BRN Discussion Ongoing

[Wags]

Announcement! Contract with US Airforce worth $1.8m. However, the message it sends to the market about the product is Priceless.

100% agree. Hoping this is the beginning of the snowball.

 

[Bravo]

 

[supersonic001]

M Anthony Lewis on LinkedIn: #tenns #mamba #brainchip

Yes to Edge AI! BrainChip has racked up an impressive number of beyond state of the art models for edge inference. These models are based on our own TENNs…

www.linkedin.com

 

[Wags]

100% agree. Hoping this is the beginning of the snowball.

And though I am only guessing, it won't surprise me if BRN has something else to say very soon, maybe today??
Validation like that...... And so it begins

 

[GDJR69]

Furthermore, if you were short, you'd be wanting to close your position about now wouldn't you? That could also add further upward momentum.

 

[Bravo]

Beep beep! Get outta my way !

 

[supersonic001]

I like this blokes thinking


View attachment 73969

Question for all product professionals:

What do you do when a product is so innovative, so disruptive, and so perfect for solving billions of $ of problems, and providing billions of $ of savings but is so new and revolutionary that companies are afraid to be first?

This is the very unique problem faced by #BrainChip and when fear of being first gives way to the determination to solve problems that are bordering on crisis, technology companies around the world will line up for BrainChip's product. Until then, fear wins the day. #apple #google #auto #tesla

spot on TTM - crippling fear of unknown.... do some more research BIG dog Co's and get on board, time for the guinea pig to go bye bye... !!

 

[buena suerte :-)]

"BrainChip will partner with the subcontractor to provide R&D services developing and optimizing algorithms for a fixed fee totalling $800k over the same period."

Is Brainchip receiving or paying this $800K?

I was reading it as $1.8m for contract and we also get $800k for 'providing' R&D services !!? = AU$4mil

 

[SiDEvans]

I was reading it as $1.8m for contract and we also get $800k for 'providing' R&D services !!? = AU$4mil

That's how I read it also

 

[7für7]

Market is shocked share prices doesn’t know what to do now

 

[GazDix]

TENNS has arrived. Better late than never I suppose. Hopefully the first of many to come.
Of course the airforce collaborates with the defense force and navy too. Much potential to be had even in this little niche.

 

[Mea culpa]

Beep beep! Get outta my way !




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View attachment 73993

I've arranged for a truck load of mulch for your garden and I'm ironing my speedos as we speak, although I understand wearing them in the hot tub isn't necessary.

 

[Diogenese]

Interesting comment on Akida by Sounak Dey

https://www.linkedin.com/posts/soun...he-morpheus-activity-7195181143552401409-7O0N

SC

M Anthony Lewis on LinkedIn: #tenns #mamba #brainchip

Yes to Edge AI! BrainChip has wracked up an impressive number of beyond state of the art models for edge inference. These models are based on our own TENNs…

www.linkedin.com

Two extremely bullish posts

Akida 1 already provided a great advantage in model compression with N-of-M coding. Now it seems that TENNs provides even greater improvements.

Second page

View attachment 73983

I think the subcontractor is ISL

https://brainchip.com/information-systems-labs-early-access-program/

Information Systems Labs Joins BrainChip Early Access Program​

Laguna Hills, Calif. – January 9, 2022 – 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.

ISL is an employee-owned technology development corporation that performs expert research and complex analysis, software and systems engineering, advanced hardware design and development, and high-quality specialty fabrication for a variety of customers worldwide.

ISL specializes in the areas of advanced signal processing, space exploration, undersea technologies, surveillance and tracking, cyber security, advanced radar systems, and energy independence. As a member of BrainChip’s Early Access Program, ISL will be able to evaluate boards with the Akida device, software and hardware support and dedicated engineering resources.

“As part of BrainChip’s EAP, we’ve had the opportunity to evaluate firsthand the capabilities that Akida provides to the AI ecosystem,” said Jamie Bergin, Senior VP, Manager of Research, Development and Engineering Solutions Division at ISL.

