BRN Discussion Ongoing

Bravo

If ARM was an arm, BRN would be its biceps💪!
Hang on everyone! Put the cork back in the Bollingers.

I found this article from April 2022, which discusses Prophesee in collaboration with iCatch on a new event-based imaging sensor. And it repeats the same info as described in Qualcomm's presentation ans well as the slide I posted earlier. It states "From a hardware perspective, the new sensor appears to be very impressive, offering specs such as a >10k fps time-resolution equivalent, >120 dB dynamic range, and a 3nW/event power consumption. From a compute perspective, Metavision promises anywhere from 10 to 1000x less data than frame-rate-based solutions, with a throughput of >1000 obj/s, and a motion period irregularity detection of 1%."


Event-based Vision Sensor—“Metavison”—Promises Impressive Specs​

April 20, 2022 by Jake Hertz

PROPHESEE, along with iCatch, have teamed up to provide the industry with the "world's first event-based vision sensor" in a 13 x 15 mm mini PGBA package.​


As computer vision applications gain more and more momentum, companies are continually investing in new ways to improve the technology. At the same time, as pure imaging improves, power efficiency and data management become significant challenges on the hardware level.

An example computer vision block diagram.

An example computer vision block diagram. Image used courtesy of Cojbasic et al


One proposed solution to this challenge is ditching conventional imaging techniques in favor of event-based vision. Aiming to capitalize on this type of technology, this week, PROPHESEE, in collaboration with iCatch, released a new event-based vision sensor that boasts some impressive specs.
This article will discuss the concept of event-based vision, the benefits it offers, and dissect PROPHESEE’s newest offering.

Challenges in Conventional Vision​

One of the significant challenges in imaging systems is that, as imaging systems become conventionally better, they tend to put more stress on the hardware. Notably, as resolutions and field of view become better, the amount of raw data produced by the camera also increases.
While this may be a positive thing in terms of imaging quality, it creates a plethora of challenges for supporting hardware.

An example block diagram of a general image sensor.

An example block diagram of a general image sensor. Image used courtesy of Microsoft and LiKamWa et al


This increase in data traffic can have the harmful effect of placing an increased burden on computing resources, which now need to be able to process more data at faster speeds to maintain real-time operation. On top of this, conventional imaging systems work by applying the same frame rate to all objects in the scene. The result is that moving objects may end up being undersampled, and the important data in a scene can end up being lost.
When applied to machine learning, this increase in data traffic equals higher latency and more power consumption needed to complete a task. At the same time, much of the data being processed may not even be the essential information within a scene—further adding to the wasted energy and latency of the system.
These problems become even more concerning when coupled with the increasing demand for low power, low latency systems.

Solutions With Event-Based Vision?​

In an attempt to alleviate these issues, one promising solution is event-based vision.

Event-based vision (right) aims to remove redundant information from conventional vision (left) systems.

Event-based vision (right) aims to remove redundant information from conventional vision (left) systems. Image used courtesy of PROPHESEE


The concept of event-based vision rejects traditional frame-based imaging approaches, where every pixel reports back everything it sees at all times.
Instead, event-based sensing relies on each pixel to report what it sees only if it senses a significant change in its field of view. By only producing data when an event occurs, event-based sensing significantly reduces that raw amount of data created by imaging systems while also ensuring that the produced data is full of useful information.
Overall, the direct result type of sensing technology is that machine learning algorithms have to process less data, meaning less power consumption and lower latency overall.

The Metavision Sensor​

This week, PROPHESEE, in collaboration with iCatch, announced the release of its brand new event-based imaging sensor.
Dubbed the "Metavision sensor," the new IC leverages specialized pixels which only respond to changes in its field of view, activating themselves independently when triggered by events. While not an entirely novel technology, PROPHESEE claims that Metavision is the world's first event-based vision sensor available in an industry-standard package, coming in a 13 x 15 mm mini PGBA package.

The new Metavision sensor.

The new Metavision sensor. Image used courtesy of PROPHESEE


From a hardware perspective, the new sensor appears to be very impressive, offering specs such as a >10k fps time-resolution equivalent, >120 dB dynamic range, and a 3nW/event power consumption.
From a compute perspective, Metavision promises anywhere from 10 to 1000x less data than frame-rate-based solutions, with a throughput of >1000 obj/s, and a motion period irregularity detection of 1%.

