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uiux

uiux

Regular
I wanted to collate a few of the NASA/military/government related projects together to try get a better idea of the subterranean reach of BrainChip's Akida. If I have missed any - let me know.

Here is a summary list of organisations directly involved with BrainChip Akida:
  • NASA
  • SiFive
  • Vorago
  • Quantum Ventura
  • Intellisense Systems
  • Riverside Research
  • Tensor Innovation Partners
  • BHTech
  • Information Systems Laboritories
  • NUMEM

SiFive:

BrainChip, SiFive partner to bring AI and ML to edge computing

The integration of BrainChip's Akida technology and SiFive's multi-core capable RISC-V processors is expected to provide an efficient solution for integrated edge AI computing.
venturebeat.com venturebeat.com

SIFive is also a member of the DARPA toolbox initiative



Vorago:

Deep Neural Net and Neuromorphic Processors for In-Space Autonomy and Cognition

Vorago is radiation hardening the Akida IP.


Vorago is also radiation hardening the RISC-V IP.



Quantum Ventura:

Realtime Neuromorphic Cyber-Agents (Cyber-NeuroRT)



Intellisense Systems:

Deep Neural Net and Neuromorphic Processors for In-Space Autonomy and Cognition


Intellisense Systems, Inc. (Torrance, Calif.) for Radiofrequency One-Shot Learning for Emission Recognition

www.army.mil

Army awards $19M to small businesses to develop AI/ML technologies

WASHINGTON – The U.S. Army has awarded nearly $19 million to 23 small businesses to develop their artificial intelligence and machine learning solutions...
www.army.mil www.army.mil

Adaptive Deep Onboard Reinforcement Bidirectional Learning System



Tensor Innovation Partners:

Scalable Neural Net and Neuromorphic Module for In-Space Autonomous Orientation and Maneuvering

techport.nasa.gov

NASA TechPort

NASA's Technology Portfolio Management System (TechPort) is a single, comprehensive resource for locating detailed information about NASA-funded technologies. Those technologies cover a broad range of areas, such as propulsion, nanotechnology, robotics, and human health. You can find useful...
techport.nasa.gov techport.nasa.gov


Riverside Research:

Securing Compartmented Information with Smart Radio Systems (SCISRS)



BHTech:

Implementing Neural Network Algorithms on Neuromorphic Processors

Implementing Neural Network Algorithms on Neuromorphic Processors | SBIR.gov

www.sbir.gov www.sbir.gov
xcelaero.com

3/17/2022 Press Release - BHTech wins Phase II SBIR Award for Implementing Neural Network Algorithms on Neuromorphic Processors

The generation of real-time insights for the warfighter is an increasingly important area of interest, especially due to the growth of Electronic Warfare challenges. These insights require faster processors and smarter models that can be deployed at the edge in low Size, Weight and Power (SWaP)...
xcelaero.com xcelaero.com


Information Systems Laboratories:

Deep Learning Sensor Technology for Safe Flying Car Operations

brainchipinc.com

Information Systems Labs Joins BrainChip Early Access Program

BrainChip announced that Information Systems Labs is developing an AI-based radar research solution for the AFRL based on Akida™
brainchipinc.com brainchipinc.com

Deep Learning Sensor Technology for Safe Flying Car Operations | SBIR.gov

www.sbir.gov www.sbir.gov


NUMEM:

Neuromorphic Processor with radiation tolerant MRAM

 
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hotty4040

Regular
uiux said:
I wanted to collate a few of the NASA/military/government related projects together to try get a better idea of the subterranean reach of BrainChip's Akida. If I have missed any - let me know.

Here is a summary list of organisations directly involved with BrainChip Akida:
  • NASA
  • SiFive
  • Vorago
  • Quantum Ventura
  • Intellisense Systems
  • Riverside Research
  • Tensor Innovation Partners
  • BHTech
  • Information Systems Laboritories
  • NUMEM

SiFive:

BrainChip, SiFive partner to bring AI and ML to edge computing

The integration of BrainChip's Akida technology and SiFive's multi-core capable RISC-V processors is expected to provide an efficient solution for integrated edge AI computing.
venturebeat.com venturebeat.com

SIFive is also a member of the DARPA toolbox initiative



Vorago:

Deep Neural Net and Neuromorphic Processors for In-Space Autonomy and Cognition

Vorago is radiation hardening the Akida IP.


