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If ARM was an arm, BRN would be its biceps💪!
How about now?Not yet. Sorry.
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Hope so….it’s got a cool name. Thor
What about this??? 
imago-technologies.com
The freely programmable embedded vision system works with a special sensor from the French manufacturer Prophesee, which emulates an extraordinary characteristic of human vision that has developed over the course of evolution: Our eye, or brain, is very sensitive to rapid changes, while the brain ignores an infinite amount of motionless data.
Prophesee’s Event-based Vision Sensor (EVS) works according to the same principle: each pixel on the chip has its own logic that allows it to detect changes in brightness and send detected event data to the evaluating computer autonomously, without the line or frame rate specified for conventional image sensors. The pixels themselves decide when an event is triggered and data is sent. As with human vision, this concept leads to considerably less data traffic and thus also to a lower transfer volume and shorter processing time. The sensor chip delivers up to 50 million events per second, significantly exceeding the speed of traditional image processing sensors, and is therefore also suitable for applications in which very fast movements have to be detected.
Smart Event Based Camera Vision Cam EB - imago-technologies
The event based camera Vision Cam EB revolutionizes machine vision. The camera only shows the changes in the scene. Click here for more information!
imago-technologies.com
Prophesee’s Event-based Vision Sensor (EVS) works according to the same principle: each pixel on the chip has its own logic that allows it to detect changes in brightness and send detected event data to the evaluating computer autonomously, without the line or frame rate specified for conventional image sensors. The pixels themselves decide when an event is triggered and data is sent. As with human vision, this concept leads to considerably less data traffic and thus also to a lower transfer volume and shorter processing time. The sensor chip delivers up to 50 million events per second, significantly exceeding the speed of traditional image processing sensors, and is therefore also suitable for applications in which very fast movements have to be detected.
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These researchers are very, very well researched because they have actually heard of AKIDA:
I. INTRODUCTION
Biometric authentication has a wide range of applications including human-machine interfaces, online banking, shopping, forensic testing, and crime investigation. Nowadays, iPhone's Siri, Google Assistant, Samsung's Bixby, and other smartphone assistants use audio biometric authentication. Recently, biometric authentication has been implemented on several neuromorphic systems such as TrueNorth (Modha, 2014), Loihi-Intel (Davies et al., 2018), and BrainChip's Akida (Turchin, 2019). These hardware implementations should expand applications of biometric authentication in mobile devices, cars, computers, and beyond.”
My opinion only DYOR
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AKIDA BALLISTA
“ABSTRACT
One challenging issue in speaker identification (SID) is to achieve noise-robust performance. Humans can accurately identify speakers, even in noisy environments. We can leverage our knowledge of the function and anatomy of the human auditory pathway to design SID systems that achieve better noise-robust performance than conventional approaches. We propose a text-dependent SID system based on a real-time cochlear model called cascade of asymmetric resonators with fast-acting compression (CARFAC). We investigate the SID performance of CARFAC on signals corrupted by noise of various types and levels. We compare its performance with conventional auditory feature generators including mel-frequency cepstrum coefficients, frequency domain linear predictions, as well as another biologically inspired model called the auditory nerve model. We show that CARFAC outperforms other approaches when signals are corrupted by noise. Our results are consistent across datasets, types and levels of noise, different speaking speeds, and back-end classifiers. We show that the noise-robust SID performance of CARFAC is largely due to its nonlinear processing of auditory input signals. Presumably, the human auditory system achieves noise-robust performance via inherent nonlinearities as well.I. INTRODUCTION
Biometric authentication has a wide range of applications including human-machine interfaces, online banking, shopping, forensic testing, and crime investigation. Nowadays, iPhone's Siri, Google Assistant, Samsung's Bixby, and other smartphone assistants use audio biometric authentication. Recently, biometric authentication has been implemented on several neuromorphic systems such as TrueNorth (Modha, 2014), Loihi-Intel (Davies et al., 2018), and BrainChip's Akida (Turchin, 2019). These hardware implementations should expand applications of biometric authentication in mobile devices, cars, computers, and beyond.”
