BRN Discussion Ongoing

[chapman89]

So NVISO has partnered with Siemens Healthineers, now if you read the NVISO white paper and how much NVISO loves Brainchip, I think they’re a bigger fan of Brainchip than most out there, so I would say, in my honest opinion that NVISO has gone to Panasonic and Siemens and showed them akida running in their software!

Here’s the link-

NVISO collaborates with Siemens Healthineers to apply Human Behaviour AI in medical imaging applications

NVISO Human Behavioural Analytics AI software solution to support Siemens Healthineers solutions in developing new intelligent applications

www.nviso.ai

 

[chapman89]

So NVISO has partnered with Siemens Healthineers, now if you read the NVISO white paper and how much NVISO loves Brainchip, I think they’re a bigger fan of Brainchip than most out there, so I would say, in my honest opinion that NVISO has gone to Panasonic and Siemens and showed them akida running in their software!

Here’s the link-

NVISO collaborates with Siemens Healthineers to apply Human Behaviour AI in medical imaging applications

NVISO Human Behavioural Analytics AI software solution to support Siemens Healthineers solutions in developing new intelligent applications

www.nviso.ai

 

[Fact Finder]

PRESS RELEASE​

NVISO collaborates with Siemens Healthineers to apply Human Behaviour AI in medical imaging applications​

16th June, 2022​

​

Lausanne, Switzerland – June 16th, 2022 – – nViso SA (NVISO), the leading Human Behavioural Analytics AI company, is pleased to announce it has commenced a commercial pilot applying the NVISO Human Behavioural Analytics AI software solution to support Siemens Healthineers solutions in developing new intelligent applications. Initially the collaboration includes the deployment of real-time deep learning-based AI Apps for face detection, head pose recognition, facial recognition, and emotion recognition within a trial environment. These AI Apps are specifically designed for resource constrained hardware requiring low-power and low-memory footprints deployed at the edge without requiring an internet connection.
“We at Siemens Healthineers are convinced that patient experience will become the key differentiator in the medical device industry by creating greater clinical and operational customer value.” said Carsten Thierfelder of Siemens Healthineers “In this context, next generation man-machine-communication based on AI technologies will help interpreting patient emotions at various touchpoints and thus avoid unpleasant moments throughout their journey. Our latest collaboration activities with NVISO are already showing promising results in this space”.
Within the healthcare sector there are a growing number of use cases for AI technology in improving Health Assessment and Screening, Patient Monitoring and Workflow Automation Support to help deliver both improved patient outcomes and efficiencies within the healthcare system. Driven by the ever increasing costs in the healthcare system and the need for more resource efficient and decentralised delivery processes along with rapidly aging populations, this is achieved through using visual comprehension and NVISO’s human behavioural analytics AI running at the edge as a private, secure and noninvasive system supporting today's healthcare challenges.
- Health Assessment and Screening: Real-time health assessments and screening can assist medical staff and care assistants in both prevention and treatment of conditions and the best allocation of resources. Using AI powered visual observation for measurement of vital signs, and advanced emotions including the assessment of levels of mood, stress, fatigue and anxiety, information can be gathered to assist in decision making leading to improved patient outcomes with optimal resource utilization.
- Patient Monitoring: Monitoring of patients throughout their care experience integrated with hospital information systems, can lead to safer, more secure, and improved patient centric experiences with efficiency and better outcomes. Highly accurate biometrics analysis helps in reliable identification of delirious patients to ensure patient security throughout the treatment journey along with the observation of vital signs, management of stress and anxiety when under treatment and observation of overall mood. Further, observations of body movement, postures, extremity movements, and head pose variations can help identify medical conditions along with emergencies such as collapse or complications in post-operative recovery.
- Workflow Automation Support: Monitoring of both patient and staff identities and activities throughout the patient journey can lead to significantly improved outcomes and efficiencies as well as enhancing security. AI enables patient emotional profiling to address various challenges in communication and medical procedures including the onset of severe fatigue by medical staff and patient confusion and comprehension. AI can be used to monitor facilities and objects, for example to ensure the correct sterilisation process and tool preparation have been followed, correct patient positioning for automated processes has been made, and potential contamination sources identified (e.g., where touch has taken place).
NVISO’s solutions deliver on these use cases through its range of AI Apps providing visual observation, perception and semantic reasoning capabilities, the results of which can be used in identifying issues, in decision making processes and in supporting autonomous “human like” interactions. Examples of these AI Apps provide the analysis of core signals of human behaviour such as body movements, extremity movements, facial expressions, advanced emotions, identity, head pose variations, gaze, gestures, activities, and the identification of objects with which users interact. These AI Apps can be optimised for typically resource constrained low power and low memory processing platforms deployed on the edge without requiring an internet connection. Furthermore, NVISO AI Apps can be easily configured to suit any camera system for optimal performance in terms of distance and camera angle, and thanks to NVISO’s large scale proprietary human behaviour databases NVISO’s AI Apps are robust to the imaging conditions often found in real world deployments. Unlike cloud-based solutions, NVISO’s solutions do not require information to be sent off-device for processing elsewhere so user privacy and safety can be protected.
"Over the last year we have worked with Siemens Healthineers’ team to develop concepts to provide new solutions supporting a variety of use cases within the healthcare environment. Our engineering team has delivered an excellent AI solution for fast customer setup with deployment within the demanding environment of medical imaging applications where continuous assessment and monitoring of patients along with workflow support is required”, said Tim Llewellynn, CEO of NVISO, “Deployment of this technology can provide significant improvement in the target use cases leading to improvement in both patient outcomes and workflow efficiency. For several years, we have been investing in partnerships to integrate our AI Apps into deep learning accelerated hardware enabling breakthrough capabilities which is now starting to bear fruits. This commercial pilot provides additional evidence for the strong industry demand we are experiencing for the integration of advanced Human Behavioural Analytics technology into extreme edge-based systems for a wide range of applications ranging from consumer products through to medical devices and autonomous and connected automotive systems".

