BRN Discussion Ongoing

[stuart888]

Interesting, pick your number:

https://lendedu.com/blog/how-much-money-do-you-need-to-live-off-interest/

 

[stuart888]

How much would the normal person buy of Brainchip stock with a 1-million-dollar networth?

Assumption: $500,000 paid-off-home and $500,000-in-stocks. No debt.

Question Hint: If they had $25,000 worth of stock, would that be a lot?

This is in response to some of our lucky 100,000+ stock holders (ya'll BRN fatcats!).

Answer: $25k, I would say yes and very lucky would be $25,000 (5%) out of $500,000. Some would say that is large position in one stock. To me that is well diversified, but a nice healthy chunk. New money can be added in over time too.

 

[equanimous]

How much would the normal person buy of Brainchip stock with a 1-million-dollar networth?

Assumption: $500,000 paid-off-home and $500,000-in-stocks. No debt.

Question Hint: If they had $25,000 worth of stock, would that be a lot?

This is in response to some of our lucky 100,000+ stock holders (ya'll BRN fatcats!).

Answer: $25k, I would say yes and very lucky would be $25,000 (5%) out of $500,000. Some would say that is large position in one stock. To me that is well diversified, but a nice healthy chunk. New money can be added in over time too.

 

[stuart888]

1000 fps really gets me thinking wow. I would love to get deeper into this topic over time. Data arrays into SNN is very interesting, and Brainchip is winning, double wow!

Seems like anywhere you can move decisions to the edge involving video, big cost savings.
Video is a resource hog, Brainchip Akida SNN is not!

 

[Bravo]

Interesting...

Valeo and the CEA to collaborate on advanced research in power electronics to prepare for tomorrow’s electric mobility​

September 13, 2022

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

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

Hi All,

I just realised something about CEA-Leti in addition to the partnership announcement (as above) in Sept 2022 which states "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."

Well, recently, in December 2022 CEA-Leti recently did a tutorial presentation highlighting "promising advantages that resistive random-access memory (RRAM) technologies hold for implementing novel neuromorphic/in-memory computing systems for massively parallel, low-power and low-latency computation."

I'd find it difficult to believe that Valeo and CEA-Leti would be working together without there being conversations about BrainChip's AKIDA. Pure speculation on my behalf, but I'll let you be the judge.

CEA-Leti Presents RRAM’s ‘Promising Advantages’ For Neuromorphic/In-Memory Computing at IEDM 2022​

CEA-Leti
A CEA-Leti tutorial presented at IEDM 2022 highlighted promising advantages that resistive random-access memory (RRAM) technologies hold for implementing novel neuromorphic/in-memory computing systems for massively parallel, low-power and low-latency computation.
Published on 7 December 2022

In a presentation titled "Resistive Memories-Based Concepts for Neuromorphic Computing", Elisa Vianello, CEA-Leti's edge AI program manager, said RRAMs, aka memristors, offer advantages in energy efficiency and computing power when processing AI workloads. She noted, however, scientists must overcome device issues, especially variability, quantization error and limited endurance to achieve commercialization of this approach.
During the conference, CEA-Leti also reported development of the first end-to-end, gesture-recognition solution for ultralow power implementation on silicon with an estimated always-on total power consumption of 0.41 μJ/frame. This breakthrough, presented in the paper "Spike-based Beamforming Using pMUT Arrays for Ultra-Low Power Gesture Recognition", used low-power piezoelectric micromachined ultrasonic transducers (pMUTs) to emit and sense ultrasonic signals. This novel spike-based beamforming extracts spatial temporal information and a spiking recurrent neural network (SRNN) to perform simple gesture detection and classification.
Neuromorphic In-Memory Computing
In recent years, "neuromorphic" has been used to describe mixed-signal and pure digital systems that can be used to simulate spiking neural networks. As interest in the potential for this technology grew, the neuromorphic researchers were joined by material and device-physics researchers to study memristor properties and leverage their physics to implement neural and synaptic functions.
Meanwhile, artificial intelligence (AI) algorithms were being applied in healthcare, robotics, agriculture and other sectors, but those applications face power constraints. To address some of these challenges, CEA-Leti's AI research focuses on the development of novel brain-inspired technologies and processing methods. This requires researchers in multiple disciplines to combine their efforts and simultaneously co-develop technologies, circuits, processing methods and the supporting computing architectures, Vianello said.