My opinion only DYOR
FF
AKIDA BALLISTA
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I am most certainly feeling this one.What about this???
The freely programmable embedded vision system works with a special sensor from the French manufacturer Prophesee, which emulates an extraordinary characteristic of human vision that has developed over the course of evolution: Our eye, or brain, is very sensitive to rapid changes, while the brain ignores an infinite amount of motionless data.Smart Event Based Camera Vision Cam EB - imago-technologies
The event based camera Vision Cam EB revolutionizes machine vision. The camera only shows the changes in the scene. Click here for more information!
Prophesee’s Event-based Vision Sensor (EVS) works according to the same principle: each pixel on the chip has its own logic that allows it to detect changes in brightness and send detected event data to the evaluating computer autonomously, without the line or frame rate specified for conventional image sensors. The pixels themselves decide when an event is triggered and data is sent. As with human vision, this concept leads to considerably less data traffic and thus also to a lower transfer volume and shorter processing time. The sensor chip delivers up to 50 million events per second, significantly exceeding the speed of traditional image processing sensors, and is therefore also suitable for applications in which very fast movements have to be detected.
Can I add this last year and earlier this year Prophesee was using the following language “with Ai Algorithms on board” .
When you go to the following and read the final paragraph by Luca Verre you will see a substantial change in the language and of course a claim that fits perfectly with AKIDA IP now being incorporated. I have emboldened in red the words that in my opinion support this conclusion:
“PARIS – October 3, 2022 – The full extent of the power and accessibility of Prophesee’s advanced neuromorphic vision systems will be on display at the 2022 VISION show, with an array of technology showcases, partner demonstrations and live interactions that showcase the company’s breakthrough event-based vision approach to machine vision.
Prophesee will have in-depth product demonstrations at its Booth 8B29 at the premier industry event happening October 4-6 in Stuttgart, Germany. Prophesee will also deliver an overview of its event-based platform on Wednesday, 6 October at 12:20 (Hall 8 Booth C70), entitled “The World Between Frames; Event Camera Come of Age.”
Secure your private meeting today for in-depth insights from our experts: http://prophesee.ai/meet
Prophesee’s Metavision® platform has gained traction with leading developers of machine vision systems in industrial automation, robotics, automotive and IoT. Its event-based vision approach significantly reduces the amount of data needed to capture information. Among the benefits of the sensor and AI technology are ultra-low latency, robustness to challenging lighting conditions, energy efficiency, and low data rate.
The company’s breakthrough sensors, accompanying development tools, open-source algorithms and models are at the foundation of several announcements and demonstrations at the show, including:
- CENTURY ARKS: Century Arks announces it will release mid-October the SilkyEvCam HD, first commercial Event-based Vision camera featuring the IMX636MP sensor realized in collaboration between Sony and Prophesee.
- CIS: Prophesee announces collaboration with CIS, a leading machine vision provider, to build the first Event-Based 3D sensing evaluation platform, leveraging advanced VCSEL technology: https://www.prophesee.ai/2022/10/03/cis-prophesee-structured-light-evaluation-kit/
- Datalogic: A global technology leader in the automatic data capture and factory automation markets begins landmark partnership with Prophesee to bring the performance and efficiency of neuromorphic vision to its industrial products: https://www.prophesee.ai/2022/10/03/datalogic-prophesee-event-camera-partnership/
- Framos: A leading global supplier of imaging products, custom vision solutions and OEM services is releasing their brand new Event-Based Vision development kit based on NVIDIA Jetson Xavier, featuring IMX636 sensor realized in collaboration between Sony and Prophesee.
- Lucid Vision Labs: Following early prototype announcement at VISION 2021, Machine Vision leader Lucid announces commercial availability of its new Triton EVS, featuring the Prophesee Metavision sensor inside.