View attachment 9499

 

[TechGirl]

Not a bad Statement

"Our latest collaboration activities with NVISO are already showing promising results in this space"

I believe Rob Telson said once that in medical devices or the medical field we are actually dominating.......hmmmm...

 

[Fullmoonfever]

PRESS RELEASE​

NVISO collaborates with Siemens Healthineers to apply Human Behaviour AI in medical imaging applications​

16th June, 2022​

​

Lausanne, Switzerland – June 16th, 2022 – – nViso SA (NVISO), the leading Human Behavioural Analytics AI company, is pleased to announce it has commenced a commercial pilot applying the NVISO Human Behavioural Analytics AI software solution to support Siemens Healthineers solutions in developing new intelligent applications. Initially the collaboration includes the deployment of real-time deep learning-based AI Apps for face detection, head pose recognition, facial recognition, and emotion recognition within a trial environment. These AI Apps are specifically designed for resource constrained hardware requiring low-power and low-memory footprints deployed at the edge without requiring an internet connection.
“We at Siemens Healthineers are convinced that patient experience will become the key differentiator in the medical device industry by creating greater clinical and operational customer value.” said Carsten Thierfelder of Siemens Healthineers “In this context, next generation man-machine-communication based on AI technologies will help interpreting patient emotions at various touchpoints and thus avoid unpleasant moments throughout their journey. Our latest collaboration activities with NVISO are already showing promising results in this space”.
Within the healthcare sector there are a growing number of use cases for AI technology in improving Health Assessment and Screening, Patient Monitoring and Workflow Automation Support to help deliver both improved patient outcomes and efficiencies within the healthcare system. Driven by the ever increasing costs in the healthcare system and the need for more resource efficient and decentralised delivery processes along with rapidly aging populations, this is achieved through using visual comprehension and NVISO’s human behavioural analytics AI running at the edge as a private, secure and noninvasive system supporting today's healthcare challenges.
- Health Assessment and Screening: Real-time health assessments and screening can assist medical staff and care assistants in both prevention and treatment of conditions and the best allocation of resources. Using AI powered visual observation for measurement of vital signs, and advanced emotions including the assessment of levels of mood, stress, fatigue and anxiety, information can be gathered to assist in decision making leading to improved patient outcomes with optimal resource utilization.
- Patient Monitoring: Monitoring of patients throughout their care experience integrated with hospital information systems, can lead to safer, more secure, and improved patient centric experiences with efficiency and better outcomes. Highly accurate biometrics analysis helps in reliable identification of delirious patients to ensure patient security throughout the treatment journey along with the observation of vital signs, management of stress and anxiety when under treatment and observation of overall mood. Further, observations of body movement, postures, extremity movements, and head pose variations can help identify medical conditions along with emergencies such as collapse or complications in post-operative recovery.
- Workflow Automation Support: Monitoring of both patient and staff identities and activities throughout the patient journey can lead to significantly improved outcomes and efficiencies as well as enhancing security. AI enables patient emotional profiling to address various challenges in communication and medical procedures including the onset of severe fatigue by medical staff and patient confusion and comprehension. AI can be used to monitor facilities and objects, for example to ensure the correct sterilisation process and tool preparation have been followed, correct patient positioning for automated processes has been made, and potential contamination sources identified (e.g., where touch has taken place).
NVISO’s solutions deliver on these use cases through its range of AI Apps providing visual observation, perception and semantic reasoning capabilities, the results of which can be used in identifying issues, in decision making processes and in supporting autonomous “human like” interactions. Examples of these AI Apps provide the analysis of core signals of human behaviour such as body movements, extremity movements, facial expressions, advanced emotions, identity, head pose variations, gaze, gestures, activities, and the identification of objects with which users interact. These AI Apps can be optimised for typically resource constrained low power and low memory processing platforms deployed on the edge without requiring an internet connection. Furthermore, NVISO AI Apps can be easily configured to suit any camera system for optimal performance in terms of distance and camera angle, and thanks to NVISO’s large scale proprietary human behaviour databases NVISO’s AI Apps are robust to the imaging conditions often found in real world deployments. Unlike cloud-based solutions, NVISO’s solutions do not require information to be sent off-device for processing elsewhere so user privacy and safety can be protected.
"Over the last year we have worked with Siemens Healthineers’ team to develop concepts to provide new solutions supporting a variety of use cases within the healthcare environment. Our engineering team has delivered an excellent AI solution for fast customer setup with deployment within the demanding environment of medical imaging applications where continuous assessment and monitoring of patients along with workflow support is required”, said Tim Llewellynn, CEO of NVISO, “Deployment of this technology can provide significant improvement in the target use cases leading to improvement in both patient outcomes and workflow efficiency. For several years, we have been investing in partnerships to integrate our AI Apps into deep learning accelerated hardware enabling breakthrough capabilities which is now starting to bear fruits. This commercial pilot provides additional evidence for the strong industry demand we are experiencing for the integration of advanced Human Behavioural Analytics technology into extreme edge-based systems for a wide range of applications ranging from consumer products through to medical devices and autonomous and connected automotive systems".

Particularly liked this bit

These AI Apps are specifically designed for resource constrained hardware requiring low-power and low-memory footprints deployed at the edge without requiring an internet connection.

 

[BaconLover]

So NVISO has partnered with Siemens Healthineers, now if you read the NVISO white paper and how much NVISO loves Brainchip, I think they’re a bigger fan of Brainchip than most out there, so I would say, in my honest opinion that NVISO has gone to Panasonic and Siemens and showed them akida running in their software!

Here’s the link-

NVISO collaborates with Siemens Healthineers to apply Human Behaviour AI in medical imaging applications

NVISO Human Behavioural Analytics AI software solution to support Siemens Healthineers solutions in developing new intelligent applications

www.nviso.ai

This is HUGE. Pretty sure we have made some sort of dot joining with Siemens so if NVISO is partnering with them, whoa..... I think we will see a few more of these ''partnerships'' from ARM, NVISO, SiFive, MOSCHIPS etc.

Partnerships + Ecosystems = Royalties.

