BRN Discussion Ongoing

[Fact Finder]

This is an interesting page extracted from ISL's website remembering that ISL is an EAP announced application partner the last project being for an SBIR with the US Airforce Research Laboratory involving radar guidance:

Cognitive Systems​

ISL literally wrote the first book on Cognitive Radar in 2010, 2nd Edition 2020 (https://us.artechhouse.com/Cognitiv...y-Adaptive-Approach-Second-Edition-P2093.aspx ), and continues to provide cutting edge solutions in advanced cognitive sensing.

What distinguishes a cognitive system from a more traditional adaptive one, is its contextual “awareness” and advanced embedded computational and AI capabilities. In the case of active sensors such as radar, cognitive sensors also employ active “probing” of the environment to better characterize the entire channel (targets, clutter, interference).

Artificial Intelligence, Neuromorphic Computing and DoD Acceptance Testing​

ISL is focused on replicating the analog nature of biological computation and the role of neurons in cognition. ISL’s team of scientists/engineers continue to understand how the morphology of individual neurons, circuits, applications, and overall architectures creates desirable computations. Leveraging this understanding and the newly developed and emerging commercial neuromorphic chips, ISL is developing a new low-power, lightweight detect and avoid (DAA) system for very small UAS platforms that exploits automotive radar hardware, light-weight EO/IR sensors, advanced data fusion algorithms, and neuromorphic computing.

Additionally, ISL has pioneered an AI acceptance methodology that allows for DoD testing of AI solutions using essentially the same statistically based methodology in use today. ISL was awarded a US Patent for this February (see link). The methodology leverages ISL’s RF Digital Engineering tools (https://www.islinc.com/digital-engineering ).

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Fact Finder]

Way back in time when Mr. Dinardo used deliver his presentations to shareholders on one occasion he mentioned the highly politicised word 'NUCLEAR'. Mr. Dinardo only mentioned this word this one time as far as I can recall. I also do not recall any other Brainchip representative uttering this word though it is possible it occurred I do not believe it was ever produced in any written document that has been released by the company. Given Brainchip's publicly released relationship with ISL the following intelligent controller for nuclear power plants caught my attention:

Nuclear energy is an excellent source of process heat for various industrial applications including desalination, synthetic and unconventional oil production, oil refining, biomass-based ethanol production, and in the future: hydrogen production.
For most major industrial heat applications, nuclear energy is the only credible non-carbon option. But the challenge is how to efficiently regulate, control, and appropriate the excess nuclear heat energy for industrial heat application.
ISL has solved the problem with iCLEAR – Intelligent ControL for Environmentally Advanced Reactors

• iCLEAR addresses challenges associated with CO2 by simultaneously providing clean electricity and sequestering CO2.
• iCLEAR provides an environmentally safe high temperature heat source for processes such as sequestration,
  desalination, etc.
• iCLEAR is an intelligent nuclear controller that anticipates changes in electrical demand and adjusts appropriately.
• iCLEAR is aligned with the next wave of small, advanced nuclear reactors.

Intelligent controller that performs multiple tasks to optimize the use of nuclear reactor output.

• Simultaneously provides clean nuclear electricity and CO2 sequestration
• Anticipates electrical grid demand based on multiple real time inputs
• Implements artificial intelligence to predict future usage trends
• Integrates nuclear island with environmentally desirable processes
• Carbon sequestration
• Desalination
• Production of products with economic value (carbon-based electronics, fuels, hydrogen)
• Heat for industrial processes
• Manages load balance manoeuvres to transfer heat output

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Deleted member 118]

A few people might find this an interesting read (not that I have read it, maybe just a few lines)

Artificial Intelligence Technology and China’s Defense System

Artificial intelligence (AI) technologies have been developed for many years and applied in various areas. Applications of AI are contested not only on domestic surveillance but also on military uses.

www.airuniversity.af.edu

 

[Fact Finder]

Hi Boab,

Looks like the booklet needs to be updated:

https://www.nviso.ai/en/news/nviso-...l-neuromorphic-processor-platform-at-ces-2023