- MVTec: Prophesee and MVTec Partner to Support Integration of Prophesee Event-Based Metavision® Cameras with MVTec HALCON Machine Vision Software. https://www.prophesee.ai/2022/10/03/mvtec-prophesee-halcon-integration-partnership/
My opinion only DYOR
FF
AKIDA BALLISTA
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cosors
👀
I had yesterday a stupid and naive post regarding Akidas in parallel but already deleted again. Nevertheless, the thought does not let me go. The answers to my following questions can be found here somewhere but you know how it is. So I just dare to ask:
1.) How many Akidas can be connected in parallel, at least I assume that it is parallel.
2.) Why is the number limited?
3) I assume that the energy consumption cannot be the same no matter what is calculated. What is the maximum energy consumption per Akida if someone upscaled the full program?
My thought goes in the direction of an Akida cluster. So the maximum what goes. Like an Akida mainframe.
1.) How many Akidas can be connected in parallel, at least I assume that it is parallel.
2.) Why is the number limited?
3) I assume that the energy consumption cannot be the same no matter what is calculated. What is the maximum energy consumption per Akida if someone upscaled the full program?
My thought goes in the direction of an Akida cluster. So the maximum what goes. Like an Akida mainframe.
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What confuses me is the specification page which mentions the Prophesee camera but the processor specs stump me . When reading the camera general information page it clearly sounds like Akida
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Oh behave!Just getting ready for Monday guys.
Ahh yes … wonder if they have changed processors or if that camera is still sold
So it seems Prophesee isn’t with Imago technologies anymore as they are not listed there?? And Imago were also at that show.
I wonder if they installed their radar on the Ghost Bat (Loyal Wingman) drone the USAF just bought from RAAF/Boeing.I will let you draw your own conclusion as to how successful the Brainchip and ISL collaboration with the US Airforce Research Laboratory has been but in my opinion ‘Highly successful’ seems the likely answer.
A: The original Brainchip & ISL announcement as a memory refresh.
January 09, 2022 05:30 PM Eastern Standard Time
LAGUNA HILLS, Calif.--(BUSINESS WIRE)--BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), a leading provider of ultra-low power, high performance artificial intelligence technology and the world’s first commercial producer of neuromorphic AI chips and IP, today announced that Information Systems Laboratories, Inc. (ISL) is developing an AI-based radar research solution for the Air Force Research Laboratory (AFRL) based on its Akida™ neural networking processor
B: An Extract from ISL’s website advising that the CEO Dr. Joe Guerci will deliver a Keynote Address on recent radar advances.
IEEE International Microwave Symposium (IMS)
Denver, Colorado USA June 2022
ISL CEO Dr. Joe Guerci delivered a Keynote address on recent radar advances. In recent years, there has been a wide variety of technological advances that have either directly or indirectly impacted both the government and commercial radar industries. These include new radar architectures such as cognitive radar, and many key enabling technologies such as RF systems-on-a-chip, high performance embedded computing, machine learning/AI, and low cost, size weight and power RF subsystems. Concurrently, there has been significant technology pull from new applications in unmanned aerial systems (UAS), counter UAS (CUAS), space-borne radar, and commercial self-driving vehicles. In this talk, Dr. Guerci surveyed both the new emerging technology trends, and the applications for which they are finding a home.
C: The link to the slides used in his Keynote Address which I suggest reading through.
Click here for a link to the presentation slides
D: Slide number 7 extract which appears to relate directly to A. above.
7
Keynote
New Architectures: Cognitive Radar (cont.)
• Cognitive Fully Adaptive Radar (CoFAR) architecture
• Highly successful AFRL project has led to DoD follow-on and commercialization (new Digital Engineering tools)
My opinion only DYOR
FF
AKIDA BALLISTA
Fullmoonfever
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Appears recent news with Imago though?So it seems Prophesee isn’t with Imago technologies anymore as they are not listed there?? And Imago were also at that show.