 

[chapman89]

From the NVISO white paper-

“SMART HEALTH
HUMAN-CENTRIC EXPERIENCES
NO CLOUD​

Data will play an increasingly important role in providing a better understanding of consumer needs in terms of health, and to enhance and tailor a more cost-efficient health offering that delivers the right care at the right time and in the right place. The interconnections made possible by being able to access pools of data not previously available (worldwide databases, data clouds, apps, in-sensor computing etc) are creating a major shift in healthcare provision.
According to different projections, healthcare budgets around the world are expected to increase by 10% in aggregate by 2030. Healthcare spending will be driven by ageing and growing populations, rising labour costs, and also by clinical and technology advances. Consequently, by 2030 healthcare is expected to be centered on patients being empowered to prevent disease rather than seek treatment.
Healthcare budgets in Europe will therefore shift towards novel areas such as digital health and more advanced prevention and rehabilitation options, for which homecare will play a key role. Money is expected to be redirected toward personalised medicine for the most complex diseases, and preventive, early stage treatments. This split is likely to lead to significant changes and require new R&D strategies for many industry players.

USE CASES
FOR EXTREME EDGE AI​

REMOTE VITAL SIGN MONITORING​

Non-invasive observational sensors (for heart rated, breathing frequency, movement patterns, etc) are important components in many medical applications. However, a cloud-based implementation of the sensing would be too slow in time critical contexts. This is not the only problem of cloud systems as storing generated data in them is also a privacy concern. Issues of latency and privacy can be solved by using edge AI”

 

[Pappagallo]

I present you with... 2 opportunities to LOL.

View attachment 9493



View attachment 9494

King of the WANCAs that bloke.

Love how he brings up our 4 cent SP from over two years ago without acknowledging ANY of our achievements since and the subsequent derisking of the company. Validation of the physical silicon, IP deals, millions in the bank, partnerships with big tech, a concept car from one of the famous automotive brands in the world, on the cusp of literally going into space, none of it rates a mention! Honestly I just SMDH at the fact that this shareman-tier analysis makes the cut at the AFR these days.

 

[chapman89]

Is there any German investors in this forum that attended the presentation in Germany to the Brainchip shareholders from the CEO of NVISO?
I believe the webinar is being set up for us here.

 

[Fact Finder]

Particularly liked this bit

These AI Apps are specifically designed for resource constrained hardware requiring low-power and low-memory footprints deployed at the edge without requiring an internet connection.

I like this statement as well:

“Driven by the ever increasing costs in the healthcare system and the need for more resource efficient and decentralised delivery processes along with rapidly aging populations, this is achieved through using visual comprehension and NVISO’s human behavioural analytics AI running at the edge as a private, secure and noninvasive system supporting today's healthcare challenges.”

FF

AKIDA BALLISTA

 

[Fact Finder]

King of the WANCAs that bloke.

Love how he brings up our 4 cent SP from over two years ago without acknowledging ANY of our achievements since and the subsequent derisking of the company. Validation of the physical silicon, IP deals, millions in the bank, partnerships with big tech, a concept car from one of the famous automotive brands in the world, on the cusp of literally going into space, none of it rates a mention! Honestly I just SMDH at the fact that this shareman-tier analysis makes the cut at the AFR these days.

Great post.

FF

AKIDA BALLISTA

 

[miaeffect]

I like this statement as well:

“Driven by the ever increasing costs in the healthcare system and the need for more resource efficient and decentralised delivery processes along with rapidly aging populations, this is achieved through using visual comprehension and NVISO’s human behavioural analytics AI running at the edge as a private, secure and noninvasive system supporting today's healthcare challenges.”

FF

AKIDA BALLISTA

For several years, we have been investing in partnerships to integrate our AI Apps into deep learning accelerated hardware enabling breakthrough capabilities which is now starting to bear fruits.

 

[jtardif999]

I must add, the camera security company he talked about (a well known company, in his words) he said "is building security cameras and they wanted Edge applications so they get notification when someone appears at the front with a black mask"

That sounds like a perfect fit of our use case.
Does this mean we're already in this particular product which is coming to the market as we speak!?
Time to search for security cameras with Edge functionality

Also said the camera is battery powered - hint hint,.. couldn’t be us (I say with sarcasm intended)

 

[Fact Finder]

