CrabmansFriend
Regular
I‘m patiently waiting for some Akida related announcement, fabricated in 7nm (Nandan mentioned this process node for an energy consumption example in an video/interview some time ago).
Hi Sirod,why 0, when will 1 + 1 come together?
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why 0, when will 1 + 1 come together?
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Nice to see ZF listed under the client / partner section like Brainchip.So, have we got an offshoot, rebranding, part the restructure process on NVISO?
BeEmotion.ai.
I thought the layout, images and graphics looked similar when I looked at their homepage initially and digging deeper find some of what I snipped below.
When I scrolled to the bottom of the page I can see the site managed by Tropus here in Perth. I know exactly where their office is as drive past it for certain client meetings.
There is also a small Japanese link at the bottom which takes you to the Japanese site.
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BeEmotion
beemotion.ai
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BeEmotion
beemotion.ai
View attachment 53840
HUMAN BEHAVIOUR AI
NEUROMORPHIC COMPUTING
BeEmotion empowers system integrators to build AI-driven human machine interfaces to transform our lives using neuromorphic computing. Understand people and their behavior in real-time without an internet connection to make autonomous devices safe, secure, and personalized for humans.
NEUROMORPHIC COMPUTING INTEROPERABILITY
ULTRA-LOW LATENCY WITH LOW POWER
ULTRA-LOW LATENCY (<1MS)
Total BeEmotion Neuro Model latency is similar for GPU and BrainChip Akida™ neuromorphic processor (300 MHz), however CPU latency is approximately 2.4x slower. All models on all platforms can achieve <10ms latency and the best model can achieve 0.6ms which is almost 2x times faster than a GPU. On a clock frequency normalization basis, this represents an acceleration of 6x.
HIGH THROUGHPUT (>1000 FPS)
BeEmotion Neuro Model performance can be accelerated by an average of 3.67x using BrainChip Akida™ neuromorphic processor at 300MHz over a single core ARM Cortex A57 as found in a NVIDIA Jetson Nano (4GB) running at close to 5x the clock frequency. On a clock frequency normalization basis, this represents an acceleration of 18.1x.
SMALL STORAGE (<1MB)
BeEmotion Neuro Models can achieve a model storage size under 1MB targeting ultra-low power MCU system where onboard flash memory is limited. Removing the need for external flash memory saves cost and power. BrainChip Akida™ format uses 4-bit quantisation where ONNX format uses Float32 format.
DESIGNED FOR EDGE COMPUTING
NO CLOUD REQUIRED
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PRIVACY PRESERVING
By processing video and audio sensor data locally it does not have to be sent over a network to remote servers for processing. This improves data security and privacy as it can perform all processing disconnected from the central server, which is a more secure and private architecture decreasing security risks
This is a great endorsement of Akida!So, have we got an offshoot, rebranding, part the restructure process on NVISO?
BeEmotion.ai.
I thought the layout, images and graphics looked similar when I looked at their homepage initially and digging deeper find some of what I snipped below.
When I scrolled to the bottom of the page I can see the site managed by Tropus here in Perth. I know exactly where their office is as drive past it for certain client meetings.
There is also a small Japanese link at the bottom which takes you to the Japanese site.
![]()
BeEmotion
beemotion.ai
![]()
BeEmotion
beemotion.ai
View attachment 53840
HUMAN BEHAVIOUR AI
NEUROMORPHIC COMPUTING
BeEmotion empowers system integrators to build AI-driven human machine interfaces to transform our lives using neuromorphic computing. Understand people and their behavior in real-time without an internet connection to make autonomous devices safe, secure, and personalized for humans.
NEUROMORPHIC COMPUTING INTEROPERABILITY
ULTRA-LOW LATENCY WITH LOW POWER
ULTRA-LOW LATENCY (<1MS)
Total BeEmotion Neuro Model latency is similar for GPU and BrainChip Akida™ neuromorphic processor (300 MHz), however CPU latency is approximately 2.4x slower. All models on all platforms can achieve <10ms latency and the best model can achieve 0.6ms which is almost 2x times faster than a GPU. On a clock frequency normalization basis, this represents an acceleration of 6x.
HIGH THROUGHPUT (>1000 FPS)
BeEmotion Neuro Model performance can be accelerated by an average of 3.67x using BrainChip Akida™ neuromorphic processor at 300MHz over a single core ARM Cortex A57 as found in a NVIDIA Jetson Nano (4GB) running at close to 5x the clock frequency. On a clock frequency normalization basis, this represents an acceleration of 18.1x.
SMALL STORAGE (<1MB)
BeEmotion Neuro Models can achieve a model storage size under 1MB targeting ultra-low power MCU system where onboard flash memory is limited. Removing the need for external flash memory saves cost and power. BrainChip Akida™ format uses 4-bit quantisation where ONNX format uses Float32 format.
