BRN Discussion Ongoing

[jtardif999]

My favourite part of the podcast was the super hero answer Drew came up with.. He chose Vince Lombardi and some Kiwi Rugby coach whose name I’ve already forgotten - the theme being that they did so much with so little, had lasting success and left a legacy that has never been forgotten and the Kiwi case has translated into success in all fields of sport for an island nation with a population the size of Sydney. If I’m not imagining things I reckon instead he is actually referring to PVMD - achieving so much with so little.

 

[Dhm]

I like this bit of info off the Mercedes Benz USA website. Read what you want into the meanings behind his statements! I know I have.
-----------------------------------------------------------------------------
MERCEDES BENZ - USA Website
Neuromorphic computing – a car that thinks like you

Another key efficiency feature of the VISION EQXX that takes its cue from nature is the way it thinks. It uses an innovative form of information processing called neuromorphic computing. The hardware runs spiking neural networks. Information is coded in discrete spikes and energy is only consumed when a spike occurs, which reduces energy consumption by orders of magnitude. Working with California-based artificial intelligence experts BrainChip, Mercedes-Benz engineers developed systems based on BrainChip's Akida hardware and software. The example in the VISION EQXX is the "Hey Mercedes" key-word detection. Structured along neuromorphic principles, it is five to ten times more efficient than conventional voice control.

Although neuromorphic computing is still in its infancy, systems like these will be available on the market in just a few years. When applied on scale throughout a vehicle, they have the potential to radically reduce the energy needed to run the latest AI technologies.
--------------------------------------
What more info do you need to convince you?
If Benz are going to use Akida then so will other Brands within the Company Group.


Yak52

I can't find the specific page this comes from, can you supply a link? I did search the mbusa.com website and searched for Brainchip but no results. Cheers.

 

[Dhm]

I like our chances of being involved here, .................developed by the University?

Rewired: An AI That Can Learn Like A Human Brain

A brain-inspired computer chip that is capable of rewiring itself as it learns,could transform the development of human-level Artificial Intelligence.

www.cybersecurityintelligence.com

One reason for the human brain’s incredible power is its ability to rewire itself as it learns. Now, researchers at Purdue University have created electronic circuits that can do the same. The Purdue research team has created a brain-inspired computer chip that could transform the development of human-level AI.

They have demonstrated new circuit components whose functions can be reconfigured with electronic pulses in the form of an innovative circuit capable of rewiring itself as it learns.

This allows them to seamlessly switch between acting as resistors, memory capacitors, artificial neurons, and artificial synapses. The breakthrough opens the door to creating dynamic neural networks in hardware that can rewire themselves as they learn, just like the human brain.

The chip contains “reconfigurable neuromorphic functions”, allowing it to be reprogrammed at room temperature by simple electrical pulses. These pulses generate the different functions of neurons, synapses and memory capacitors, which are crucial for achieving adaptive learning that humans excel at. “The brains of living beings can continuously learn throughout their lifespan. We have now created an artificial platform for machines to learn throughout their lifespan,” said Shriram Ramanathan, a professor in Purdue University’s School of Materials Engineering. “If we want to build a computer or a machine that is inspired by the brain, then correspondingly, we want to have the ability to continuously program, reprogram and change the chip.” he said.

A study describing the breakthrough, published in the journal Science, details how the chip is able to optimise its underlying hardware in order to meet new challenges as they arise.

The researchers tested the chip’s performance on individual devices, before using the data to simulate a large network of them. Through this method, known as reservoir computing, they were able to outperform other theoretical and experimental models at certain learning tasks.

The network was also able to function as a “Grow When Required” (GWR) neural network, which allows it to grow and shrink depending on the size of the task. This optimises the chip’s efficiency in a way that conventional chips are unable to, and allows it to “pick and choose” which circuits are the best fit for addressing problems.

The design of the new chip could also help make artificial intelligence more portable, such as for autonomous vehicles or robots, as the AI could be embedded directly into hardware rather than just running on software. The researchers are now working to demonstrate the chips on a larger scale, with the eventual goal of building a brain-inspired computer.

Aren't we massively ahead of the Perdue University's research already? They are talking about 'could also help' and 'now working to demonstrate the chips on a larger scale'. We have already achieved that and are selling our chips and IP. 100++ NDA's already.