From the NVISO white paper-

“SMART HEALTH​

HUMAN-CENTRIC EXPERIENCES​

NO CLOUD​

Data will play an increasingly important role in providing a better understanding of consumer needs in terms of health, and to enhance and tailor a more cost-efficient health offering that delivers the right care at the right time and in the right place. The interconnections made possible by being able to access pools of data not previously available (worldwide databases, data clouds, apps, in-sensor computing etc) are creating a major shift in healthcare provision.
According to different projections, healthcare budgets around the world are expected to increase by 10% in aggregate by 2030. Healthcare spending will be driven by ageing and growing populations, rising labour costs, and also by clinical and technology advances. Consequently, by 2030 healthcare is expected to be centered on patients being empowered to prevent disease rather than seek treatment.
Healthcare budgets in Europe will therefore shift towards novel areas such as digital health and more advanced prevention and rehabilitation options, for which homecare will play a key role. Money is expected to be redirected toward personalised medicine for the most complex diseases, and preventive, early stage treatments. This split is likely to lead to significant changes and require new R&D strategies for many industry players.

USE CASES​

FOR EXTREME EDGE AI​

REMOTE VITAL SIGN MONITORING​

Non-invasive observational sensors (for heart rated, breathing frequency, movement patterns, etc) are important components in many medical applications. However, a cloud-based implementation of the sensing would be too slow in time critical contexts. This is not the only problem of cloud systems as storing generated data in them is also a privacy concern. Issues of latency and privacy can be solved by using edge AI”

It is like a jigsaw puzzle where the pieces just keep magically appearing:

“ However, a cloud-based implementation of the sensing would be too slow in time critical contexts”

I think we have stumbled onto another one of those existential truths from Tim Llewellyn at the demo of Nviso using AKIDA when he said that AKIDA was the only chip powerful enough to run all the Nviso Apps.

RUNNING A PROCESS OF ELIMINATION OVER A LIST OF ONE POSSIBLE SOLUTION THE ANSWER IS OBVIOUS.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Diogenese]

PRESS RELEASE​

NVISO collaborates with Siemens Healthineers to apply Human Behaviour AI in medical imaging applications​

16th June, 2022​

​

Lausanne, Switzerland – June 16th, 2022 – – nViso SA (NVISO), the leading Human Behavioural Analytics AI company, is pleased to announce it has commenced a commercial pilot applying the NVISO Human Behavioural Analytics AI software solution to support Siemens Healthineers solutions in developing new intelligent applications. Initially the collaboration includes the deployment of real-time deep learning-based AI Apps for face detection, head pose recognition, facial recognition, and emotion recognition within a trial environment. These AI Apps are specifically designed for resource constrained hardware requiring low-power and low-memory footprints deployed at the edge without requiring an internet connection.
“We at Siemens Healthineers are convinced that patient experience will become the key differentiator in the medical device industry by creating greater clinical and operational customer value.” said Carsten Thierfelder of Siemens Healthineers “In this context, next generation man-machine-communication based on AI technologies will help interpreting patient emotions at various touchpoints and thus avoid unpleasant moments throughout their journey. Our latest collaboration activities with NVISO are already showing promising results in this space”.
Within the healthcare sector there are a growing number of use cases for AI technology in improving Health Assessment and Screening, Patient Monitoring and Workflow Automation Support to help deliver both improved patient outcomes and efficiencies within the healthcare system. Driven by the ever increasing costs in the healthcare system and the need for more resource efficient and decentralised delivery processes along with rapidly aging populations, this is achieved through using visual comprehension and NVISO’s human behavioural analytics AI running at the edge as a private, secure and noninvasive system supporting today's healthcare challenges.
