist and he said this in 2021???
The timing was probably a complete coincidence.
My opinion only DYOR
FF
AKIDA BALLISTA
15 clients, 15 mil IP fee for each and announcement on 15th of September 2022Perhaps the number 15 directly under the chip is trying to tell us they have 15 clients signed up to IP licenses?
View attachment 16547
Lex555
Regular
So true, and the opposite on a down day.
With our flucturing share price I’ve been thinking a lot about market sentiment which can easily be viewed on TSE and I include myself, with euphoria and a shared camaraderie when BRN goes from $1.00 to $1.20, and then deep reflection and increased individualism when it bottoms again below $0.90.
Then if SP stays low long enough a surging share price is again followed with the same euphoria when it jumps back to $1.20. But nothing has changed, no money has changed hands no house was repossessed, it’s all psychological.
I’ve mentioned it before but I often try to think of how I’d feel at certain substantially higher price levels, in a way to steadfast myself and improve my long term psychological investing ability, mainly from the fear I sell out early for the quick hit. Much like effective mental imagery used in sports to more so react than feel when the situation comes.
An old interview, but good snapshot summary of CNN vs SNN (GPU v Akida) and fintech applications…
Anna Reitman
FacebookTwitterLinkedInEmail
The application of artificial intelligence across industries depends on hardware acceleration, and some of the ways that’s being done was detailed at a recent Nvidia conference for GPU (graphics processing unit) developers, held in Tel Aviv.
But the advance of neural networks is itself branching out, from the computationally intensive convoluted neural networks (CNNs) to the emerging spiking neural networks (SNNs), also known as neuromorphic computing.
Nvidia’s chief scientist, Bill Dally, was dismissive of the challenge presented by SNNs, saying that because the design is inspired by biological systems, computation is analog, and therefore inefficient. He compared it to “making airplanes that flap wings.”
Robert Beachler, SVP, BrainChip
ASX-listed firm BrainChip recently announced that it’s going to market with the Akida Neuromorphic System-on-Chip (NSoC) for embedded vision, cybersecurity, and fintech, targeting a $10 price point for the chip.
We asked Robert Beachler, SVP of marketing and business development to explain how SNNs are developing for fintech applications.
Fintech Capital Markets: How would you respond to Bill Dally’s description of SNNs?
Robert Beachler: His thesis is that SNNs need to use analog computational elements to be efficient. This is an incorrect statement. BrainChip’s neuron model is purely digital, and BrainChip accelerates spiking neural networks in a digital manner.
On representing numbers as spikes: This is a common misperception that spokespeople working with CNNs have of SNNs. In CNNs they use numbers to represent data and therefore think that SNNs need to use numbers as well – which is incorrect.
Neurons don’t think in mathematical and floating point values, which is why humans invented calculators and computers – we recognized that the human mind is not good at complex math.
BrainChip’s data-to-spike converters take the external information (whether it is pixels, audio, fintech data, etc.) and translates it to a series of spikes. This translation does not encode the values of numbers.
Rather, the spike series represent pertinent information such as frequency, magnitude change, or other characteristics. This is what sensory organs do, like the retina, cochlea, etc.; they don’t send numbers – they send spike series that represent the pertinent information.
Source: BrainChip
The reason CNNs take so much power and silicon real estate is that they try to emulate what neurons perform using complex math functions – taking hundreds of watts. SNNs, by contrast, are more efficient as they more closely emulate the most efficient thinking machine – the human mind, which only uses 20 watts.
And regarding planes that flap and have feathers: This is a rather elementary attack that shows a lack of understanding of how state-of-the-art SNNs operate. If you tried to exactly model the complex bio-electrical process of the human neuron, like electron potentials, ion channels, dopamine reactions, etc., you would indeed have a very complex and inefficient neuron model.
But if you emulate only the most important neuron characteristics, synaptic connections and firing thresholds, in a purely digital manner, you end up with a very efficient neuron model, which BrainChip has been researching for many years. That is why the BrainChip neuromorphic system-on-chip is an order of magnitude more efficient on an images / second / watt basis compared to GPUs and FPGAs (field-programmable gate arrays).
FTCM: Can you describe the difference between CNNs and SNNs?
RB: Traditional computer architecture is really set up for sequential execution, whereas an artificial neural network is a distributed parallel feed-forward architecture that doesn’t lend itself to sequential execution; it really wants to be distributed, it wants to be a lot of compute in parallel. And the primary difference between a CNN and an SNN is what is being done in the neuron itself.
With CNNs, it’s essentially a filtering operation. At its base, it is matrix multiplication, so all of the CNN acceleration chips are really just looking at ways to do more multiply accumulates with lower amounts of silicon and lower amounts of power consumption.