Push for More Event-based Vision​

With Metavision, PROPHESEE and iCatch appear to have brought an exciting and promising new technology to an industry-standard format, making it more accessible for engineers everywhere.
Thanks to this, the companies are hopeful that event-based vision could start to permeate into the industry and bring its benefits along with it.
 
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Terroni2105

Founding Member
Of course a simple Google search revealed Qualcomm has it’s own Neural Software:

View attachment 27506

So I could be guilty of jumping the gun on this one and providing poorly researched information!

Sorry. :(


Edit: I might blame my pain meds!
But he talks about hardware and Akida is hardware isn’t it?
“…this is happening in hardware in real time in 60fps and can be shot with video or photo so pretty cool stuff and you can only do this in hardware”

edit. I just relistened to the video and the part I have quoted above is not,related to,Prophesee, it is when he is talking about another bit
 
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Thank you!







Is this what you are looking for not sure if someone already sorted you out.
 

Diogenese

Top 20
Hang on everyone! Put the cork back in the Bollingers.

I found this article from April 2022, which discusses Prophesee in collaboration with iCatch on a new event-based imaging sensor. And it repeats the same info as described in Qualcomm's presentation ans well as the slide I posted earlier. It states "From a hardware perspective, the new sensor appears to be very impressive, offering specs such as a >10k fps time-resolution equivalent, >120 dB dynamic range, and a 3nW/event power consumption. From a compute perspective, Metavision promises anywhere from 10 to 1000x less data than frame-rate-based solutions, with a throughput of >1000 obj/s, and a motion period irregularity detection of 1%."


Event-based Vision Sensor—“Metavison”—Promises Impressive Specs​

April 20, 2022 by Jake Hertz

PROPHESEE, along with iCatch, have teamed up to provide the industry with the "world's first event-based vision sensor" in a 13 x 15 mm mini PGBA package.​


As computer vision applications gain more and more momentum, companies are continually investing in new ways to improve the technology. At the same time, as pure imaging improves, power efficiency and data management become significant challenges on the hardware level.

An example computer vision block diagram.

An example computer vision block diagram. Image used courtesy of Cojbasic et al


One proposed solution to this challenge is ditching conventional imaging techniques in favor of event-based vision. Aiming to capitalize on this type of technology, this week, PROPHESEE, in collaboration with iCatch, released a new event-based vision sensor that boasts some impressive specs.
This article will discuss the concept of event-based vision, the benefits it offers, and dissect PROPHESEE’s newest offering.

Challenges in Conventional Vision​

One of the significant challenges in imaging systems is that, as imaging systems become conventionally better, they tend to put more stress on the hardware. Notably, as resolutions and field of view become better, the amount of raw data produced by the camera also increases.
While this may be a positive thing in terms of imaging quality, it creates a plethora of challenges for supporting hardware.

An example block diagram of a general image sensor.

An example block diagram of a general image sensor. Image used courtesy of Microsoft and LiKamWa et al


This increase in data traffic can have the harmful effect of placing an increased burden on computing resources, which now need to be able to process more data at faster speeds to maintain real-time operation. On top of this, conventional imaging systems work by applying the same frame rate to all objects in the scene. The result is that moving objects may end up being undersampled, and the important data in a scene can end up being lost.
When applied to machine learning, this increase in data traffic equals higher latency and more power consumption needed to complete a task. At the same time, much of the data being processed may not even be the essential information within a scene—further adding to the wasted energy and latency of the system.
These problems become even more concerning when coupled with the increasing demand for low power, low latency systems.

Solutions With Event-Based Vision?​

In an attempt to alleviate these issues, one promising solution is event-based vision.

Event-based vision (right) aims to remove redundant information from conventional vision (left) systems.

Event-based vision (right) aims to remove redundant information from conventional vision (left) systems. Image used courtesy of PROPHESEE


The concept of event-based vision rejects traditional frame-based imaging approaches, where every pixel reports back everything it sees at all times.
Instead, event-based sensing relies on each pixel to report what it sees only if it senses a significant change in its field of view. By only producing data when an event occurs, event-based sensing significantly reduces that raw amount of data created by imaging systems while also ensuring that the produced data is full of useful information.
Overall, the direct result type of sensing technology is that machine learning algorithms have to process less data, meaning less power consumption and lower latency overall.