- Health Assessment and Screening: Real-time health assessments and screening can assist medical staff and care assistants in both prevention and treatment of conditions and the best allocation of resources. Using AI powered visual observation for measurement of vital signs, and advanced emotions including the assessment of levels of mood, stress, fatigue and anxiety, information can be gathered to assist in decision making leading to improved patient outcomes with optimal resource utilization.
- Patient Monitoring: Monitoring of patients throughout their care experience integrated with hospital information systems, can lead to safer, more secure, and improved patient centric experiences with efficiency and better outcomes. Highly accurate biometrics analysis helps in reliable identification of delirious patients to ensure patient security throughout the treatment journey along with the observation of vital signs, management of stress and anxiety when under treatment and observation of overall mood. Further, observations of body movement, postures, extremity movements, and head pose variations can help identify medical conditions along with emergencies such as collapse or complications in post-operative recovery.
- Workflow Automation Support: Monitoring of both patient and staff identities and activities throughout the patient journey can lead to significantly improved outcomes and efficiencies as well as enhancing security. AI enables patient emotional profiling to address various challenges in communication and medical procedures including the onset of severe fatigue by medical staff and patient confusion and comprehension. AI can be used to monitor facilities and objects, for example to ensure the correct sterilisation process and tool preparation have been followed, correct patient positioning for automated processes has been made, and potential contamination sources identified (e.g., where touch has taken place).
NVISO’s solutions deliver on these use cases through its range of AI Apps providing visual observation, perception and semantic reasoning capabilities, the results of which can be used in identifying issues, in decision making processes and in supporting autonomous “human like” interactions. Examples of these AI Apps provide the analysis of core signals of human behaviour such as body movements, extremity movements, facial expressions, advanced emotions, identity, head pose variations, gaze, gestures, activities, and the identification of objects with which users interact. These AI Apps can be optimised for typically resource constrained low power and low memory processing platforms deployed on the edge without requiring an internet connection. Furthermore, NVISO AI Apps can be easily configured to suit any camera system for optimal performance in terms of distance and camera angle, and thanks to NVISO’s large scale proprietary human behaviour databases NVISO’s AI Apps are robust to the imaging conditions often found in real world deployments. Unlike cloud-based solutions, NVISO’s solutions do not require information to be sent off-device for processing elsewhere so user privacy and safety can be protected.
"Over the last year we have worked with Siemens Healthineers’ team to develop concepts to provide new solutions supporting a variety of use cases within the healthcare environment. Our engineering team has delivered an excellent AI solution for fast customer setup with deployment within the demanding environment of medical imaging applications where continuous assessment and monitoring of patients along with workflow support is required”, said Tim Llewellynn, CEO of NVISO, “Deployment of this technology can provide significant improvement in the target use cases leading to improvement in both patient outcomes and workflow efficiency. For several years, we have been investing in partnerships to integrate our AI Apps into deep learning accelerated hardware enabling breakthrough capabilities which is now starting to bear fruits. This commercial pilot provides additional evidence for the strong industry demand we are experiencing for the integration of advanced Human Behavioural Analytics technology into extreme edge-based systems for a wide range of applications ranging from consumer products through to medical devices and autonomous and connected automotive systems".