For SNNs, instead of using this math function, the actual neuron that we use is modeled after biology where you have synapses and neurons, and the data between the synapses are spikes in the brain. The way that it learns is that you reinforce or inhibit these synaptic connections and then you also can change the firing threshold of the neuron itself. The chip learns through reinforcement and inhibition of synaptic connections and the thresholds.
Source: BrainChip
FTCM: Can you give me an example that makes sense for finance?
RB: In the case of financial technology, there’s a lot of unlabeled data. What these neural networks will do is cluster things that are similar together, and that could be successful trading patterns, economic indicators, it could be basically just about any type of data that financial traders or economists want to look at.
There’s an entire science of converting data into spikes. We have embedded in our chips certain data-to-spike conversions for specific applications, but for fintech it’s more of a general data-to-spike conversion, that takes generic data and puts it into a time series of spikes. Inside, on a neuron fabric, a spiking neural network model is doing pattern recognition in an unsupervised mode using unlabeled data.
FTCM: One of the first things I think of is the “black box” problem. Can you see how decisions get made?
RB: That’s really a conversation that hasn’t been solved, because it’s really hard to understand; you have these deep neural networks, multiple layers, looking inside of them to see what it’s doing. It’s very hard to visualize and it’s not something that you really can do very well.
It’s really a self-organizing, self-training type of system, and you’re right, it’s very difficult to explain the pattern.
FTCM: This is commercially available now, right? Can you tell us about your financial services clients?
RB: We have the development environment that’s available now for our customers to start creating the SNNs; we anticipate sampling the silicon mid-2019. We are focusing on three areas: vision systems, cybersecurity and fintech.
The financial sector is a rarefied environment; it’s not going to be thousands of customers, whereas there can be thousands of drones and vision-guided robotic systems. Our fintech and cybersecurity will be a smaller percentage in terms of number of customers, but it might be higher in terms of the potential revenue size for us because they would be buying lots of chips in big groups for servers. I can’t say anything more specific at the moment.
In the fintech community, there’s not a lot of public domain information about what are the neural networks that these companies are using. They are in the business of making money and they are really protecting that intellectual property.
FTCM: And what does it actually look like to set up?
RB: In most fintech applications, it would be a PCI Express card that may have between 20 and 50 of these chips in order to be able to execute very large neural networks very quickly.
We measure things in terms of neurons, and the neuron fabric has 1.2 million neurons and 10 billion synapses. It has a lot of compute capability. When we talk about replacing math-intensive convolutions of backpropagation methods, we are talking about replacing those matrices with the neurons and the synapses.
Each neuron-processing core can do a certain number of neurons and synapses. We made their functionality to accelerate this computation but also to be able to emulate a lot of the convolutional neural network styles.
Source: BrainChip
FTCM: How do you see the future unfolding for the different kinds of hardware acceleration architecture?
RB: You’re seeing a melding of the different technologies on any given chip. If you were to look into the future, you could have an ARM processor (architecture for systems-on-chips) and an embedded FPGA for data manipulation and scaling, then you have a neuron fabric which is either accelerating SNNs and CNNs, and that all comes together in a monolithic piece of silicon.
AI tech: are your neural networks convoluted? Try spikes.
October 26, 2018Anna Reitman
FacebookTwitterLinkedInEmail
The application of artificial intelligence across industries depends on hardware acceleration, and some of the ways that’s being done was detailed at a recent Nvidia conference for GPU (graphics processing unit) developers, held in Tel Aviv.
But the advance of neural networks is itself branching out, from the computationally intensive convoluted neural networks (CNNs) to the emerging spiking neural networks (SNNs), also known as neuromorphic computing.
Nvidia’s chief scientist, Bill Dally, was dismissive of the challenge presented by SNNs, saying that because the design is inspired by biological systems, computation is analog, and therefore inefficient. He compared it to “making airplanes that flap wings.”
Robert Beachler, SVP, BrainChip
ASX-listed firm BrainChip recently announced that it’s going to market with the Akida Neuromorphic System-on-Chip (NSoC) for embedded vision, cybersecurity, and fintech, targeting a $10 price point for the chip.
We asked Robert Beachler, SVP of marketing and business development to explain how SNNs are developing for fintech applications.
Fintech Capital Markets: How would you respond to Bill Dally’s description of SNNs?
Robert Beachler: His thesis is that SNNs need to use analog computational elements to be efficient. This is an incorrect statement. BrainChip’s neuron model is purely digital, and BrainChip accelerates spiking neural networks in a digital manner.
On representing numbers as spikes: This is a common misperception that spokespeople working with CNNs have of SNNs. In CNNs they use numbers to represent data and therefore think that SNNs need to use numbers as well – which is incorrect.
Neurons don’t think in mathematical and floating point values, which is why humans invented calculators and computers – we recognized that the human mind is not good at complex math.
BrainChip’s data-to-spike converters take the external information (whether it is pixels, audio, fintech data, etc.) and translates it to a series of spikes. This translation does not encode the values of numbers.