The Metavision Sensor​

This week, PROPHESEE, in collaboration with iCatch, announced the release of its brand new event-based imaging sensor.
Dubbed the "Metavision sensor," the new IC leverages specialized pixels which only respond to changes in its field of view, activating themselves independently when triggered by events. While not an entirely novel technology, PROPHESEE claims that Metavision is the world's first event-based vision sensor available in an industry-standard package, coming in a 13 x 15 mm mini PGBA package.

The new Metavision sensor.

The new Metavision sensor. Image used courtesy of PROPHESEE


From a hardware perspective, the new sensor appears to be very impressive, offering specs such as a >10k fps time-resolution equivalent, >120 dB dynamic range, and a 3nW/event power consumption.
From a compute perspective, Metavision promises anywhere from 10 to 1000x less data than frame-rate-based solutions, with a throughput of >1000 obj/s, and a motion period irregularity detection of 1%.

Push for More Event-based Vision​

With Metavision, PROPHESEE and iCatch appear to have brought an exciting and promising new technology to an industry-standard format, making it more accessible for engineers everywhere.
Thanks to this, the companies are hopeful that event-based vision could start to permeate into the industry and bring its benefits along with it.

Put your happy pants back on - April 2022 was before June 2022 if I remember correctly:-

https://www.prophesee.ai/2022/06/20/brainchip-partners-with-prophesee/

BrainChip Partners with Prophesee Optimizing Computer Vision AI Performance and Efficiency​


Laguna Hills, Calif. – June 14, 2022 – BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of neuromorphic AI IP, and Prophesee, the inventor of the world’s most advanced neuromorphic vision systems, today announced a technology partnership that delivers next-generation platforms for OEMs looking to integrate event-based vision systems with high levels of AI performance coupled with ultra-low power technologies.
 
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But he talks about hardware and Akida is hardware isn’t it?
“…this is happening in hardware in real time in 60fps and can be shot with video or photo so pretty cool stuff and you can only do this in hardware”

Yes. I agree and I did see that was software whereas they were promoting on chip hardware but I was a bit exuberant at the start and hadn’t looked into it as close as I should before I started celebrating so I was putting a bit more of a realistic approach to my post so as not to raise expectations. Ultimately we still haven’t got an affirming announcement, even via media if not the ASX.

I see Bravo has probably now probably found the answer with Icatch. Although again I’m not sure where Icatch has gotten their hardware from as it looks (with a quick read) they are SOC designers which my understanding is they still needed to get their IP from somewhere.


I was hoping someone with actual technical knowledge could fill the void of my lack of knowledge!

The highs and lows, knowns and unknowns!

Edit: and DIO has entered the room. Someone with actual technical knowledge and expertise; so I’ll listen to him.
 
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Dhm

Regular
Sorry....off piste, but I just witnessed a new Australian tennis star win just then. Alexie Popyrin. Amazing game, amazingly humble.
 
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Getupthere

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Yes. I agree and I did see that was software whereas they were promoting on chip hardware but I was a bit exuberant at the start and hadn’t looked into it as close as I should before I started celebrating so I was putting a bit more of a realistic approach to my post so as not to raise expectations. Ultimately we still haven’t got an affirming announcement, even via media if not the ASX.

I see Bravo has probably now probably found the answer with Icatch. Although again I’m not sure where Icatch has gotten their hardware from as it looks (with a quick read) they are SOC designers which my understanding is they still needed to get their IP from somewhere.


I was hoping someone with actual technical knowledge could fill the void of my lack of knowledge!

The highs and lows, knowns and unknowns!

Edit: and DIO has entered the room. Someone with actual technical knowledge and expertise; so I’ll listen to him.
I had another listen to the Brainchip Prophesee podcast today.