Lots of places where you can slot Akida in:

These AI Apps can be optimised for typically resource constrained low power and low memory processing platforms deployed on the edge without requiring an internet connection.


https://www.nviso.ai/en/technology

also, inter alia, Nvidia

https://www.nviso.ai/en/technology
How does it work? NVISO’s visual intelligence technology uses computers to learn from examples opposed to being manually programmed. Using deep Convolutional Neural Networks (CNNs) and state-of-the-art machine learning to understand human behaviors depicted in images and videos, it can achieve accuracy levels that surpass human performance in many narrowly defined tasks.

CNNs and modern machine learning scale to learn from billions of examples resulting in an extraordinary capacity to learn highly complex behaviors and thousands of categories. Thanks to high volumes of data and powerful computing resources, NVISO intelligence technology can train powerful and highly accurate models.

...

NVISO's technology is purpose built for a new class of ultra-efficient machine learning processors for smart edge devices and edge compute with heterogeneous and secure architecture. Supporting a wide range of heterogenous computing platforms ranging from CPU, GPU, NPU, and Neuromorphic computing it reduces the high barriers-to-entry into the AI space through cost-effective standardized AI Apps that are future proof and work optimally at the extreme edge (low power, on-device, without requiring an internet connection).

• Support a wide range of activations and weights data types (32-bit floating point to 2-bit binary).
• Mixed precision and unstructured sparsity to reduce memory bandwidth and power consumption.
• Support for both advanced NN architectures such as RNN, transformers (self-attention), 3D convolution as well as fully sequential architectures for ultra-low power mixed signal inference engines.

We hooked up with nviso in mid-April this year, so they had already been working with Siemens for several months:

"Over the last year we have worked with Siemens Healthineers’ team to develop concepts to provide new solutions supporting a variety of use cases within the healthcare environment.

... but, and this is a very big butt, this announcement is dated 16 June 2022 or there abouts. Obviously, nviso would have been playing with Akida/Meta-TF for some time before the April 2022 agreement with Brainchip, so it is entirely possible that Akida helped clinch the commercial pilot deal between nviso and Siemens.

 

[Labsy]

Not sure what you are implying here.

The post reads ''Stellantis has chosen our third-generation LIDAR..................''

Now in this instance Valeo is stating that Stellantis has chosen their tech - they have not revealed too much technical details, so they possibly have NDA in place too.

Brainchip openly mentioned Valeo via ASX Announcement a couple of years ago, not sure how much more open the company can be when declaring a client relationship.

NDA is important.

A silly example - those who eat KFC, do you know what is in it? Apparently there are 18 ingredients which not many know, because that's their secret recipe. Don't think those who handle it are going to share it with every person just because they want to know.
It is their moat, which they won't give it away.

I bet akida could identify those 18 secret ingredients in a second

 

[TheFunkMachine]

No what I am suggesting is that Tony Dawe and hence Brainchip have adopted Jesse’s post and as such can be seen as recommending his views as an accurate assessment of the company and its investment potential.

What Jesse thinks is immaterial it’s Brainchips implied adoption of what he thinks that is important.

My opinion only DYOR
FF

AKIDA BALLISTA

Let’s be honest FF. This is what you think, as you wrote it first

 

[Rise from the ashes]

@Slymeat a mate I sent that photo of you and doggo paws/two emu's
Drew a picture of it.

 

[DingoBorat]

Lots of places where you can slot Akida in:

These AI Apps can be optimised for typically resource constrained low power and low memory processing platforms deployed on the edge without requiring an internet connection.


https://www.nviso.ai/en/technology View attachment 9500
also, inter alia, Nvidia

https://www.nviso.ai/en/technology
How does it work? NVISO’s visual intelligence technology uses computers to learn from examples opposed to being manually programmed. Using deep Convolutional Neural Networks (CNNs) and state-of-the-art machine learning to understand human behaviors depicted in images and videos, it can achieve accuracy levels that surpass human performance in many narrowly defined tasks.

CNNs and modern machine learning scale to learn from billions of examples resulting in an extraordinary capacity to learn highly complex behaviors and thousands of categories. Thanks to high volumes of data and powerful computing resources, NVISO intelligence technology can train powerful and highly accurate models.

...

NVISO's technology is purpose built for a new class of ultra-efficient machine learning processors for smart edge devices and edge compute with heterogeneous and secure architecture. Supporting a wide range of heterogenous computing platforms ranging from CPU, GPU, NPU, and Neuromorphic computing it reduces the high barriers-to-entry into the AI space through cost-effective standardized AI Apps that are future proof and work optimally at the extreme edge (low power, on-device, without requiring an internet connection).

• Support a wide range of activations and weights data types (32-bit floating point to 2-bit binary).
• Mixed precision and unstructured sparsity to reduce memory bandwidth and power consumption.
• Support for both advanced NN architectures such as RNN, transformers (self-attention), 3D convolution as well as fully sequential architectures for ultra-low power mixed signal inference engines.

We hooked up with nviso in mid-April this year, so they had already been working with Siemens for several months:

"Over the last year we have worked with Siemens Healthineers’ team to develop concepts to provide new solutions supporting a variety of use cases within the healthcare environment.

... but, and this is a very big butt, this announcement is dated 16 June 2022 or there abouts. Obviously, nviso would have been playing with Akida/Meta-TF for some time before the April 2022 agreement with Brainchip, so it is entirely possible that Akida helped clinch the commercial pilot deal between nviso and Siemens.

"it is entirely possible that Akida helped clinch the commercial pilot deal between nviso and Siemens"

That, was exactly my thinking as well, Diogenese!

@Labsy @BaconLover, where did you get the 18 ingredients for KFC from!
Let's try and keep things factual here, 11 herbs and spices (of which only 1 or 2, would be a mystery), the chicken and the oil, that's 13!
Unless you're including chips and sides?

On a sour note, US futures looking miserable again already ..

The roller coaster continues..

 

[Fact Finder]

Let’s be honest FF. This is what you think, as you wrote it first

Here we go, dragging me back to existential truth yet again.

FF

AKIDA BALLISTA