 

[IloveLamp]

Aren't we massively ahead of the Perdue University's research already? They are talking about 'could also help' and 'now working to demonstrate the chips on a larger scale'. We have already achieved that and are selling our chips and IP. 100++ NDA's already.

That's true and I'm not 100% convinced by any means, I just like our chances (as in it sounds very AKIDA ish). I always take the narrative in these articles with a grain of salt as the accuracy and facts can be skewed by accident (due to incompetence) or on purpose (to mislead for whatever reason)

But I get what you're putting down

 

[David holland]

I just cannot get over how excited and happy he is about one bush, could he have had two birds in it before the photo was taken?
FF.

I respect your opinion Fact Finder,
Just under 9 months of the year to go, by years end what are you hoping personally the company achieves

 

[Pmel]

I can't find the specific page this comes from, can you supply a link? I did search the mbusa.com website and searched for Brainchip but no results. Cheers.

VISION EQXX – taking electric range and efficiency to an entirely new level

Range and efficiency are set to define the electric era. Exceptional range will make electric cars suitable for every journey and help to increase overall adoption.

media.mbusa.com

Search here.

 

[Justchilln]

Aren't we massively ahead of the Perdue University's research already? They are talking about 'could also help' and 'now working to demonstrate the chips on a larger scale'. We have already achieved that and are selling our chips and IP. 100++ NDA's already.

We are massively ahead of everyone else working on neuromorphic hardware.

 

[Buts97]

Could there be something here? Clearly lots of experience in adas and automotive world.

 

[Diogenese]

I like our chances of being involved here, .................developed by the University?

Rewired: An AI That Can Learn Like A Human Brain

A brain-inspired computer chip that is capable of rewiring itself as it learns,could transform the development of human-level Artificial Intelligence.

www.cybersecurityintelligence.com

One reason for the human brain’s incredible power is its ability to rewire itself as it learns. Now, researchers at Purdue University have created electronic circuits that can do the same. The Purdue research team has created a brain-inspired computer chip that could transform the development of human-level AI.

They have demonstrated new circuit components whose functions can be reconfigured with electronic pulses in the form of an innovative circuit capable of rewiring itself as it learns.

This allows them to seamlessly switch between acting as resistors, memory capacitors, artificial neurons, and artificial synapses. The breakthrough opens the door to creating dynamic neural networks in hardware that can rewire themselves as they learn, just like the human brain.

The chip contains “reconfigurable neuromorphic functions”, allowing it to be reprogrammed at room temperature by simple electrical pulses. These pulses generate the different functions of neurons, synapses and memory capacitors, which are crucial for achieving adaptive learning that humans excel at. “The brains of living beings can continuously learn throughout their lifespan. We have now created an artificial platform for machines to learn throughout their lifespan,” said Shriram Ramanathan, a professor in Purdue University’s School of Materials Engineering. “If we want to build a computer or a machine that is inspired by the brain, then correspondingly, we want to have the ability to continuously program, reprogram and change the chip.” he said.

A study describing the breakthrough, published in the journal Science, details how the chip is able to optimise its underlying hardware in order to meet new challenges as they arise.

The researchers tested the chip’s performance on individual devices, before using the data to simulate a large network of them. Through this method, known as reservoir computing, they were able to outperform other theoretical and experimental models at certain learning tasks.

The network was also able to function as a “Grow When Required” (GWR) neural network, which allows it to grow and shrink depending on the size of the task. This optimises the chip’s efficiency in a way that conventional chips are unable to, and allows it to “pick and choose” which circuits are the best fit for addressing problems.

The design of the new chip could also help make artificial intelligence more portable, such as for autonomous vehicles or robots, as the AI could be embedded directly into hardware rather than just running on software. The researchers are now working to demonstrate the chips on a larger scale, with the eventual goal of building a brain-inspired computer.

Hi ILL,

This is pretty much blue sky research and won't be out of the lab any time soon.

https://spectrum.ieee.org/neuromorphic-computing-ai-device

The scientists note that they fabricated their devices using semiconductor-foundry-compatible techniques, suggesting they might readily find use within the electronics industry. However, "the status of our research is in its infancy," Zhang says. "Much more work is required to fabricate large-scale integrated test circuitry with these devices."

It is also talking about analog NNs using memristors.