Wonder if we were"onboard' on this one given our high speed counting
Vous avez cherché Imago | PROPHESEE
www.prophesee.ai
I am wondering why Edge Impulse is promoting this.
www.linkedin.com
Along with new camera hardware, the Tensor G2 AI brain in Google's Pixel 7 Pro phone helps you zoom, focus, unblur faces, and shoot in the dark. cc: CNET, Alexander Schiffhauer | Edge Impulse (a Qualcomm company)
Along with new camera hardware, the Tensor G2 AI brain in Google's Pixel 7 Pro phone helps you zoom, focus, unblur faces, and shoot in the dark. cc: CNET, Alexander Schiffhauer
FJ-215
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Hi all,
Loving the research and dots being put up. Got pinged by Bloomberg in the early hours this morning with a piece on everything that is wrong with self driving cars. Seems legacy computers aren't up to the job.
“You think the computer can see everything and can understand what’s going to happen next. But computers are still really dumb”
Says it all really.
Worth a read.
Even After $100 Billion, Self-Driving Cars Are Going Nowhere
'The first car woke Jennifer King at 2 a.m. with a loud, high‑pitched hum. “It sounded like a hovercraft,” she says, and that wasn’t the weird part. King lives on a dead-end street at the edge of the Presidio, a 1,500-acre park in San Francisco where through traffic isn’t a thing. Outside she saw a white Jaguar SUV backing out of her driveway. It had what looked like a giant fan on its roof—a laser sensor—and bore the logo of Google’s driverless car division, Waymo.
She was observing what looked like a glitch in the self-driving software: The car seemed to be using her property to execute a three-point turn. This would’ve been no biggie, she says, if it had happened once. But dozens of Google cars began doing the exact thing, many times, every single day.'
Loving the research and dots being put up. Got pinged by Bloomberg in the early hours this morning with a piece on everything that is wrong with self driving cars. Seems legacy computers aren't up to the job.
“You think the computer can see everything and can understand what’s going to happen next. But computers are still really dumb”
Says it all really.
Worth a read.
Even After $100 Billion, Self-Driving Cars Are Going Nowhere
'The first car woke Jennifer King at 2 a.m. with a loud, high‑pitched hum. “It sounded like a hovercraft,” she says, and that wasn’t the weird part. King lives on a dead-end street at the edge of the Presidio, a 1,500-acre park in San Francisco where through traffic isn’t a thing. Outside she saw a white Jaguar SUV backing out of her driveway. It had what looked like a giant fan on its roof—a laser sensor—and bore the logo of Google’s driverless car division, Waymo.
She was observing what looked like a glitch in the self-driving software: The car seemed to be using her property to execute a three-point turn. This would’ve been no biggie, she says, if it had happened once. But dozens of Google cars began doing the exact thing, many times, every single day.'
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Rob T liking this one
www.linkedin.com
#onarm #tinyml #embedded | Mary Bennion
Arm AI Ecosystem Partner Plumerai creates extremely small AND extremely accurate AI models that run #onarm—this is a great overview of how they do it—check it out! 👇👇 #tinyml #embedded
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Cause their really nice and want to give Google a leg up in the camera industry.I am wondering why Edge Impulse is promoting this.
Along with new camera hardware, the Tensor G2 AI brain in Google's Pixel 7 Pro phone helps you zoom, focus, unblur faces, and shoot in the dark. cc: CNET, Alexander Schiffhauer | Edge Impulse (a Qualcomm company)
Along with new camera hardware, the Tensor G2 AI brain in Google's Pixel 7 Pro phone helps you zoom, focus, unblur faces, and shoot in the dark. cc: CNET, Alexander Schiffhauer
Regards
FF
AKIDA BALLISTA
Rob T liking this one
#onarm #tinyml #embedded | Mary Bennion
Arm AI Ecosystem Partner Plumerai creates extremely small AND extremely accurate AI models that run #onarm—this is a great overview of how they do it—check it out! 👇👇 #tinyml #embedded
Hi @Zedjack33
What's the emoji for chagrin?
Zedjack33
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Zedjack33
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Mary doesn’t need to explain to us Australians what a TOSA is.
#tosa #ml #arm #standards | Mary Bennion
What in the world is #TOSA?? We will tell you next week! Registration below 👇👇👇 #ml #arm #standards
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