Apologies for the rough transcript copying:
25:32
continues to evolve um that's for sure so let's talk about brain chip and prophecy and you know I
25:39
remember when when we had you here uh in in in Laguna Hills at our facility and
25:46
and we start to show you some of the demos that we were doing with some of your systems and and the time frame it
25:51
took us and the excitement on Kristoff's face when whoa this is great um and we're building upon that and
25:57
we're going to continue driving that forward the the closeness between the prophecy technology and what you guys
26:03
have done and leveraging brainships you know neural network accelerator with the
26:08
Kia Akita excuse me and what we're doing um so let's talk about that let's talk
26:14
about how they complement and enhance the performance of your products
and uh just tell us a little bit about that
26:20
yeah so I must say that we we are very excited about this this collaboration with uh with the brain chip uh because I
26:28
would uh I mean we are natural natural partner we our technology are are very
26:35
uh complementary
from the very beginning when we started the prophecy with Kristoff we knew that um
26:43
um we were actually building a house of story in fact because the retina the
26:48
retina per se is an extension of the brain that is doing uh this fantastic
26:54
job of pre-select processing information only sending what is relevant for the
26:59
decision but then the brain is doing the Rex is is actually
27:04
processing this event and then taking the decision and today what we are doing
27:10
at process is that um uh from the beginning we have been we have been
27:15
interfacing our sensor with the conventional uh compute platform based on conventional architecture that are
27:22
today optimized for frame-based type of data uh and therefore uh we faced we
27:30
have been facing we're still facing some integration challenges uh that are
27:35
sometimes uh also uh impacting to some extent the performance of of of the
27:43
sensor itself right you need to make some trade-off so now combining our
27:48
human inspired sensor with uh brainship human inspired the processing platform
27:54
which is actually by Design like our sensor conceived to actually process starts and
28:01
asynchronous and fast data that are naturally generated by ourselves then then the health story we're missing from
28:08
the beginning with Christoph is now complete now we can tell a full story to our customers
it is extremely powerful
28:14
because all the intrinsic benefit of this human inspired technology from the
28:20
acquisition to the process into the decision is now is now possible so now we can really show
28:26
um we really push the level of performance in terms of speed in terms of efficiency uh to uh to levels that
28:34
are unprecedented in the industry
yeah it's absolutely correct and this is this
28:40
this is a really key point for for all of our listeners um

This is a key exchange between Luca and Rob without disclosing confidential information. My interpretation of this conversation is that Prophesee would be CRAZY to use anything else other than Akida as much as possible IF:
- They don't want lesser performance
- They don't want said trade off's to use a different technology to Akida
- They don't want continued challenges in integration
- They don't want to continue along the path of already precedented levels of performance in the industry

I recommend giving the podcast another listen to all who haven't already! My favourite podcast Brainchip has done to date.
 
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Adam

Regular
Hey GUYS

I'M BACK. long story and i have so much catching up to do. But all is well now and I'm back :) If someone can summarise in a nutshell what i missed :cool:
We're all here. Everyone is doing great dot joining to 5 million companies. Some downrampers, but, as a LTH, I'm gonna wait till the NDAs are signed off, and we see a formal statement from Brainchip, then, we buy the champagne. Here endeth the sermon.
 