"Spike-based Beamforming Using pMUT Arrays for Ultra-Low Power Gesture Recognition"
Explaining CEA-Leti's breakthrough end-to-end, ultralow power gesture-recognition solution, Emmanuel Hardy, lead author on the paper, said previously published systems in the literature were implemented with off-the-shelf sensors and readout electronics, so gesture recognition is always performed offline in software with full precision for the inference.
Traditional beamforming directly combines the sine waves in analog or digital format after applying delays. CEA-Leti's spike-based technique simplifies the process by encoding the phase of a signal by a single spike per signal period. It then allows scientists to apply simple logic on spikes to implement beamforming. A spiking recurrent neural network (SRNN) takes the spike density as an input to perform gesture detection.
CEA-Leti's end-to-end, gesture-recognition solution is suitable for ultralow power implementation on silicon with an estimated total power consumption of 0.41 μJ/frame. The breakthrough uses low-power sensors with pMUTs and extracts and processes the minimum information with CEA-Leti's novel spike-based beamforming. It also includes classification in the spike domain with a SRNN. The institute also is working to develop an energy-efficient RRAM-based SRNN.
"Our system supports a fully integrated approach enabling ultralow-power, end-to-end operation," Hardy said. "Its primary advantage is its low manufacturing cost and easy integration, which suits its use in wearable and automotive applications. The system could be also used for acoustic ranging with interesting applications in robotics and drones."

CEA-Leti Presents RRAM’s ‘Promising Advantages’ For Neuromorphic/In-Memory Computing at IEDM 2022

A CEA-Leti tutorial presented at IEDM 2022 highlighted promising advantages that resistive random-access memory (RRAM) technologies hold for implementing novel neuromorphic/in-memory computing systems for massively parallel, low-power and low-latency computation.

www.leti-cea.com

 

[Diogenese]

Hi All,

I just realised something about CEA-Leti in addition to the partnership announcement (as above) in Sept 2022 which states "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."

Well, recently, in December 2022 CEA-Leti recently did a tutorial presentation highlighting "promising advantages that resistive random-access memory (RRAM) technologies hold for implementing novel neuromorphic/in-memory computing systems for massively parallel, low-power and low-latency computation."

I'd find it difficult to believe that Valeo and CEA-Leti would be working together without there being conversations about BrainChip's AKIDA. Pure speculation on my behalf, but I'll let you be the judge.

CEA-Leti Presents RRAM’s ‘Promising Advantages’ For Neuromorphic/In-Memory Computing at IEDM 2022​

CEA-Leti
A CEA-Leti tutorial presented at IEDM 2022 highlighted promising advantages that resistive random-access memory (RRAM) technologies hold for implementing novel neuromorphic/in-memory computing systems for massively parallel, low-power and low-latency computation.
Published on 7 December 2022

In a presentation titled "Resistive Memories-Based Concepts for Neuromorphic Computing", Elisa Vianello, CEA-Leti's edge AI program manager, said RRAMs, aka memristors, offer advantages in energy efficiency and computing power when processing AI workloads. She noted, however, scientists must overcome device issues, especially variability, quantization error and limited endurance to achieve commercialization of this approach.
During the conference, CEA-Leti also reported development of the first end-to-end, gesture-recognition solution for ultralow power implementation on silicon with an estimated always-on total power consumption of 0.41 μJ/frame. This breakthrough, presented in the paper "Spike-based Beamforming Using pMUT Arrays for Ultra-Low Power Gesture Recognition", used low-power piezoelectric micromachined ultrasonic transducers (pMUTs) to emit and sense ultrasonic signals. This novel spike-based beamforming extracts spatial temporal information and a spiking recurrent neural network (SRNN) to perform simple gesture detection and classification.
Neuromorphic In-Memory Computing
In recent years, "neuromorphic" has been used to describe mixed-signal and pure digital systems that can be used to simulate spiking neural networks. As interest in the potential for this technology grew, the neuromorphic researchers were joined by material and device-physics researchers to study memristor properties and leverage their physics to implement neural and synaptic functions.
Meanwhile, artificial intelligence (AI) algorithms were being applied in healthcare, robotics, agriculture and other sectors, but those applications face power constraints. To address some of these challenges, CEA-Leti's AI research focuses on the development of novel brain-inspired technologies and processing methods. This requires researchers in multiple disciplines to combine their efforts and simultaneously co-develop technologies, circuits, processing methods and the supporting computing architectures, Vianello said.