Vorago is also radiation hardening the RISC-V IP.



Quantum Ventura:

Realtime Neuromorphic Cyber-Agents (Cyber-NeuroRT)



Intellisense Systems:

Deep Neural Net and Neuromorphic Processors for In-Space Autonomy and Cognition


Intellisense Systems, Inc. (Torrance, Calif.) for Radiofrequency One-Shot Learning for Emission Recognition

www.army.mil

Army awards $19M to small businesses to develop AI/ML technologies

WASHINGTON – The U.S. Army has awarded nearly $19 million to 23 small businesses to develop their artificial intelligence and machine learning solutions...
www.army.mil www.army.mil

Adaptive Deep Onboard Reinforcement Bidirectional Learning System



Tensor Innovation Partners:

Scalable Neural Net and Neuromorphic Module for In-Space Autonomous Orientation and Maneuvering

techport.nasa.gov

NASA TechPort

NASA's Technology Portfolio Management System (TechPort) is a single, comprehensive resource for locating detailed information about NASA-funded technologies. Those technologies cover a broad range of areas, such as propulsion, nanotechnology, robotics, and human health. You can find useful...
techport.nasa.gov techport.nasa.gov


Riverside Research:

Securing Compartmented Information with Smart Radio Systems (SCISRS)



BHTech:

Implementing Neural Network Algorithms on Neuromorphic Processors

Implementing Neural Network Algorithms on Neuromorphic Processors | SBIR.gov

www.sbir.gov www.sbir.gov
xcelaero.com

3/17/2022 Press Release - BHTech wins Phase II SBIR Award for Implementing Neural Network Algorithms on Neuromorphic Processors

The generation of real-time insights for the warfighter is an increasingly important area of interest, especially due to the growth of Electronic Warfare challenges. These insights require faster processors and smarter models that can be deployed at the edge in low Size, Weight and Power (SWaP)...
xcelaero.com xcelaero.com


Information Systems Laboratories:

Deep Learning Sensor Technology for Safe Flying Car Operations

brainchipinc.com

Information Systems Labs Joins BrainChip Early Access Program

BrainChip announced that Information Systems Labs is developing an AI-based radar research solution for the AFRL based on Akida™
brainchipinc.com brainchipinc.com

Deep Learning Sensor Technology for Safe Flying Car Operations | SBIR.gov

www.sbir.gov www.sbir.gov


NUMEM:

Neuromorphic Processor with radiation tolerant MRAM

Click to expand...

Robust info there uiux, and useful reminders of our ( Brainchips ) involvement's in the scheme of things, IMO. Great to hear from you, and that you're still around.

We need a ( seal the deal ) so to speak, discovery, of not too categoric proportions to bump us along a bit more in the interim. This will help for sure!.


gltah

A B

hotty...
 
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Bravo

Bravo

If ARM was an arm, BRN would be its biceps💪!
uiux said:
I wanted to collate a few of the NASA/military/government related projects together to try get a better idea of the subterranean reach of BrainChip's Akida. If I have missed any - let me know.

Here is a summary list of organisations directly involved with BrainChip Akida:
  • NASA
  • SiFive
  • Vorago
  • Quantum Ventura
  • Intellisense Systems
  • Riverside Research
  • Tensor Innovation Partners
  • BHTech
  • Information Systems Laboritories
  • NUMEM

SiFive:

BrainChip, SiFive partner to bring AI and ML to edge computing

The integration of BrainChip's Akida technology and SiFive's multi-core capable RISC-V processors is expected to provide an efficient solution for integrated edge AI computing.
venturebeat.com venturebeat.com

SIFive is also a member of the DARPA toolbox initiative



Vorago:

Deep Neural Net and Neuromorphic Processors for In-Space Autonomy and Cognition

Vorago is radiation hardening the Akida IP.


Vorago is also radiation hardening the RISC-V IP.