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Getupthere

Regular

Home » AI » Consumer Products Could Soon Feature Neuromorphic Sensing

Consumer Products Could Soon Feature Neuromorphic Sensing​

Article By : Sally Ward-Foxton​

Prophesee-Sony-Sensor_600.jpg

In this interview with Prophesee CEO Luca Verre, we discuss Prophesee's approach to commercializing its retina-inspired sensors and where the technology will go from here.
What does “neuromorphic” mean today?
“You will get 10 different answers from 10 different people,” laughed Luca Verre, CEO of Prophesee. “As companies take the step from ‘this is what we believe’ to ‘how can we make this a reality,’ what neuromorphic means will change.”
Most companies doing neuromorphic sensing and computing have a similar vision in mind, he said, but implementations and strategies will be different based on varying product, market, and investment constraints.
【Download】The QA exchange deck in Solido Crosscheck enables an IP qualification handshake
“The reason why… all these companies are working [on neuromorphic technologies] is because there is a fundamental belief that the biological model has superior characteristics compared to the conventional,” he said. “People make different assumptions on product, on system integration, on business opportunities, and they make different implementations… But fundamentally, the belief is the same.”
Prophesee CEO Luca Verre Luca Verre (Source: Prophesee)
Verre’s vision is that neuromorphic technologies can bring technology closer to human beings, which ultimately makes for a more immersive experience and allows technologies such as autonomous driving and augmented reality to be adopted faster.
“When people understand the technology behind it is closer to the way we work, and fundamentally natural, this is an incredible source of reassurance,” he said.
Which markets first?
Prophesee is already several years into its mission to commercialize the event–based camera using its proprietary dynamic vision sensor technology. The company has collaborated with camera leader Sony to make a compact, high–resolution event–based camera module, the IMX 636. In this module, the photodiode layer is stacked directly on top of the CMOS layer using Sony’s 3D die stacking process.
According to Verre, the sector closest to commercial adoption of this technology is industrial machine vision.
“Industrial is a leading segment today because historically we pushed our third–generation camera into this segment, which was a bigger sensor and more tuned for this type of application,” he said. “Industrial has historically been a very active machine vision segment, in fact, it is probably one of the segments that adopted the CCD and CMOS technologies at the very beginning… definitely a key market.”
Prophesee Sony IMX 636 event-based camera Prophesee and Sony IMX 636 is a fourth-generation product. Prophesee said future generations will reduce pixel pitch and ease integration with conventional computing platforms (Source: Prophesee)
The second key market for the IMX 636 is consumer technologies, driven by the shrink in size enabled by Sony’s die–stacking process. Consumer applications include IoT cameras, surveillance cameras, action cameras, drones, consumer robots, and even smartphones. In many cases, the event–based camera is used alongside a full–frame camera, detecting motion so that image processing can be applied to capture better quality images, even when the subject is moving.
“The reason is very simple: event–based cameras are great to understand motion,” he said. “This is what they are meant for. Frame–based cameras are more suited to understanding static information. The combination of the dynamic information from an event–based camera and static information from a frame–based camera is complementary if you want to capture a picture or video in a scene where there’s something moving.”
Event data can be combined with full–frame images to correct any blur on the frame, especially for action cameras and surveillance cameras.
“We clearly see some traction in this in this area, which of course is very promising because the volume typically associated with this application can be quite substantial compared to industrial vision,” he said.
Prophesee is also working with a customer on automotive driver monitoring solutions, where Verre said event–based cameras bring advantages in terms of low light performance, sensitivity, and fast detection. Applications here include eye blinking detection, tracking or face tracking, and micro–expression detection.
Approach to commercialization
Prophesee's EV4 evaluation kit Prophesee’s EV4 evaluation kit (Source: Prophesee)
Prophesee has been working hard on driving commercialization of event–based cameras. The company recently released a new evaluation kit (EVK4) for the IMX 636. This kit is designed for industrial vision with a rugged housing but will work for all applications (Verre said several hundred of these kits have been sold). The company’s Metavision SDK for event–based vision has also recently been open–sourced in order to reduce friction in the adoption of event–based technology. The Metavision community has around 5,000 registered members today.
“The EDK is a great tool to further push and evangelize the technology, and it comes in a very typical form factor,” Verre said. “The SDK hides the perception of complexity that every engineer or researcher may have when testing or exploring a new technology… Think about engineers that have been working for a couple of decades on processing images that now see events… they don’t want to be stretched too much out of their comfort zone.”
New to the Metavision SDK is a simulator to convert full frames into events to help designers transition between the way they work today and the event domain. Noting a reluctance of some designers to move away from full frames, Verre said the simulator is intended to show them there’s nothing magic about events.