"Spike-based Beamforming Using pMUT Arrays for Ultra-Low Power Gesture Recognition"
Explaining CEA-Leti's breakthrough end-to-end, ultralow power gesture-recognition solution, Emmanuel Hardy, lead author on the paper, said previously published systems in the literature were implemented with off-the-shelf sensors and readout electronics, so gesture recognition is always performed offline in software with full precision for the inference.
Traditional beamforming directly combines the sine waves in analog or digital format after applying delays. CEA-Leti's spike-based technique simplifies the process by encoding the phase of a signal by a single spike per signal period. It then allows scientists to apply simple logic on spikes to implement beamforming. A spiking recurrent neural network (SRNN) takes the spike density as an input to perform gesture detection.
CEA-Leti's end-to-end, gesture-recognition solution is suitable for ultralow power implementation on silicon with an estimated total power consumption of 0.41 μJ/frame. The breakthrough uses low-power sensors with pMUTs and extracts and processes the minimum information with CEA-Leti's novel spike-based beamforming. It also includes classification in the spike domain with a SRNN. The institute also is working to develop an energy-efficient RRAM-based SRNN.
"Our system supports a fully integrated approach enabling ultralow-power, end-to-end operation," Hardy said. "Its primary advantage is its low manufacturing cost and easy integration, which suits its use in wearable and automotive applications. The system could be also used for acoustic ranging with interesting applications in robotics and drones."

CEA-Leti Presents RRAM’s ‘Promising Advantages’ For Neuromorphic/In-Memory Computing at IEDM 2022

A CEA-Leti tutorial presented at IEDM 2022 highlighted promising advantages that resistive random-access memory (RRAM) technologies hold for implementing novel neuromorphic/in-memory computing systems for massively parallel, low-power and low-latency computation.

www.leti-cea.com

So, now that we're alone ...

 

[Diogenese]

So, now that we're alone ...

...
CEA-Leti have been dabbling with ReRAM/MemRistors for many years:

Priorities DE10349750A·2003-10-23; EP2004011812W·2004-10-19​

US7876605B2 Phase change memory, phase change memory assembly, phase change memory cell, 2D phase change memory cell array, 3D phase change memory cell array and electronic component

A phase change memory having a memory material layer consisting of a phase change material, and a first and second electrical contact which are located at a distance from one another and via which a switching zone of the memory material layer can be traversed by a current signal, wherein the current signal can be used to induce a reversible phase change between a crystalline phase and an amorphous phase and thus a change in resistance of the phase change material in the switching zone. The invention also relates to a phase change memory assembly, a phase change memory cell, a 2D phase change memory cell array, a 3D phase change memory cell array and an electronic component.

 

[Diogenese]

So, now that we're alone ...

... come up and see my scrip.

 

[Bravo]

How much would the normal person buy of Brainchip stock with a 1-million-dollar networth?

Assumption: $500,000 paid-off-home and $500,000-in-stocks. No debt.

Question Hint: If they had $25,000 worth of stock, would that be a lot?

This is in response to some of our lucky 100,000+ stock holders (ya'll BRN fatcats!).

Answer: $25k, I would say yes and very lucky would be $25,000 (5%) out of $500,000. Some would say that is large position in one stock. To me that is well diversified, but a nice healthy chunk. New money can be added in over time too.

Answer: As much as we can get our hands (and feet) on

 

[Diogenese]

Answer: As much as we can get our hands (and feet) on.

View attachment 27286

Don't show everybody my smorgasbord technique ...