Rather, the spike series represent pertinent information such as frequency, magnitude change, or other characteristics. This is what sensory organs do, like the retina, cochlea, etc.; they don’t send numbers – they send spike series that represent the pertinent information.
Source: BrainChip
The reason CNNs take so much power and silicon real estate is that they try to emulate what neurons perform using complex math functions – taking hundreds of watts. SNNs, by contrast, are more efficient as they more closely emulate the most efficient thinking machine – the human mind, which only uses 20 watts.
And regarding planes that flap and have feathers: This is a rather elementary attack that shows a lack of understanding of how state-of-the-art SNNs operate. If you tried to exactly model the complex bio-electrical process of the human neuron, like electron potentials, ion channels, dopamine reactions, etc., you would indeed have a very complex and inefficient neuron model.
But if you emulate only the most important neuron characteristics, synaptic connections and firing thresholds, in a purely digital manner, you end up with a very efficient neuron model, which BrainChip has been researching for many years. That is why the BrainChip neuromorphic system-on-chip is an order of magnitude more efficient on an images / second / watt basis compared to GPUs and FPGAs (field-programmable gate arrays).
FTCM: Can you describe the difference between CNNs and SNNs?
RB: Traditional computer architecture is really set up for sequential execution, whereas an artificial neural network is a distributed parallel feed-forward architecture that doesn’t lend itself to sequential execution; it really wants to be distributed, it wants to be a lot of compute in parallel. And the primary difference between a CNN and an SNN is what is being done in the neuron itself.
With CNNs, it’s essentially a filtering operation. At its base, it is matrix multiplication, so all of the CNN acceleration chips are really just looking at ways to do more multiply accumulates with lower amounts of silicon and lower amounts of power consumption.
For SNNs, instead of using this math function, the actual neuron that we use is modeled after biology where you have synapses and neurons, and the data between the synapses are spikes in the brain. The way that it learns is that you reinforce or inhibit these synaptic connections and then you also can change the firing threshold of the neuron itself. The chip learns through reinforcement and inhibition of synaptic connections and the thresholds.
Source: BrainChip
FTCM: Can you give me an example that makes sense for finance?
RB: In the case of financial technology, there’s a lot of unlabeled data. What these neural networks will do is cluster things that are similar together, and that could be successful trading patterns, economic indicators, it could be basically just about any type of data that financial traders or economists want to look at.
There’s an entire science of converting data into spikes. We have embedded in our chips certain data-to-spike conversions for specific applications, but for fintech it’s more of a general data-to-spike conversion, that takes generic data and puts it into a time series of spikes. Inside, on a neuron fabric, a spiking neural network model is doing pattern recognition in an unsupervised mode using unlabeled data.
FTCM: One of the first things I think of is the “black box” problem. Can you see how decisions get made?
RB: That’s really a conversation that hasn’t been solved, because it’s really hard to understand; you have these deep neural networks, multiple layers, looking inside of them to see what it’s doing. It’s very hard to visualize and it’s not something that you really can do very well.
It’s really a self-organizing, self-training type of system, and you’re right, it’s very difficult to explain the pattern.
FTCM: This is commercially available now, right? Can you tell us about your financial services clients?
RB: We have the development environment that’s available now for our customers to start creating the SNNs; we anticipate sampling the silicon mid-2019. We are focusing on three areas: vision systems, cybersecurity and fintech.
The financial sector is a rarefied environment; it’s not going to be thousands of customers, whereas there can be thousands of drones and vision-guided robotic systems. Our fintech and cybersecurity will be a smaller percentage in terms of number of customers, but it might be higher in terms of the potential revenue size for us because they would be buying lots of chips in big groups for servers. I can’t say anything more specific at the moment.
In the fintech community, there’s not a lot of public domain information about what are the neural networks that these companies are using. They are in the business of making money and they are really protecting that intellectual property.
FTCM: And what does it actually look like to set up?
RB: In most fintech applications, it would be a PCI Express card that may have between 20 and 50 of these chips in order to be able to execute very large neural networks very quickly.
We measure things in terms of neurons, and the neuron fabric has 1.2 million neurons and 10 billion synapses. It has a lot of compute capability. When we talk about replacing math-intensive convolutions of backpropagation methods, we are talking about replacing those matrices with the neurons and the synapses.
Each neuron-processing core can do a certain number of neurons and synapses. We made their functionality to accelerate this computation but also to be able to emulate a lot of the convolutional neural network styles.
Source: BrainChip
FTCM: How do you see the future unfolding for the different kinds of hardware acceleration architecture?
RB: You’re seeing a melding of the different technologies on any given chip. If you were to look into the future, you could have an ARM processor (architecture for systems-on-chips) and an embedded FPGA for data manipulation and scaling, then you have a neuron fabric which is either accelerating SNNs and CNNs, and that all comes together in a monolithic piece of silicon.
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