“[Events are] just a way of capturing information from the scene that contains much more temporal precision compared to images, and is actually much more relevant, because typically you get only what is changing,” he said.
How Prophesee's event-based cameras work How Prophesee’s event-based cameras work (click to enlarge) (Source: Prophesee)
The simulator can also reconstruct image full frames from event data, which he says people find reassuring.
“The majority of customers don’t pose this challenge any longer because they understand that they need to see from a different perspective, similar to when they use technology like time of flight or ultrasound,” he said. “The challenge is when their perception is that this is another image sensor… for this category of customer, we made this tool that can show them the way to transition stepwise to this new sensing modality… it is a mindset shift that may take some time, but it will come.”
Applications realized in the Prophesee developer community include restoring some sight for the blind, detecting and classifying contaminants in medical samples, particle tracking in research, robotic touch sensors, and tracking space debris.
Hardware roadmap
In terms of roadmap, Prophesee plans to continue development of both hardware and software, alongside new evaluation kits, development kits, and reference designs. This may include system reference designs which combine Prohpesee sensors with specially developed processors. For example, Prohpesee partner iCatch has developed an AI vision processor SoC that interfaces natively with the IMX 636 and features an on–chip event decoder. Japanese AI core provider DMP is also working with Prophesee on an FPGA–based system, and there are more partnerships in the works, said Verre.
“We see that there is growing interest from ecosystem partners at the SoC level, but also the software level, that are interested in building new solutions based on Prophesee technology,” he said. “This type of asset is important for the community, because it is another step towards the full solution — they can get the sensor, camera, computing platform, and software to develop an entire solution.”
Prophesee event-based camera roadmap The evolution of Prophesee’s event-based vision sensors (click to enlarge) (Source: Prophesee)
Where does event–based sensor hardware go from here? Verre cited two key directions the technology will move in. The first is further reduction of pixel size (pixel pitch) and overall reduction of the sensor to make it suitable for compact consumer applications such as wearables. The second is facilitating the integration of event–based sensing with conventional SoC platforms.
Working with computing companies will be critically important to ensure next–generation sensors natively embed the capability to interface with the computing platform, which simplifies the task at the system level. The result will be smarter sensors, with added intelligence at the sensor level.
“We think events make sense, so let’s do more pre-processing inside the sensor itself, because it’s where you can make the least compromise,” Verre said. “The closer you get to the acquisition of the information, the better off you are in terms of efficiency and low latency. You also avoid the need to encode and transmit the data. So this is something that we are pursuing.”
As foundries continue to make progress in the 3D stacking process, stacking in two or even three layers using the most advanced CMOS processes can help bring more intelligence down to the pixel level.
How much intelligence in the pixel is the right amount?
Verre said it’s a compromise between increasing the cost of silicon and having sufficient intelligence to make sure the interface with conventional computing platforms is good enough.
“Sensors don’t typically use advanced process nodes, 28nm or 22nm at most,” he said. “Mainstream SoCs use 12nm, 7nm, 5nm, and below, so they’re on technology nodes that can compress the digital component extremely well. The size versus cost equation means at a certain point it’s more efficient, more economical [to put the intelligence] in the SoC.”
Applications for Prophesee event-based cameras A selection of applications for Prophesee event-based cameras (click to enlarge) (Source: Prophesee)
There is also a certain synergy to combining event–based sensors with neuromorphic computing architectures.
“The ultimate goal of neuromorphic technology is to have both the sensing and processing neuromorphic or event–based, but we are not yet there in terms of maturity of this type of solution,” he said. “We are very active in this area to prepare for the future — we are working with Intel, SynSense, and other partners in this area — but in the short term, the mainstream market is occupied by conventional SoC platforms.
Prophesee’s approach here is pragmatic. Verre said the company’s aim is to try to minimize any compromises to deliver benefits that are superior to conventional solutions.
“Ultimately we believe that events should naturally stream asynchronously to a compute architecture that is also asynchronous in order to benefit fully in terms of latency and power,” he said. “But we need to be pragmatic and stage this evolution, and really capitalize on the existing platforms out there and work with key partners in this space that are willing to invest in software–hardware developments and to optimize certain solution for certain markets.”
This article was originally published on EE Times.
Sally Ward-Foxton covers AI technology and related issues for EETimes.com and all aspects of the European industry for EE Times Europe magazine. Sally has spent more than 15 years writing about the electronics industry from London, UK. She has written for Electronic Design, ECN, Electronic Specifier: Design, Components in Electronics, and many more. She holds a Masters’ degree in Electrical and Electronic Engineering from the University of Cambridge.
 