 

[Bravo]

...
CEA-Leti have been dabbling with ReRAM/MemRistors for many years:

Priorities DE10349750A·2003-10-23; EP2004011812W·2004-10-19​

US7876605B2 Phase change memory, phase change memory assembly, phase change memory cell, 2D phase change memory cell array, 3D phase change memory cell array and electronic component

View attachment 27281




A phase change memory having a memory material layer consisting of a phase change material, and a first and second electrical contact which are located at a distance from one another and via which a switching zone of the memory material layer can be traversed by a current signal, wherein the current signal can be used to induce a reversible phase change between a crystalline phase and an amorphous phase and thus a change in resistance of the phase change material in the switching zone. The invention also relates to a phase change memory assembly, a phase change memory cell, a 2D phase change memory cell array, a 3D phase change memory cell array and an electronic component.

Well, seeing I'm as good at engineering as I was at math - the only thing I took out of that was that they need some sort of electronic component. Is that worth a least a quarter of a star?

 

[Diogenese]

Well, seeing I'm as good at engineering as I was at math - the only thing I took out of that was that they need some sort of electronic component. Is that worth a least a quarter of a star?




View attachment 27287

Hi Bravo,

Well, they've been footling around with MemRistors for 20 years and:-

"In a presentation titled "Resistive Memories-Based Concepts for Neuromorphic Computing", Elisa Vianello, CEA-Leti's edge AI program manager, said RRAMs, aka memristors, offer advantages in energy efficiency and computing power when processing AI workloads. She noted, however, scientists must overcome device issues, especially variability, quantization error and limited endurance to achieve commercialization of this approach."

Many AI researchers have been beguiled by the close similarity between synapses and ReRAM in that ReRAM theoretically can be arranged to directly add the strengths of incoming signals (analog), whereas digital synapses such as Akida counts binary bits to arrive at the sum (digital). But, as Elias points out, there are practical difficulties in making the ReRAM devices sufficiently precise to produce consistent results, remembering that we are talking about millions of ReRAM devices so cumulative errors can be significant.

So, in theory, ReRAM has advantages over digital, but, in practice, digital works.

Like Renesas, they have sunk costs in their in-house tech.

 

[The Pope]

As you can see most holders here can't influence the SP so don't sweat the small stuff. we are all on the bus to wherever the big holders wanna take us. I am in the company of 1471 other holders, thats not many really. View attachment 27272

This is my understanding.
If you have BRN shares in both commsec or similar plus say via Australian super account (invest up to 20%) then you are counted as two individuals.
So people like me are counted as 2 of the 46000 approx shareholders. How many of the 1000 eyes or other BRN investors may be like me.

 

[Fullmoonfever]

Posted in the TA thread also.

Just watching the longer potential falling wedge in play.

Would need a break above ~ 0.90 with continuing support to drive a trend change and projected eventual 1.80 odd target.

 

[misslou]

This is my understanding.
If you have BRN shares in both commsec or similar plus say via Australian super account (invest up to 20%) then you are counted as two individuals.
So people like me are counted as 2 of the 46000 approx shareholders. How many of the 1000 eyes or other BRN investors may be like me.

I am counted as 3 shareholders for my total holding

 

[HopalongPetrovski]

I identify as a BRN holder but given that I also hold in my Super does that mean I'm Bi???
Asking for a friend.

 

[Esq.111]

Well i have pressed the BUY button with both left & right hands ....

Class myself as ambidextrous.

Esq.

 

[robsmark]

I am, I hold a shares which put me in the largest holder category both personally and in my SMSF - I’ve mentioned this before, the numbers are inaccurate (through no fault of the company).

This is my understanding.
If you have BRN shares in both commsec or similar plus say via Australian super account (invest up to 20%) then you are counted as two individuals.
So people like me are counted as 2 of the 46000 approx shareholders. How many of the 1000 eyes or other BRN investors may be like me

 

[thelittleshort]

TARGET APPLICATIONS​

AUTOMOTIVE​

MEDICAL​

RETAIL​

INDUSTRY​

SECURITY AND SURVEILLANCE​

 

[alwaysgreen]

I hold some personally and some via my company/trust. None in super because I don't plan that far ahead!