Lausanne, Switzerland – 2nd January, 2023 – nViso SA (NVISO), the leading Human Behavioural Analytics AI company, is pleased that its Neuro SDK will be demonstrated running on the Brainchip Akida platform at the Socionext stand at CES2023. Following the porting of additional AI Apps from its catalogue, NVISO has further enhanced the range of Human Behavioural AI Apps that it supports on the BrainChip Akida event-based, fully digital neuromorphic processing platform. These additions include Action Units, Body Pose and Gesture Recognition on top of the Headpose, Facial Landmark, Gaze and Emotion AI Apps previously announced with the launch of the Evaluation Kit (EVK) version. This increased capability supports the further deployment of NVISO Human Behavioural Analytics AI software solutions with these being able to further exploit the performance capabilities of BrainChip neuromorphic AI processing IP to be deployed within the next generation of SOC devices. Target applications include Robotics, Automotive, Telecommunication, Infotainment, and Gaming.

My memory from the live presentation I attended by Nviso's Tim Llewellyn after the Brainchip AGM last year he said they were working on porting up to 20 or 24 Ai Apps to AKIDA including Ai Apps to monitor driver health including blood pressure and heart rate.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Straw]

 

[Deleted member 118]

Most Americans are uncomfortable with artificial intelligence in health care, survey finds | CNN

Most Americans feel “significant discomfort” about the idea of their doctors using artificial intelligence to help manage their health, a new survey finds, but they generally acknowledge AI’s potential to reduce medical mistakes and to eliminate some of the problems doctors may have with racial...

amp.cnn.com

 

[Diogenese]

Found it. Page 3

Hi Boab,

Looks like the booklet needs to be updated:

https://www.nviso.ai/en/news/nviso-...l-neuromorphic-processor-platform-at-ces-2023

Lausanne, Switzerland – 2nd January, 2023 – nViso SA (NVISO), the leading Human Behavioural Analytics AI company, is pleased that its Neuro SDK will be demonstrated running on the Brainchip Akida platform at the Socionext stand at CES2023. Following the porting of additional AI Apps from its catalogue, NVISO has further enhanced the range of Human Behavioural AI Apps that it supports on the BrainChip Akida event-based, fully digital neuromorphic processing platform. These additions include Action Units, Body Pose and Gesture Recognition on top of the Headpose, Facial Landmark, Gaze and Emotion AI Apps previously announced with the launch of the Evaluation Kit (EVK) version. This increased capability supports the further deployment of NVISO Human Behavioural Analytics AI software solutions with these being able to further exploit the performance capabilities of BrainChip neuromorphic AI processing IP to be deployed within the next generation of SOC devices. Target applications include Robotics, Automotive, Telecommunication, Infotainment, and Gaming.
“BrainChip’s event-based Akida platform is accelerating today’s traditional networks and simultaneously enabling future trends in AI software applications” said Rob Telson, VP Ecosystems, BrainChip. “NVISO is a valued partner of Brain Chip’s growing ecosystem, and their leadership in driving extremely efficient software solutions gives a taste of what compelling applications are possible at the edge on a minimal energy budget”.

Hi Boab,

The remarkable thing is that your press release without Akida gesture and pose is dated 16 December 2022, and the CES announcement dated 2 January 2023 has added Akida gesture and pose to the nViso AI App. It's easy in software.

MetaTF is free for users to use for testing, but I wonder if we charge for commercial use?

 

[Serengeti]

Good evening,

Could this be BRN?

CHIP DEVELOPMENTDevelopment of ultra-low power on-device learning edge AI chip​

08.12.2022 From ROHM (press release)


ROHM has developed an on-device learning AI chip (SoC with on-device learning AI accelerator) for edge computer endpoints in the IoT field. It utilizes artificial intelligence to predict failures (predictive failure detection) in electronic devices equipped with motors and sensors in real-time with ultra-low power consumption.

Combining the 20,000-gate ultra-compact AI accelerator with a high-performance CPU enables learning and inference with ultra-low power consumption of just a few tens of mW (1000× smaller than conventional AI chips capable of learning).