DESIGNED FOR EDGE COMPUTING
NO CLOUD REQUIRED
![]()
![]()
PRIVACY PRESERVING
By processing video and audio sensor data locally it does not have to be sent over a network to remote servers for processing. This improves data security and privacy as it can perform all processing disconnected from the central server, which is a more secure and private architecture decreasing security risks
Good point.This is a great endorsement of Akida!
... and BeEmotion will need to do a lot of brand recognition work and it looks like we will be dragged along with their coattails. They need us to show the benefits of their product.
So nViso must have lost out on the trade mark front to the security software mob. Maybe they thought using lower case with the capital V was sufficient to distinguish them, but, apart from being a feeble point of difference, it doesn't help phonetically.
So, have we got an offshoot, rebranding, part the restructure process on NVISO?
BeEmotion.ai.
I thought the layout, images and graphics looked similar when I looked at their homepage initially and digging deeper find some of what I snipped below.
When I scrolled to the bottom of the page I can see the site managed by Tropus here in Perth. I know exactly where their office is as drive past it for certain client meetings.
There is also a small Japanese link at the bottom which takes you to the Japanese site.
![]()
BeEmotion
beemotion.ai
![]()
BeEmotion
beemotion.ai
View attachment 53840
HUMAN BEHAVIOUR AI
NEUROMORPHIC COMPUTING
BeEmotion empowers system integrators to build AI-driven human machine interfaces to transform our lives using neuromorphic computing. Understand people and their behavior in real-time without an internet connection to make autonomous devices safe, secure, and personalized for humans.
NEUROMORPHIC COMPUTING INTEROPERABILITY
ULTRA-LOW LATENCY WITH LOW POWER
ULTRA-LOW LATENCY (<1MS)
Total BeEmotion Neuro Model latency is similar for GPU and BrainChip Akida™ neuromorphic processor (300 MHz), however CPU latency is approximately 2.4x slower. All models on all platforms can achieve <10ms latency and the best model can achieve 0.6ms which is almost 2x times faster than a GPU. On a clock frequency normalization basis, this represents an acceleration of 6x.
HIGH THROUGHPUT (>1000 FPS)
BeEmotion Neuro Model performance can be accelerated by an average of 3.67x using BrainChip Akida™ neuromorphic processor at 300MHz over a single core ARM Cortex A57 as found in a NVIDIA Jetson Nano (4GB) running at close to 5x the clock frequency. On a clock frequency normalization basis, this represents an acceleration of 18.1x.
SMALL STORAGE (<1MB)
BeEmotion Neuro Models can achieve a model storage size under 1MB targeting ultra-low power MCU system where onboard flash memory is limited. Removing the need for external flash memory saves cost and power. BrainChip Akida™ format uses 4-bit quantisation where ONNX format uses Float32 format.
DESIGNED FOR EDGE COMPUTING
NO CLOUD REQUIRED
![]()
![]()
PRIVACY PRESERVING
By processing video and audio sensor data locally it does not have to be sent over a network to remote servers for processing. This improves data security and privacy as it can perform all processing disconnected from the central server, which is a more secure and private architecture decreasing security risks
So nViso must have lost out on the trade mark front to the security software mob. Maybe they thought using lower case with the capital V was sufficient to distinguish them, but, apart from being a feeble point of difference, it doesn't help phonetically.
Let me confuse you even more:
As you will surely recall, sometimes 2 x 3 equals 4 and 3 x 3 = 6!
Yes but Renesas has an ip licence so the can factor Akida in as they already have akida and akida is compatible with m85. So 1 +1= $Hi Sirod,
The Akida family are all compatible with ARM's M85, but they are not part of M85. Thay are optional extras.
Helium is basically ARM in-house software for machine learning and digital signal processing.
https://www.arm.com/products/silicon-ip-cpu/cortex-m/cortex-m85
Arm Cortex-M85 is the highest performing Cortex-M processor with Arm Helium technology and provides the natural upgrade path for Cortex-M based applications that require significantly higher performance and increased security.
Renesas has said that they will use their in-house DRP-AI for "heavy" AI loads, and Akida will be used for simple AI tasks. It would be surprising if Renesas were to produce the high performance M85 with only 2 nodes of Akida.
Brainchip has said that they are unable to say when the Renesas processor incorporating Akida will be produced. That is entirely within the control of Renesas.
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SynSense and iniVation announce strategic partnership for next-gen intelligent eye tracking. | iniVation
SynSense and iniVation announce strategic partnership for next-gen intelligent eye tracking. SynSense the leader in ultra-low-power neuromorphic processing, has teamed up with iniVation, the neuromorphic vision market leader, to build next-generation low-power, high speed eye tracking devices...www.linkedin.com
inivation working with Synsense. CES 24 is looking a bit sad for us, nothing about Merc, Renesas or Prophesee . Hopefully our new head of sales can make some inroads..