Quantum Ventura:

Realtime Neuromorphic Cyber-Agents (Cyber-NeuroRT)



Intellisense Systems:

Deep Neural Net and Neuromorphic Processors for In-Space Autonomy and Cognition


Intellisense Systems, Inc. (Torrance, Calif.) for Radiofrequency One-Shot Learning for Emission Recognition

www.army.mil

Army awards $19M to small businesses to develop AI/ML technologies

WASHINGTON – The U.S. Army has awarded nearly $19 million to 23 small businesses to develop their artificial intelligence and machine learning solutions...
www.army.mil www.army.mil

Adaptive Deep Onboard Reinforcement Bidirectional Learning System



Tensor Innovation Partners:

Scalable Neural Net and Neuromorphic Module for In-Space Autonomous Orientation and Maneuvering

techport.nasa.gov

NASA TechPort

NASA's Technology Portfolio Management System (TechPort) is a single, comprehensive resource for locating detailed information about NASA-funded technologies. Those technologies cover a broad range of areas, such as propulsion, nanotechnology, robotics, and human health. You can find useful...
techport.nasa.gov techport.nasa.gov


Riverside Research:

Securing Compartmented Information with Smart Radio Systems (SCISRS)



BHTech:

Implementing Neural Network Algorithms on Neuromorphic Processors

Implementing Neural Network Algorithms on Neuromorphic Processors | SBIR.gov

www.sbir.gov www.sbir.gov
xcelaero.com

3/17/2022 Press Release - BHTech wins Phase II SBIR Award for Implementing Neural Network Algorithms on Neuromorphic Processors

The generation of real-time insights for the warfighter is an increasingly important area of interest, especially due to the growth of Electronic Warfare challenges. These insights require faster processors and smarter models that can be deployed at the edge in low Size, Weight and Power (SWaP)...
xcelaero.com xcelaero.com


Information Systems Laboratories:

Deep Learning Sensor Technology for Safe Flying Car Operations

brainchipinc.com

Information Systems Labs Joins BrainChip Early Access Program

BrainChip announced that Information Systems Labs is developing an AI-based radar research solution for the AFRL based on Akida™
brainchipinc.com brainchipinc.com

Deep Learning Sensor Technology for Safe Flying Car Operations | SBIR.gov

www.sbir.gov www.sbir.gov


NUMEM:

Neuromorphic Processor with radiation tolerant MRAM

Click to expand...
Hi uiux,

It might not fit here but I think it's interesting that MosChip contributes to space tech working on various projects with ISRO (Indian Space Research Organisation).

moschip.com

Embedded Devices for Space Tech: Where are we Today?

Embedded systems are all about maximizing efficiency and minimizing clutter. They’ve become indispensable in daily life, playing...
moschip.com

 
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Reactions: 17 users
uiux

uiux

Regular
Here are three recent SBIR proposals that may end up involving Akida - I have seen several proposals start in ph1 with a vague description of neuromorphic computing and specifically mention Akida in ph2. So these are projects to watch.




Niobium Microsystems

Scalable Neuromorphic Energy-Efficient Accelerator for Heterogeneous Processor Architectures

Technical Abstract (Limit 2000 characters, approximately 200 words):
Under this effort, Niobium Microsystems, Inc. is proposing a low power computing architecture accelerator for neuromorphic processing which can enable real-time sensor data processing and autonomous decision making that is cost-effective and scalable to the growing data ingestion and processing needs of future autonomous systems. The proposed architecture will be highly scalable and compatible with modern processor systems (such as RISC-V or ARM), so that it can be easily adopted in a variety of new systems, and also easily integrated into existing systems. Additionally, Niobium proposes to integrate the proposed accelerator into a larger SoC that will serve as a proving ground and reference design for the accelerator concept. The SoC will be capable of acting as a primary processor in systems or as a co-processor to existing systems. Ultimately Niobium intended to utilize this accelerator as a standard block in its family of heterogeneous processor architectures.
Niobium proposes the following four technical objectives for Phase I:
(1) Study prior efforts and capture the performance and efficiency metrics as well as the limitations of existing platforms;
(2) Propose a novel architecture for a neuromorphic accelerator compatible with heterogeneous processor platforms (RISC-V- or ARM-based);
(3) Explore available MRAM technology (GlobalFoundries 22FDX), characterize its PPA and propose ways for incorporating into the architecture; and
(4) Estimate performance, power and efficiency metrics for comparison to existing solutions.

Potential NASA Applications (Limit 1500 characters, approximately 150 words):
Space platform which require on-board energy efficient inference capabilities and possibly decision making and action will benefit from the low-power energy efficient inference capability of Neuromorphic processors. Long range missions that will require long-term unsupervised learning and adaptation based on constantly evolving unpredictable conditions can also benefit by the learning modalities that Neuromorphic architectures uniquely support.

Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words):
Niobium is pursuing a fabless semiconductor model & planning to incorporate this accelerator into future energy-efficient SoCs along with existing accelerators for DNNs, cryptography & other computationally intensive functions. These energy-efficient processor SoCs will target energy-constrained application markets (unsupervised sensors & sensor networks, lightweight robotics, drones, wearables).




Brisk Computing, LLC

Adaptive Neuromorphic Processors for Cognitive Communications

Technical Abstract (Limit 2000 characters, approximately 200 words):
The objective of this work is to develop highly Size, Weight, and Power (SWaP) efficient neuromorphic processors that can train deep learning algorithms. The training phase for deep learning is very compute and data intensive. Being able to train a network on the satellite eliminates the need to send large volumes of data to earth for training a new network. However, this requires an extremely energy efficient deep learning training processor. We will develop resistive crossbar neuromorphic processors, with the primary target being to train deep learning algorithms. Although our system would work for any type of data, we plan to focus on networks for cognitive communication applications. We will also look at processing networks for other data sets. The key outcomes of the work will be the processor design, processor performance metrics on various applications, prototype system, and software for the processor.

Potential NASA Applications (Limit 1500 characters, approximately 150 words):
Potential NASA applications include various deep learning training and inference tasks on satellites. These include cognitive communications, processing sensor outputs, and scientific experiments. Additionally, the developed system could be used for UAVs.

Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words):
The non-NASA market would be primarily for edge processing, where power is highly limited. The market includes both the DoD and the commercial market. DoD applications include cognitive communications, sensor processing, cognitive decision making, and federated learning. Commercial applications include communications systems, automobiles, consumer electronics, and robots.




Exploration Institute, LLC

Neuromorphic Electronics that Rethinks Verifiable Efficiency on Spacecraft (NERVES)

Technical Abstract (Limit 2000 characters, approximately 200 words):
To meet the NASA need for power efficient algorithms that improve onboard autonomy, Exploration Institute proposes to develop NERVES, an approach for power efficient, verifiable generic calculation and signals processing onboard resource constrained systems using the latest neuromorphic hardware.
Through our substantial experience in applying and developing neuromorphic algorithms for spacecraft systems, we have determined that the performance of our algorithms can be substantially improved if the lowest level substrate, the building blocks, were designed to use the most power efficient traits of neuromorphic hardware. More efficient performance of key mathematical operations in neuromorphic hardware would provide high value to spacecraft developers as they can translate their existing work directly into a vastly more power efficient and faster processing system. NERVES is driven by a practical need and the pipeline to commercialization is already established through Exploration Institute’s track record and current work.
NERVES directly maps conventional algorithms to any neuromorphic processor, combining the benefits of more capable, well known algorithms with the power savings of a neuromorphic architecture. A neuromorphic chip like Intel’s Loihi has a computational power density of more than 1000x that of a CPU or GPU for some tasks. Based on our initial analysis, Exploration Institute predicts that NERVES will enable these kinds of power savings (or conversely, computational capacity increase for the same power) which will greatly improve NASA's capacity for onboard autonomy.
As an added bonus, NERVES provides a more verifiabile approach to neuromorphic computing in space, by allowing the use of verified computing approaches (non-neuromorphic, conventional) on neuromorphic hardware with all the power savings that can entail. This enables more likely adoption and infusion into NASA programs.

Potential NASA Applications (Limit 1500 characters, approximately 150 words):
For a given power budget, using NERVES in concert with neuromorphic hardware, NASA could run significantly more complex processing onboard that will enable more onboard autonomy. With such a general, infrastructure-level additional capability, the potential applications are numerous, including: safer human habitation modules, faster onboard autonomy for navigation and other applications, more automated onboard Fault Management, and a foundation to build onboard cognitive computing to support general operations.

Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words):
NERVES is specifically designed for spacecraft systems such as Gateway, planetary robotics, and government and commercial satellites in general, but also applies to any autonomous system, particularly autonomous vehicles, and is especially useful for applications that are power constrained and mobile (for example: agricultural and automated platforms).
 
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