Going forward, ROHM plans to incorporate the AI accelerator used in this AI chip into various IC products for motors and sensors. Commercialization is scheduled to start in 2023, with mass production planned in 2024.

ROHM Develops Ultra-Low-Power On-Device Learning Edge AI Chip | ROHM Semiconductor - ROHM Co., Ltd.

ROHM has developed an on-device learning AI chip (SoC with on-device learning AI accelerator) for edge computer endpoints in the IoT field.

www.rohm.com

 

[Boab]

Hi Boab,

The remarkable thing is that your press release without Akida gesture and pose is dated 16 December 2022, and the CES announcement dated 2 January 2023 has added Akida gesture and pose to the nViso AI App. It's easy in software.

MetaTF is free for users to use for testing, but I wonder if we charge for commercial use?

I'm excited.

 

[Learning]

Good evening,

Could this be BRN?

CHIP DEVELOPMENTDevelopment of ultra-low power on-device learning edge AI chip​

08.12.2022 From ROHM (press release)


ROHM has developed an on-device learning AI chip (SoC with on-device learning AI accelerator) for edge computer endpoints in the IoT field. It utilizes artificial intelligence to predict failures (predictive failure detection) in electronic devices equipped with motors and sensors in real-time with ultra-low power consumption.

View attachment 33011

Combining the 20,000-gate ultra-compact AI accelerator with a high-performance CPU enables learning and inference with ultra-low power consumption of just a few tens of mW (1000× smaller than conventional AI chips capable of learning).

Going forward, ROHM plans to incorporate the AI accelerator used in this AI chip into various IC products for motors and sensors. Commercialization is scheduled to start in 2023, with mass production planned in 2024.

ROHM Develops Ultra-Low-Power On-Device Learning Edge AI Chip | ROHM Semiconductor - ROHM Co., Ltd.

ROHM has developed an on-device learning AI chip (SoC with on-device learning AI accelerator) for edge computer endpoints in the IoT field.

www.rohm.com

Hi Serengeti,

Our more knowledgeable members would give you a more definitive answer.

However, reading this,

"Based on an ‘on-device learning algorithm’ developed by Professor Matsutani of Keio University,"

reading the above, I believe it's not Akida.

Learning 🏖

 

[chapman89]

Good evening,

Could this be BRN?

CHIP DEVELOPMENTDevelopment of ultra-low power on-device learning edge AI chip​

08.12.2022 From ROHM (press release)


ROHM has developed an on-device learning AI chip (SoC with on-device learning AI accelerator) for edge computer endpoints in the IoT field. It utilizes artificial intelligence to predict failures (predictive failure detection) in electronic devices equipped with motors and sensors in real-time with ultra-low power consumption.

View attachment 33011

Combining the 20,000-gate ultra-compact AI accelerator with a high-performance CPU enables learning and inference with ultra-low power consumption of just a few tens of mW (1000× smaller than conventional AI chips capable of learning).

Going forward, ROHM plans to incorporate the AI accelerator used in this AI chip into various IC products for motors and sensors. Commercialization is scheduled to start in 2023, with mass production planned in 2024.

ROHM Develops Ultra-Low-Power On-Device Learning Edge AI Chip | ROHM Semiconductor - ROHM Co., Ltd.

ROHM has developed an on-device learning AI chip (SoC with on-device learning AI accelerator) for edge computer endpoints in the IoT field.

www.rohm.com

 

[equanimous]

Time in the market

 

[Fastback6666]

Prophesee’s Big Three: Sony, Qualcomm and Smartphones | The Ojo-Yoshida Report

Finally, event-based image sensors leveraging neuromorphic engineering principles come to smartphones.

ojoyoshidareport.com

By teaming with Sony, the world’s largest CMOS image sensor company, and Qualcomm, which commands a 50-percent share of the mobile SoC market, Prophesee, a Paris-based startup, is finally finding a massive volume market for its unique event-based cameras in smartphones

So does this mean Brainchip will have massive volume in royalties flowing through from this? Sounds exciting....