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Earlyrelease

Regular
Well my takeaway from today must be the definition of the employment term for hybrid.
I look forward to applying this to my retirement plans. Thus a $10 SP, I will swap between sightseeing, indulging in fine food and drinks between a variety of workplaces aka- locations which may or may not be restricted the WA hopefully consisting of palms trees beaches and stunning scenery.
🌴🛩️🛳️🏕️⛩️🛤️🕌
 
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chapman89

Founding Member
Put your happy pants back on - April 2022 was before June 2022 if I remember correctly:-

https://www.prophesee.ai/2022/06/20/brainchip-partners-with-prophesee/

BrainChip Partners with Prophesee Optimizing Computer Vision AI Performance and Efficiency​


Laguna Hills, Calif. – June 14, 2022 – BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of neuromorphic AI IP, and Prophesee, the inventor of the world’s most advanced neuromorphic vision systems, today announced a technology partnership that delivers next-generation platforms for OEMs looking to integrate event-based vision systems with high levels of AI performance coupled with ultra-low power technologies.
Hi Dio, luca told me back in October 2022 that the relationship between Prophesee & Brainchip started back in 2021…..despite the offical announcement in June 2022.
DDB8F93A-D43F-4CAD-B0D8-F4B4E660B0B5.jpeg
 
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buena suerte :-)

BOB Bank of Brainchip
Sorry....off piste, but I just witnessed a new Australian tennis star win just then. Alexie Popyrin. Amazing game, amazingly humble.
Absolutely Dhm.... What a game ... Great Lad .. looking forward to his next match:cool:
 
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Boab

I wish I could paint like Vincent
“A ‘Level 3’ system (semi-autonomous system), whether at 60, 80 or 120 kilometres per hour, which constantly switches off in the tunnel, switches off when it rains, switches off in the dark, switches off in fog – what’s that supposed to mean? No customer buys it.

I know a Co that has the solution.

 
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Jumpchooks

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skutza

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They still need AKIDA desperately though. If he says get my tools, he may get the bag or he may get the tool from Motley fool. One shot learning to tell the difference between tools!
 
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Bravo

If ARM was an arm, BRN would be its biceps💪!
Put your happy pants back on - April 2022 was before June 2022 if I remember correctly:-

https://www.prophesee.ai/2022/06/20/brainchip-partners-with-prophesee/

BrainChip Partners with Prophesee Optimizing Computer Vision AI Performance and Efficiency​


Laguna Hills, Calif. – June 14, 2022 – BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of neuromorphic AI IP, and Prophesee, the inventor of the world’s most advanced neuromorphic vision systems, today announced a technology partnership that delivers next-generation platforms for OEMs looking to integrate event-based vision systems with high levels of AI performance coupled with ultra-low power technologies.

Dear Dodgy-knees,

I just took my PJ's off and put my happy pants back on and I also took the cork back out of the champers just in case! Here are two extracts from an article dated Thursday 6 October 2022 which are leading me to think, hope and pray that iCatch may have incorporated Akida. If @Stable Genius is right when he said iCatch are "SOC designers so my understanding is they still needed to get their IP from somewhere", then where else would they be getting their IP that can perform all of the bits and bobs outlined in the two extracts below? See the link at the bottom of the post for the full article.

I mean, does Sony Semiconductor Solutions have its own AI Deep Learning Accelerator? Can it protect the driver's privacy, monitor their attentiveness and their health status through multi-sensor fusion and AI edge computing and even take control over the car when needed?

Screen Shot 2023-01-19 at 10.44.00 pm.png

Screen Shot 2023-01-19 at 10.45.35 pm.png


I don't want to get too excited. Heck, who am I kidding? I wan't to get REALLY, REALLY EXCITED!!!!! 🥳


 
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Sirod69

bavarian girl ;-)
don´t know, if we are involved? Thought it´s perhaps interesting for some of you?🙋‍♀️


DIYA SOUBRA

DIYA SOUBRA• 2.Market Entry Wizard at Arm - IoT, Edge Compute, Machine learning, Smart Home, Matter, Ambient AI, Digital Transformation


Apple released #Matter smart home hub

PRESS RELEASEJanuary 18, 2023

Apple introduces the new HomePod with breakthrough sound and intelligence​

Delivering incredible audio quality, enhanced Siri capabilities, and a safe and secure smart home experience

 
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Diogenese

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Hi Dio, luca told me back in October 2022 that the relationship between Prophesee & Brainchip started back in 2021…..despite the offical announcement in June 2022. View attachment 27512
Thanks Jesse,

I remember when you posted this now - the dendrites had not connected before.