An adaptable new device can transform into all the key electric components needed for artificial-intelligence hardware, for potential use in robotics and autonomous systems, a new study finds.

It has an extraordinarily short shelf life - 1.6 million switching operations at 300 MHz is about 2 milliseconds, and the hydrogen ion in the perovskite only hangs about for 6 months. Hydrogen is notoriously itinerant and can penetrate many molecular lattices. Optical fibres often have a nitride cladding to prevent hydrogen penetration, as hydrogen has an absorption band in the desired laser wavelength.

The new device proved stable over 1.6 million cycles of switching between states. "Also, hydrogen ions remain in the device for a long period of time after its initial treatment—over six months—which is encouraging," Park says

Switching the function of millions of devices seems to me to be an enormously complicated exercise.

The scientists incorporated protons into perovskite nickelate. Electric pulses applied to this material could shuffle the protons [hydrogen ions] around within the material's lattice, altering its electronic properties. The researchers could electrically reconfigure a device made from this proton-doped perovskite nickelate into a resistor, a memory capacitor, a neuron, or a synapse on demand.
...
The versatility of this device "could simplify AI circuit design for complex computational tasks by avoiding an agglomeration of different functional units that are area- and power-consuming," says study colead author Michael Tae Joon Park, an electrical engineer and materials scientist at Purdue. Potential applications include robotics and autonomous systems, he notes.

In simulations using the new device in an artificial neural network, which mimics the structure of neurons in biological brains, the scientists found that the reconfigurable nature of the new device enabled the neural network "to make its decisions more efficiently, compared to conventional static networks, in complex and ever-changing environments," Zhang says.

The researchers suggest their device could find use in grow-when-required networks, which are neural networks that can grow their computing power on demand. Similarly, such networks can shrink in size if the device detects nodes that are regularly inactive in order to become more efficient.

Akida is reconfigurable in that the library of models changes the weights of the neurons. I am not familiar with "grow-when-required networks", but Akida would seem to incorporate this capability in determining the number of layers and the weights of the neurons. For example, Akida 1000 uses far fewer nodes (4 NPUs) doing key word spotting than it uses in image classification.

Their reference to "conventional static networks" is a reference to analog NNs. Akida is not a "conventional static network". Making decisions may be more efficient, but what about the time/energy in reconfiguring the function of the devices in the whole network?

 

[Slade]

I don't know if this has been posted before (youtube March 24, 2022). It's an Eastronics BrainChip Webinar. Despite the guys not being as smooth as Rob and Todd with Akida there are some interesting things covered. The Rob and Todd bit is not new at the start but the Eastronics guy and a French BrainChip engineer come on at around 38 mins. It's not too polished and a little frustrating at times. Interesting that he says you can buy the chip from MegaChips or Renesas in the form of some general purpose chip. He loses his internet connection but does the Akida demo at the end.

 

[Jumpchooks]

Did your vehicles have bullbars or were they higher four wheel drive type vehicles?

I am speaking about vehicles like the ordinary passenger sedan.

In the case I mentioned the insurer pleaded contributory negligence and a great deal of expert evidence from different engineers with a range of experience in the area of accident reconstruction reported and they all agreed that the physics supported the risk of an animal in this case a horse rolling onto the bonnet and through the windscreen.

The issue was whether my client was paying proper attention and if he could have avoided the collision.

FF.

Y

Did your vehicles have bullbars or were they higher four wheel drive type vehicles?

I am speaking about vehicles like the ordinary passenger sedan.

In the case I mentioned the insurer pleaded contributory negligence and a great deal of expert evidence from different engineers with a range of experience in the area of accident reconstruction reported and they all agreed that the physics supported the risk of an animal in this case a horse rolling onto the bonnet and through the windscreen.

The issue was whether my client was paying proper attention and if he could have avoided the collision.

FF.

 

[Jumpchooks]

Y

Did your vehicles have bullbars or were they higher four wheel drive type vehicles?

I am speaking about vehicles like the ordinary passenger sedan.

In the case I mentioned the insurer pleaded contributory negligence and a great deal of expert evidence from different engineers with a range of experience in the area of accident reconstruction reported and they all agreed that the physics supported the risk of an animal in this case a horse rolling onto the bonnet and through the windscreen.

The issue was whether my client was paying proper attention and if he could have avoided the collision.

FF.