 

[Diogenese]

I'm excited.

https://www.nviso.ai/en/extreme-edge-high-performance-computing-hpc

NVISO Neuro Models™ are purpose built for a new class of ultra-efficient AI processors designed for ultra-low deep learning on edge devices. Supporting a wide range of heterogenous computing platforms ranging from CPU, GPU, VPU, NPU, and neuromorphic computing they reduce the high barriers-to-entry into the embedded AI space through cost-effective standardized AI Apps which work optimally on edge devices for a range of common human behaviour use cases (low power, on-device, without requiring an internet connection). NVISO Neuro Models™ use low and mixed precision activations and weights data types (1 to 8-bit) combined with state-of-the-art unstructured sparsity to reduce memory bandwidth and power consumption. Using proprietary compact network architectures, they can be fully sequential suitable for ultra-low power mixed signal inference engines and fully interoperable with neuromorphic processors as well as existing digital accelerators.

Now who do we know who has a digital SNN capable of handling 1 to 8 bits ...
... in particular, 8-bit weights and activations?

 

[Fact Finder]

We all know Quantum Ventura they famously confirmed in a peer reviewed research paper that an AKIDA 1000 USB at $50.00 could match it with a Nvidia GPU at $30,000.

https://www.sciencedirect.com/science/article/pii/S1877050922017860/pdf?md5=c6abc5833a81c629954f7969fc65de04&pid=1-s2.0-S1877050922017860-main.pdf

Well this is what they are presently doing according to their website:

Our Current Federally-Funded Research Projects as the Prime Contractor:​

AI/ML/ Hyperspectral Imaging/ Neuromorphic/ Cybersecurity related topics:



DARPA: "AI Verification with provable guarantees" using advanced AI verification tools.

Partner: NC State University



Navy Air Warfare: "Certification of AI Systems - CORSI" using Advanced AI to certify AI/ML applications. (Phase 1 and Phase 2 SBIRs)

Partner: Lockheed Martin.



Missile Defense Agency: "Hypersonic Threat Detection" using bio-inspired processing, neuromorphic computing and Advanced AI. (Phase 1 STTR)

Partners: University of Florida and Lockheed Martin.



Navy Air Warfare: "Detection of UAVs and rogue drones using hyperspectral Imaging" (SBIR Phase 1).

Partners: Bodkin Imaging and Lockheed



Navy Air Warfare: "Vulnerability detection of source code using advanced AI/ML" - SBIR Phase 1



Homeland Security: "Opioid/contraband detection using hyperspectral imaging" - SBIR Phase 1



Department of Energy: "Cyber threat-detection using neuromorphic computing" - SBIR Phase 1

All sounding a bit ubiquitous if you ask me.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Diogenese]

I couldn't resist another peek at the Gen 2 Product Brief:

https://brainchip.com/wp-content/uploads/2023/03/BrainChip_second_generation_Platform_Brief.pdf

I can't wait!!!!!!!!!!!!!! ...

"Exceptional spatio-temporal capability: Patent-pending Temporal Event-based Neural Nets (TENNs) revolutionize time-series data applications"



"Efficient Vision Transformer acceleration: Vision Transformer encoder acceleration to provide radically better vision solutions"


Note that, when not operating in pure SNN mode, some processor participation is needed:
"Accelerates today’s networks: CNNs, DNNs, RNNs, Vision Transformers (ViT), and more, directly in hardware with minimal CPU intervention ...
Independent neural processor operation: Intelligent DMA minimizes or eliminates need for CPU in AI acceleration; minimizes system load"

Well I haven't looked at Renesas DRP-AI (dynamically reconfigurable processor -AI), but Akida can do it with your eyes closed.

Multi-Pass Processing Delivers Scalability, Future-Proofing:
Extremely scalable
• Runs larger networks on given set of nodes
• Reduces Silicon footprint and Power in SoC
Transparent to application developer and users
• Handled by runtime software
• Segments and processes network sequentially
Minimizes incremental latency
• Handles multiple layers concurrently
• Minimizes CPU intervention

That's pretty Tardus-like - if you need more nodes than there are on the SoC, we'll just keep using the ones we have until the jobs done. It's like when the team bus breaks down and you've only got a Mini ...