Of course they would have been in contact befoe the announcement, so at least 6 monthe earlier.

Anil's comment in June 2022 was:
“We’ve successfully ported the data from Prophesee’s neuromorphic-based camera sensor to process inference on Akida with impressive performance,” said Anil Mankar, Co-Founder and CDO of BrainChip. “This combination of intelligent vision sensors with Akida’s ability to process data with unparalleled efficiency, precision and economy of energy at the point of acquisition truly advances state-of-the-art AI enablement and offers manufacturers a ready-to-implement solution.”

This reads like they had not actually soldered the Prophesee DVS to the Akida SoC, but had run a Prophesee DVS data file on Akida SoC, and the performance was "impressive".

Similarly, they would have been in contact with iChat for some time before.

https://www.prophesee.ai/2022/04/19/icatch-prophesee-collaboration-ai-vision-processor/

"Now iCatch has collaborated with Prophesee on Event-based Metavision sensing projects that integrated iCatch’s V57 AI vision processor with the new Sony Semiconductor Solutions (“SSS”) stacked Event-based Vision Sensor IMX636, realized in collaboration between SSS and Prophesee."

They had run the iCatch V57 AI chip with the Sony/Prophesee Event-based Vision Sensor IMX636. This would have entailed some physical circuit design to connect the processor to the DVs chip, so the start of cooperation between Prophesee and iChat would have pre-dated the Prophesee/BrainCHip hook-up.

So I checked on the iChat V57 AI processor which was used with Prophesee:
https://www.icatchtek.com/Upload/202207251104172758601.pdf

A group of CV (computer vision) engines which comprise of an optical flow processing (OPF) accelerator, matrix arithmetic engine (MAE) with DSP functions and high performance NPU engine, can manipulate the image and video data in real-time to support edge computing and intelligent processing, such as pedestrian detection, vechicle detection, distance extraction, behavior recognition, gesture recognition, or even action recognition, and much more. The embedded USB3.2 Gen1 device interface and support ultra high-speed and high-resolution video data transfer.

2.5. Neural network accelerator

  • High performance 1.2 TOPS NPU engine
  • Supports weight/bias quantization using UINT8, INT8, INT16,
    • Float16, BFloat16 and Post-training quantization
  • MAE engine – pre/post DSP accelerator
iChat are using 8-bit and 16-bit MAC, so several times slower and more power hungry than Akida.

As Luca Verre said:

"By combining our Metavision solution with Akida-based IP, we are better able to deliver a complete high-performance and ultra-low power solution to OEMs looking to leverage edge-based visual technologies as part of their product offerings, said Luca Verre, CEO and co-founder of Prophesee."
 
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Diogenese

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Dear Dodgy-knees,

I just took my PJ's off and put my happy pants back on and I also took the cork back out of the champers just in case! Here are two extracts from an article dated Thursday 6 October 2022 which are leading me to think, hope and pray that iCatch may have incorporated Akida. If @Stable Genius is right when he said iCatch are "SOC designers so my understanding is they still needed to get their IP from somewhere", then where else would they be getting their IP that can perform all of the bits and bobs outlined in the two extracts below? See the link at the bottom of the post for the full article.

I mean, does Sony Semiconductor Solutions have its own AI Deep Learning Accelerator? Can it protect the driver's privacy, monitor their attentiveness and their health status through multi-sensor fusion and AI edge computing and even take control over the car when needed?

View attachment 27513
View attachment 27514

I don't want to get too excited. Heck, who am I kidding? I wan't to get REALLY, REALLY EXCITED!!!!! 🥳


Hi Bravo,

By all means keep the champers flowing and keep your happy pants on, but I'm afraid @Stable Genius is leading you up the garden path.

iCatch have a very complex chip, the V57 AI processor (see above), which includes their proprietary NPU.

Unfortunately for them, they have used a design from the last millennium for their NPU.

Bottoms up!
1674131153697.png


PS: If iCatch have a contract with Sony, we may have to wait for the contract to expire, so drink slowly.
 
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