Yes , we were driving 4wd vehicles with bull bars. I agree the risk of impact through the windscreen is very high in low bonnet passenger cars.

 

[IloveLamp]

Hi ILL,

This is pretty much blue sky research and won't be out of the lab any time soon.

https://spectrum.ieee.org/neuromorphic-computing-ai-device

The scientists note that they fabricated their devices using semiconductor-foundry-compatible techniques, suggesting they might readily find use within the electronics industry. However, "the status of our research is in its infancy," Zhang says. "Much more work is required to fabricate large-scale integrated test circuitry with these devices."

It is also talking about analog NNs using memristors.

An adaptable new device can transform into all the key electric components needed for artificial-intelligence hardware, for potential use in robotics and autonomous systems, a new study finds.

It has an extraordinarily short shelf life - 1.6 million switching operations at 300 MHz is about 2 milliseconds, and the hydrogen ion in the perovskite only hangs about for 6 months. Hydrogen is notoriously itinerant and can penetrate many molecular lattices. Optical fibres often have a nitride cladding to prevent hydrogen penetration, as hydrogen has an absorption band in the desired laser wavelength.

The new device proved stable over 1.6 million cycles of switching between states. "Also, hydrogen ions remain in the device for a long period of time after its initial treatment—over six months—which is encouraging," Park says

Switching the function of millions of devices seems to me to be an enormously complicated exercise.

The scientists incorporated protons into perovskite nickelate. Electric pulses applied to this material could shuffle the protons [hydrogen ions] around within the material's lattice, altering its electronic properties. The researchers could electrically reconfigure a device made from this proton-doped perovskite nickelate into a resistor, a memory capacitor, a neuron, or a synapse on demand.
...
The versatility of this device "could simplify AI circuit design for complex computational tasks by avoiding an agglomeration of different functional units that are area- and power-consuming," says study colead author Michael Tae Joon Park, an electrical engineer and materials scientist at Purdue. Potential applications include robotics and autonomous systems, he notes.

In simulations using the new device in an artificial neural network, which mimics the structure of neurons in biological brains, the scientists found that the reconfigurable nature of the new device enabled the neural network "to make its decisions more efficiently, compared to conventional static networks, in complex and ever-changing environments," Zhang says.

The researchers suggest their device could find use in grow-when-required networks, which are neural networks that can grow their computing power on demand. Similarly, such networks can shrink in size if the device detects nodes that are regularly inactive in order to become more efficient.

Akida is reconfigurable in that the library of models changes the weights of the neurons. I am not familiar with "grow-when-required networks", but Akida would seem to incorporate this capability in determining the number of layers and the weights of the neurons. For example, Akida 1000 uses far fewer nodes (4 NPUs) doing key word spotting than it uses in image classification.

Their reference to "conventional static networks" is a reference to analog NNs. Akida is not a "conventional static network". Making decisions may be more efficient, but what about the time/energy in reconfiguring the function of the devices in the whole network?

View attachment 3708

Thanks Dio,

Honestly I only understood maybe half of that, but I get the gist. Thank you for explaining the difference

 

[Fact Finder]

I don't know if this has been posted before (youtube March 24, 2022). It's an Eastronics BrainChip Webinar. Despite the guys not being as smooth as Rob and Todd with Akida there are some interesting things covered. The Rob and Todd bit is not new at the start but the Eastronics guy and a French BrainChip engineer come on at around 38 mins. It's not too polished and a little frustrating at times. Interesting that he says you can buy the chip from MegaChips or Renesas in the form of some general purpose chip. He loses his internet connection but does the Akida demo at the end.

As I said the other day the demo at the end is a great add for why having a critical function in an EV being handed off to the web is a road map to the mortuary at 110 kph down hill on an expressway in the wet. The idea absolutely terrifies me given how many times a day my iPhone looses connection and I am only 17 kilometres from the heart of the CBD in Sydney.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Fact Finder]

Y

Yes , we were driving 4wd vehicles with bull bars. I agree the risk of impact through the windscreen is very high in low bonnet passenger cars.