"Akida is model-, network-, and OS-agnostic"
So we can use custom models like nViso's as well as the standard models and out own in-house models.

 

[Deadpool]

We all know Quantum Ventura they famously confirmed in a peer reviewed research paper that an AKIDA 1000 USB at $50.00 could match it with a Nvidia GPU at $30,000.

https://www.sciencedirect.com/science/article/pii/S1877050922017860/pdf?md5=c6abc5833a81c629954f7969fc65de04&pid=1-s2.0-S1877050922017860-main.pdf

Well this is what they are presently doing according to their website:

Our Current Federally-Funded Research Projects as the Prime Contractor:​

AI/ML/ Hyperspectral Imaging/ Neuromorphic/ Cybersecurity related topics:



DARPA: "AI Verification with provable guarantees" using advanced AI verification tools.

Partner: NC State University



Navy Air Warfare: "Certification of AI Systems - CORSI" using Advanced AI to certify AI/ML applications. (Phase 1 and Phase 2 SBIRs)

Partner: Lockheed Martin.



Missile Defense Agency: "Hypersonic Threat Detection" using bio-inspired processing, neuromorphic computing and Advanced AI. (Phase 1 STTR)

Partners: University of Florida and Lockheed Martin.



Navy Air Warfare: "Detection of UAVs and rogue drones using hyperspectral Imaging" (SBIR Phase 1).

Partners: Bodkin Imaging and Lockheed



Navy Air Warfare: "Vulnerability detection of source code using advanced AI/ML" - SBIR Phase 1



Homeland Security: "Opioid/contraband detection using hyperspectral imaging" - SBIR Phase 1



Department of Energy: "Cyber threat-detection using neuromorphic computing" - SBIR Phase 1

All sounding a bit ubiquitous if you ask me.

My opinion only DYOR
FF

AKIDA BALLISTA

I think we're going to need a bigger boat.

 

[Diogenese]

I think we're going to need a bigger boat.

I think we're gonna need a flotilla.

 

[Diogenese]

So does this mean Brainchip will have massive volume in royalties flowing through from this? Sounds exciting....

We haven't seen any evidence that we are involved in this first round of Sony/Prophesee, ...

... but

... does anyone else make mobile phones?

 

[Fact Finder]

I couldn't resist another peek at the Gen 2 Product Brief:

https://brainchip.com/wp-content/uploads/2023/03/BrainChip_second_generation_Platform_Brief.pdf



View attachment 33016

View attachment 33018



I can't wait!!!!!!!!!!!!!! ...

"Exceptional spatio-temporal capability: Patent-pending Temporal Event-based Neural Nets (TENNs) revolutionize time-series data applications"



"Efficient Vision Transformer acceleration: Vision Transformer encoder acceleration to provide radically better vision solutions"


Note that, when not operating in pure SNN mode, some processor participation is needed:
"Accelerates today’s networks: CNNs, DNNs, RNNs, Vision Transformers (ViT), and more, directly in hardware with minimal CPU intervention ...
Independent neural processor operation: Intelligent DMA minimizes or eliminates need for CPU in AI acceleration; minimizes system load"

View attachment 33019


Well I haven't looked at Renesas DRP-AI (dynamically reconfigurable processor -AI), but Akida can do it with your eyes closed.

Multi-Pass Processing Delivers Scalability, Future-Proofing:
Extremely scalable
• Runs larger networks on given set of nodes
• Reduces Silicon footprint and Power in SoC
Transparent to application developer and users
• Handled by runtime software
• Segments and processes network sequentially
Minimizes incremental latency
• Handles multiple layers concurrently
• Minimizes CPU intervention

That's pretty Tardus-like - if you need more nodes than there are on the SoC, we'll just keep using the ones we have until the jobs done. It's like when the team bus breaks down and you've only got a Mini ...


"Akida is model-, network-, and OS-agnostic"
So we can use custom models like nViso's as well as the standard models and out own in-house models.

It reminds me of this Charlie Chaplin skit - just keep going around till you knock it out of the park: