BRN Discussion Ongoing

Thanks for posting that Q.

A technical question. Does Quadric accelerate others AI or do they have their own AI?

I’m questioning if Megachips has bought into Quadric to accelerate Akida. I was of the view, based on an interview with Anil Mankar and Denso staff together that Akida was going to be implemented in Denso technology so querying if that would be why Denso has announced they have signed Quadric.

Are they an add-on to help accelerate the information or decision making after Akida has done it’s work at the sensor?

Denso “Having evaluated Quadric’s q16 processor, its ability to run many types of algorithms efficiently and flexibly allows Quadric’s platform to enable AI in new services and products. We look forward to continuing to work closely with Quadric and plan to integrate their IP into DENSO’s SoCproducts.”

I’d be interested if someone with some technical expertise who could shed light on this please?

Cheers

I’ll start with a caution that I don’t know anything about this technology industry, it’s far from my field of expertise: but I can read and hopefully I have interpreted the words meanings correctly and can answer this one myself.


Introducing the First Generation quadric architecture.​

We built this architecture to meet the demands of various workloads. From Neural Networks to Digital Signal Processing to Computer Vision to the State of the Art that you're developing today we've got you covered. Develop your algorithms once and deploy them on any device that has a quadric architecture instance. When our architecture improves so will your algorithms.

So based on the description above I am surmising the announcement from Denso that they are using Quadric q16 in the development of their vehicles that there is still a chance Akida will be included. That the Quadric chip‘s purpose is to accelerate the algorithms after Akida has done it’s job at the sensor?

The reason I am trying to get to the bottom of this is that Denso is a massive in vehicles, they are part of the Toyota group, and would be great to have onboard.

Another reason I am thinking Denso are using Quadric to work with Akida is that they are both under Megachips banner and Denso is Japanese as well.

If anyone with technical knowledge wants to tell me I’m wrong I’m all ears, as I’m trying to learn.

By the way: great article about Mercedes Benz today FF. Fantastic news!

Cheers,
 
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I just been looking in the Brainchip store:

The Development kit- Shuttle PC is still available for just under 10 grand.

Also the PCIe board can be had for 500 bucks.

Lets hope they will get stock soon of the Development kit Raspberry Pi kit as it certainly will be in everyone's best interest to supply eager customers with what they want ASAP.

 
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"a soldier firing an NLAW simply points the weapon at a moving vehicle, engages the guidance system and tracks the target for a few seconds before firing. The missile then flies to a point where it predicts the target will be."


is looks to me like Akida. One step learning, two step learning, then pull the trigger.
 
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Diogenese

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I’ll start with a caution that I don’t know anything about this technology industry, it’s far from my field of expertise: but I can read and hopefully I have interpreted the words meanings correctly and can answer this one myself.


Introducing the First Generation quadric architecture.​

We built this architecture to meet the demands of various workloads. From Neural Networks to Digital Signal Processing to Computer Vision to the State of the Art that you're developing today we've got you covered. Develop your algorithms once and deploy them on any device that has a quadric architecture instance. When our architecture improves so will your algorithms.

So based on the description above I am surmising the announcement from Denso that they are using Quadric q16 in the development of their vehicles that there is still a chance Akida will be included. That the Quadric chip‘s purpose is to accelerate the algorithms after Akida has done it’s job at the sensor?

The reason I am trying to get to the bottom of this is that Denso is a massive in vehicles, they are part of the Toyota group, and would be great to have onboard.

Another reason I am thinking Denso are using Quadric to work with Akida is that they are both under Megachips banner and Denso is Japanese as well.

If anyone with technical knowledge wants to tell me I’m wrong I’m all ears, as I’m trying to learn.

By the way: great article about Mercedes Benz today FF. Fantastic news!

Cheers,

Hi SG,

We looked at Quadric a few pages ago: (There are a few more posts following this)

https://thestockexchange.com.au/threads/brn-discussion-2022.1/page-281#post-32194

Hi JB,

Quadric make what they call a "Supercomputer" which integrates the functions of CPU/GPT/AI accelerator using a modified CNN for image classification.

Its basic unit seems to be their Vortex ALU.

It won't be used for doorbells.

The White Paper 2019​

May, 2019

https://www.quadric.io/post/the-white-paper

we founded Quadric to build a product that brings server-class performance to the edge.

1647508064624.png



By 2015, researchers were proving classification results on the Imagenet challenge that exceeded human error rates. One such advanced CNN network architecture, RESNET50 strikes a balance between total computational network complexity and error rate.

1647508699958.png


####################################################################################

https://brainchipinc.com/wp-content...brief_6-How-BrainChip-is-Changing-AI_v1.2.pdf
The Akida Event-Based Neural Processor
The Akida event-based neural processor is a fundamentally different approach that breaks the linear relationship between high power consumption and performance seen in traditional accelerators. The Akida processor is 10x to 30x more energy-efficient than its nearest competitor for inferencing on industry-standard benchmarks such as MobileNet and Google Keyword Spotting DNNs, and is easy to use. Trained on MobileNet’s Imagenet 1000 data set, the Akida neural processor can classify all 1.2 million images, and 1,000 classes, at 30 frames per second within a power budget of just 156 milliwatts in 28nm, compared to several watts for a Google Edge TPU. Audio keyword recognition using the Google keyword database runs at an extremely low power of 150 microwatts
.

30 frames per second in 156 mW = 192 frames per second per Watt. (This is the 2019 Akida, not the improved 2021 commercial version - to be fair, the Quadric figures are from a 2019 white paper). So Quadric is in the same ballpark, but Akida has made home base, while Quadric just making 3rd.

The main difference is that Quadric is a Frankenstein amalgam of CPU, GPU and AI accelerator. Their AI accelerator uses ResNet50, an improved CNN arrangement which enables skip connections when intermediate layers are not required.

1647513839516.png



Also remember Akida's performance at key word spotting:
1647510358747.png


IPS = inferences (identified words) per second

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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Hi SG,

We looked at Quadric a few pages ago: (There are a few more posts following this)

https://thestockexchange.com.au/threads/brn-discussion-2022.1/page-281#post-32194

Hi JB,

Quadric make what they call a "Supercomputer" which integrates the functions of CPU/GPT/AI accelerator using a modified CNN for image classification.

Its basic unit seems to be their Vortex ALU.

It won't be used for doorbells.

The White Paper 2019​

May, 2019

https://www.quadric.io/post/the-white-paper

we founded Quadric to build a product that brings server-class performance to the edge.

1647508064624.png



By 2015, researchers were proving classification results on the Imagenet challenge that exceeded human error rates. One such advanced CNN network architecture, RESNET50 strikes a balance between total computational network complexity and error rate.

1647508699958.png


####################################################################################

https://brainchipinc.com/wp-content...brief_6-How-BrainChip-is-Changing-AI_v1.2.pdf
The Akida Event-Based Neural Processor
The Akida event-based neural processor is a fundamentally different approach that breaks the linear relationship between high power consumption and performance seen in traditional accelerators. The Akida processor is 10x to 30x more energy-efficient than its nearest competitor for inferencing on industry-standard benchmarks such as MobileNet and Google Keyword Spotting DNNs, and is easy to use. Trained on MobileNet’s Imagenet 1000 data set, the Akida neural processor can classify all 1.2 million images, and 1,000 classes, at 30 frames per second within a power budget of just 156 milliwatts in 28nm, compared to several watts for a Google Edge TPU. Audio keyword recognition using the Google keyword database runs at an extremely low power of 150 microwatts
.

30 frames per second in 156 mW = 192 frames per second per Watt. (This is the 2019 Akida, not the improved 2021 commercial version - to be fair, the Quadric figures are from a 2019 white paper). So Quadric is in the same ballpark, but Akida has made home base, while Quadric just making 3rd.

The main difference is that Quadric is a Frankenstein amalgam of CPU, GPU and AI accelerator. Their AI accelerator uses ResNet50, an improved CNN arrangement which enables skip connections when intermediate layers are not required.

1647513839516.png



Also remember Akida's performance at key word spotting:
1647510358747.png


IPS = inferences (identified words) per second

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.

Stock Disclosure:
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Reply
Report Edit Delete
Thanks for the reply Dio.

I don’t understand a lot of the terminology but I guess you‘re saying they are heavy on power use. If that’s the case why are Denso using them as the are car parts manufacturers and I thought we were trying to reduce power usage to improve efficiency?

How would they be used with Akida in a vehicle? Or because Denso have chosen Quadric that rules Akida out?

Sorry for asking silly questions but I can’t get my head around some of these concepts.

If the answers too convoluted that’s fine. It’ll all come out in the wash one day regardless and I’m confident of Brainchips profitability. I‘m just curious and hate not understanding things.

Cheers
 
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Diogenese

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Thanks for the reply Dio.

I don’t understand a lot of the terminology but I guess you‘re saying they are heavy on power use. If that’s the case why are Denso using them as the are car parts manufacturers and I thought we were trying to reduce power usage to improve efficiency?

How would they be used with Akida in a vehicle? Or because Denso have chosen Quadric that rules Akida out?

Sorry for asking silly questions but I can’t get my head around some of these concepts.

If the answers too convoluted that’s fine. It’ll all come out in the wash one day regardless and I’m confident of Brainchips profitability. I‘m just curious and hate not understanding things.

Cheers
On the figures they quote, they are quite good on power usage compared to the also-rans. They quote ~ 130 images/second/watt.

Akida (engineering sample) was 192 images/second/watt. Akida 1000 (commercial) has been said to have better performance than expected, but I haven't seen the figures. So the old Akida seems to be about 50% better than Quadric on this measure, assuming they were both tested on the same dataset of images.

They are using ALUs (arithmetic logic units), distributed memory, and ResNet50, which is a modified CNN arrangement with some form of data compression, if I recall correctly.

It seems to be directed to fairly heavy lifting, but I suppose they envisage it as a one-stop shop for automotive.
"we founded Quadric to build a product that brings server-class performance to the edge."

I don't see them as a danger re Mercedes, who are fairly committed to their do-it-yourself (with a couple of mates) system.

Where we may cross swords would be in the 64-chip Akida array type applications.
 
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On the figures they quote, they are quite good on power usage compared to the also-rans. They quote ~ 130 images/second/watt.

Akida (engineering sample) was 192 images/second/watt. Akida 1000 (commercial) has been said to have better performance than expected, but I haven't seen the figures. So the old Akida seems to be about 50% better than Quadric on this measure, assuming they were both tested on the same dataset of images.

They are using ALUs (arithmetic logic units), distributed memory, and ResNet50, which is a modified CNN arrangement with some form of data compression, if I recall correctly.
Thanks Dio.

I am laughing because you are speaking on so much a higher level than I can grasp.

My knowledge of computers how to switch it off for a minute and then turn it back on to reboot it!

It’s not your fault I can’t grasp the concept. Thanks for humouring me.

For example I don’t know what an ALU is, I’m guessing it uses maths to compute its decisions.

But it’s like the scene in the Simpson’s when Marge is talking and Homers thought bubble has a chimpanzee clanging symbols!

It’ll come out one day what Denso are doing when they release their product and I’ll go: “Ohhh, now I get it.”

Cheers!
 
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Thanks Dio.

I am laughing because you are speaking on so much a higher level than I can grasp.

My knowledge of computers how to switch it off for a minute and then turn it back on to reboot it!

It’s not your fault I can’t grasp the concept. Thanks for humouring me.

For example I don’t know what an ALU is, I’m guessing it uses maths to compute its decisions.

But it’s like the scene in the Simpson’s when Marge is talking and Homers thought bubble has a chimpanzee clanging symbols!

It’ll come out one day what Denso are doing when they release their product and I’ll go: “Ohhh, now I get it.”

Cheers!
1647946399202.gif
 
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Diogenese

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Thanks Dio.

I am laughing because you are speaking on so much a higher level than I can grasp.

My knowledge of computers how to switch it off for a minute and then turn it back on to reboot it!

It’s not your fault I can’t grasp the concept. Thanks for humouring me.

For example I don’t know what an ALU is, I’m guessing it uses maths to compute its decisions.

But it’s like the scene in the Simpson’s when Marge is talking and Homers thought bubble has a chimpanzee clanging symbols!

It’ll come out one day what Denso are doing when they release their product and I’ll go: “Ohhh, now I get it.”

Cheers!
The ALU is the bit where the number-crunching happens in the old fashioned von Neumann (vN) CPU. It adds two multi-bit binary numbers - usually between 8-bits and up to 128 bits or more, and can implement multiplication.

As far as I understand it, Quadric has distributed ALUs among numerous cells each with their own memory to avoid the (peak hour) vN bottleneck which occurs when all the data is stored in a large memory and must be transferred over a common 32 line (for example) cable (bus) to the single processor.

The operative interconnection of the processors can be reconfigured electronically.

########################################################### (SG-proof fence)

This is the patent for Quadric processor architecture:

US10474398B2 Machine perception and dense algorithm integrated circuit

1647949425187.png




A circuit that includes a plurality of array cores (110),
each array core of the plurality of array cores comprising:
a plurality of distinct data processing circuits; and

a data queue register file (130);

a plurality of border cores (120), each border core of the plurality of border cores comprising: at least a register file, wherein:
at least a subset of the plurality of border cores encompasses a periphery of a first subset of the plurality of array cores; and
[ii] a combination of the plurality of array cores and the plurality of border cores define an integrated circuit array
.

A good proportion of the array is used by the "border" processors (cores) 120 in organizing the data inputs/outputs of the working processors 110.
 
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Ah yeah, thanks Dio - that clears it up 🤔
 
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Vielleicht interessant. Hello ID Spracherkennung 95 Prozent genau 🦧🤖😁
 
 
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Schon wieder Mercedes 😁🍺💰
 
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Morning all,

Valeo received an award for their Lidar 3.

Isn’t it wonderful to be a known partner with Valeo (and possibly part of this lauded innovative technology).

Future looks good!

Valeo Lauded by Frost & Sullivan for Delivering Cutting-edge 3D Sensors and Related Software Perception Stack to the Automotive Industry​

Valeo is currently the only automotive supplier commercializing mass-produced automotive-grade LiDAR sensors, with the perception software included.

Valeo Lauded by Frost & Sullivan for Delivering Cutting-edge 3D Sensors and Related Software Perception Stack to the Automotive Industry

Valeo Award Logo
San Antonio — March 15, 2022 — Based on its recent analysis of the global automotive light detection and ranging (LiDAR) industry, Frost & Sullivan recognizes Valeo with the 2022 Global Market Leadership Award for strengthening its global market presence with pioneering automotive 3D sensors. Valeo is a globally renowned company with 99 years of expertise in the automotive sector and one of the biggest automotive suppliers worldwide.
Click here to view the full multimedia release: https://best-practices.frost.com/valeo/
Valeo’s advanced systems promote intuitive and effective driving, facilitating autonomous vehicle (AV) adoption. The company recently launched a new flagship product, SCALA®, which offers highly differentiated 3D sensing that enable superior autonomy, resolution, distance and speed measurement, pedestrian detection, and autonomous emergency braking, among other features.
“The company manufactures SCALA®, the automotive industry’s first commercial 3D LiDAR sensor for AV applications. Valeo SCALA® is a 3D mechanical scanning LiDAR sensor that offers a wide Field of View (FoV) of up to 145 degrees. Its AI-based integrated software detects, recognizes, and classifies static and dynamic objects up to a distance of 200 meters in all weather and lighting conditions,” said Kamalesh Mohanarangam, Research Manager at Frost & Sullivan. “Valeo’s sensor portfolio includes ultrasonic sensors, cameras, and radars, providing intelligent sensing solutions for advanced driver-assistance systems (ADAS) and autonomous applications.”
Valeo seeks to be a key player in the future of global mobility while addressing the current environmental and societal challenges. To this end, the company leverages its solid market position to work closely with automakers, new mobility players, and technology partners and meet customer demands with breakthrough solutions that improve driving-assistance systems, telematics, lighting setup, interior control software, and much more.
The company is committed to research and development and has 63 research centers working to create cutting-edge, advanced technologies at industry-standard costs. To date, Valeo’s strategy of innovating forward-looking products enabled it to maintain its market leadership and the company is expected to continue leading the LiDAR industry in the long term.
“Valeo’s growth strategy focuses on innovation in solutions and market expansion in high-growth countries. The company positions itself as a technology company for electric and AV applications and has solidified its market leadership by equipping one-third of global electric and AV volumes with innovative solutions,” noted Mohanarangam. “With innovation as its key growth strategy, Valeo will strengthen its global market presence and extend its solution offerings in the electric and AV market.”
Each year, Frost & Sullivan presents this award to the company that has developed an innovative element in a product by leveraging leading-edge technologies. The award recognizes the value-added features/benefits of the product and the increased ROI it offers customers, which, in turn, raises customer acquisition and overall market penetration potential.
Frost & Sullivan Best Practices awards recognize companies in various regional and global markets for demonstrating outstanding achievement and superior performance in leadership, technological innovation, customer service, and strategic product development. Industry analysts compare market participants and measure performance through in-depth interviews, analyses, and extensive secondary research to identify best practices in the industry.

Peace




Valeo’s LiDAR technology, the key to conditionally automated driving, part of the Mercedes-Benz DRIVE PILOT SAE-Level 3 system​



Valeo SCALA® 2, Valeo's second generation LiDAR, plays an important role in Mercedes-Benz DRIVE PILOT system for conditionally automated driving (SAE-Level 3), allowing the driver to delegate under certain conditions the driving task to the car in complete safety.

The new Mercedes-Benz S-Class is the first car in the world to be equipped with this Valeo technology. In December 2021, Mercedes-Benz received the world’s first internationally valid system approval for conditionally automated driving (SAE-Level 3), meeting the demanding legal requirements of UN-R157 for such a system. If the particular national legislation allows it, DRIVE PILOT is able to operate in conditionally automated driving mode at speeds of up to 60 km/h, in heavy traffic or congested situations and on suitable stretches of motorway. DRIVE PILOT will be available in Germany in the first half of 2022. The next step is clear: the car manufacturer plans to apply for regulatory approval in California and Nevada in 2022.
Valeo SCALA® 2 sees what the human eye, cameras and radars cannot see and adapts to all light conditions and changes according to light levels. It is not blinded by sunlight and can see equally well in total darkness.
It measures the distance to surrounding objects to the nearest centimeter, by calculating the time it takes its laser beam to travel to an obstacle and back again. This enables it to build a complete 3D image of the vehicle’s surroundings. The image, called a “point cloud,” is analyzed by sophisticated algorithms to identify all of the objects, allowing the device to distinguish between moving and static objects. It classifies them into different categories, such as cars, trucks, buses, bicycles, motorcycles, pedestrians, infrastructure, and captures their shape and position.
If the objects are moving, it measures their speed and keeps tracking them, even when they are no longer in the driver’s line of sight. It predicts the objects’ behavior and trajectory. But it doesn’t just detect objects: it also anticipates open space where the car can drive safely. It even spots small objects, for example a tire that has fallen on the road. It is equipped with a specific algorithm that recognizes road markings based on their contrast with the road.
With its software, Valeo SCALA® 2 transforms the raw data from the sensor into useful data. It eliminates any data that could alter its calculations, as if it were filtering the information to validate only relevant data. This enables it to cancel out any “echoes” caused by raindrops on its light pulse so that it can see through the rain and measure the density of a rain shower. Its software even allows it to troubleshoot itself. Its exclusive cleaning and heating system is triggered whenever its field of vision is blocked, by dust or ice for example.
Valeo’s LiDAR is the successful combination of high-precision mechanics, optics and electronics with software, algorithms and artificial intelligence, making it reliable, sharp and intelligent. In addition to its technological leadership, Valeo also leads in manufacturing capabilities. The Valeo Group is currently the only player in the world to produce on a large scale an automotive LiDAR scanner*. Valeo SCALA® 2, central to the Mercedes-Benz DRIVE PILOT system, which helps give back drivers time during their journey.
________
* On March 15, 2022, Valeo was recognized by the American institute Frost & Sullivan as a pioneer and key player in LiDAR 3D laser scanners with the 2022 Global Market Leadership Award.
 
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View attachment 2989


View attachment 2990
The sentence that got me thinking in the article was:

"We are the world’s first commercial producer of ultra-low-power and high-performance artificial intelligence technology processors that enables a wide array of applications such as self-driving cars, hearing aids, drones, and agricultural equipment. "

They have never written this in a job description before, and one would have a guess and say that AKIDA has already been selected for the use in these applications for certain NDA's. The IP or chips may already be used in some of these applications and will be interesting to see the growth in sales in the next 4C.

Also, does anyone have any dot joins on the application of hearing aids and agricultural equipment?

1647983157110.png
 
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Learning

Learning to the Top 🕵‍♂️
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