The other thing to consider when a vehicle has a bull bar is the weight distribution and how it affects handling characteristics at speed straight on is a lot safer than attempting a sudden change of direction to avoid an animal. FF

 

[Dhm]

I don't know if this has been posted before (youtube March 24, 2022). It's an Eastronics BrainChip Webinar. Despite the guys not being as smooth as Rob and Todd with Akida there are some interesting things covered. The Rob and Todd bit is not new at the start but the Eastronics guy and a French BrainChip engineer come on at around 38 mins. It's not too polished and a little frustrating at times. Interesting that he says you can buy the chip from MegaChips or Renesas in the form of some general purpose chip. He loses his internet connection but does the Akida demo at the end.

I know BMW is on 'the wall' in the speculative users part, but the use of the Beemer at around 12 min 45 secs in the video hightens the likelihood of them being on board with us.

 

[Bravo]

Apropos of nothing, I feel very confident that LG know all about BrainChip's Akida, for the simple reason that Mercedes has revealed that LG was behind the infotainment screen in the Vision EQXX. This article states that "LG is also working with Mercedes for electric motors and ADAS technologies".

It would be completely unrealistic IMO for BrainChip, Mercedes and LG engineers to not to have worked in collaboration since (the way I understand it is), the only way that the operation of infotainment system reached such power efficiency was due to AKIDA.

LG Electrics...South Korea...

LIFE"S GOOD!

Mercedes To Use LG's Infotainment Screen On 2022 EQS

LG is behind the next generation hyperscreen that will debut on the 2022 EQS

www.carandbike.com

 

[thelittleshort]

Did this major European automobile manufacturer turn out to be Mercedes Benz or Ford (although they are American)?

 

[Slade]

As I said the other day the demo at the end is a great add for why having a critical function in an EV being handed off to the web is a road map to the mortuary at 110 kph down hill on an expressway in the wet. The idea absolutely terrifies me given how many times a day my iPhone looses connection and I am only 17 kilometres from the heart of the CBD in Sydney.

My opinion only DYOR
FF

AKIDA BALLISTA

Sorry I missed your post. Hard to keep up sometimes.

 

[Fact Finder]

That's true and I'm not 100% convinced by any means, I just like our chances (as in it sounds very AKIDA ish). I always take the narrative in these articles with a grain of salt as the accuracy and facts can be skewed by accident (due to incompetence) or on purpose (to mislead for whatever reason)

But I get what you're putting down

Because of my previous careers and my view of the reliability of human witnesses being used to underpin a judicial system I continue to take an interest in the science of and reliability of human memory.

The US has a lot of research going on in this area particularly since the use of DNA has shown so many people have been wrongly convicted as a result of honest but flawed memory of human witnesses.

Only yesterday I read a paper which after two years of research came to the conclusion that the process of asking a witness questions immediately after an event in fact made the witnesses memory less reliable and that the most accurate recollection of an event by a witness will occur about 5 days post the event following which the accuracy of the memory deteriorates. The research came to the conclusion that human eye witness evidence should be excluded.

The law used have a fundamental presumption that the passage of time made human memory of events so inherently unreliable that justice could not be served however we have for political and social reasons turned that on its head and allowed historical sexual assault and other crimes to be prosecuted on the basis of human memory.

The law has and still does give greater weight to statements made contemporaneously to the event on the basis that memory is fresher and more reliable the closer to the event you can take the eye witnesses statement. On the basis of research Police should wait 5 days and ensure no questions are put to the eye witness in the intervening period but even then it may still be flawed.

So how is this relevant well as @Diogenese has pointed out this attempt at brain emulation carries the same problem as the technology involved "has an extraordinarily short shelf life - 1.6 million switching operations at 300 MHz is about 2 milliseconds, and the hydrogen ion in the perovskite only hangs about for 6 months."

At some point the obsession with perfectly replicating the human brain will be seen for what it is a fools errand. We need something better than the human brain without all the flaws.

My opinion only DYOR
FF

AKIDA BALLISTA

Did this major European automobile manufacturer turn out to be Mercedes Benz or Ford (although they are American)?


View attachment 3709

The former CEO Mr. Dinardo mentioned Detroit enough that I am personally confident it was Mercedes in Europe and Ford in the US.

I DO LOVE READING MERCEDES DESCRIBING BRAINCHIP AS ARTIFICIAL INTELLIGENCE EXPERTS. (I even love typing it. )

We have an ‘Ai Thought Leader’ and ‘Ai Experts’ working for and promoting the company.

My opinion only DYOR
FF