 

[AARONASX]

Well credit where credit is due, Sean did say a few weeks ago something around now might come out...not that bad of a bloke after all!

 

[TheDrooben]

.......and 50/200 sma golden cross is happening. Would not want to be in a short position atm

Happy as Larry

 

[Smoothsailing]

More likes

 

[miaeffect]

Waaaat?!

 

[DingoBorat]

M Anthony Lewis on LinkedIn: #tenns #mamba #brainchip

Yes to Edge AI! BrainChip has racked up an impressive number of beyond state of the art models for edge inference. These models are based on our own TENNs…

www.linkedin.com

View attachment 73992

I'm more impressed by Dr Anthony's LinkedIn post, than the Company announcement today

 

[Diogenese]

https://digital-library.theiet.org/doi/book/10.1049/pbra034e

The micro-Doppler effect appears as Doppler frequency modulations in coherent laser or microwave radar systems induced by mechanical vibrations or rotations of a target or any part on the target. These Doppler modulations become a distinctive signature of a target that incorporates vibrating or rotating structures, and provides evidence of the identity of the target with movement. This book concentrates on the processing and application of radar micro-Doppler signatures in real world situations, providing readers with a working knowledge on various applications of radar micro-Doppler signatures such as detection, tracking and discrimination of vehicles and dismounts, identifying human movement based on radar micro-Doppler signatures, detection and tracking small boats in sea, detection and discrimination complex motion of missile warheads, discrimination of quadrupedal animals, and detection and tracking of flying birds. Topics covered include bistatic/multistatic micro-Doppler signatures, decomposition of micro-Doppler signatures, through-wall radar micro-Doppler signatures and ultrasound micro-Doppler signature studies. Radar Micro-Doppler Signatures: Processing and applications will be of interest to R&D researchers and engineers in government research centers, industries, and universities around the world who work on radar imaging and signal analysis, target feature extraction, and non-cooperative target recognition.

This is sort of the background hum on a radar reflection.

A couple of months ago, I read a post which contained a refference to identifying drones from the propellor rotation, but I can't recall the source.

 

[Fullmoonfever]

Nice win and look fwd to many more.

This is appears a D2P2...direct to Phase II award by the looks which is even better.

When you go to the page, at the bottom it lists awardees who have won similar contracts and Bascom Hunter is one of them...I wonder

The below states 6 mths - 1 year although I just found an April 24 DoD document that states it can be to a max 24 mths as further below.

Mapping Complex Sensor Signal Processing Algorithms onto Neuromorphic Chips​

ID: AF242-D015 • Type: SBIR / STTR Topic
DescriptionOverviewContactsDocsQ&ALifecycleAwardsIDVsContractsProtestsIncumbentsBidders 8SimilarAdditional
This opportunity is a topic area under the Small Business Innovation Research / Small Business Technology Transfer (SBIR/STTR). Please see the source for documents.

Description​

OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Trusted AI and Autonomy; Advanced Computing and Software; Microelectronics; Emerging Threat Reduction The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws. OBJECTIVE: Develop an efficient workflow and approach for mapping complex RF and radar signal processing algorithms onto neuromorphic hardware. The neuromorphic hardware can be a limited research prototype or a commercial product. The signal processing algorithms encompass processing of RF signals to decode communication waveforms, Multiple-Input Multiple-Output (MIMO) adaptive beamforming, Space-Time Adaptive Processing (STAP), Ground Moving Target Indicator radar, and generating Synthetic Aperture Radar (SAR) images from raw in-phase and quadrature data. The goal is to outline a versatile approach that can translate algorithms as specified in the Matlab or Python software environment into a neuromorphic model implemented in physical hardware. DESCRIPTION: The ubiquity of embedded RF devices and the Internet of Things (IoT) has motivated approaches to process data with less latency and power consumption [1]. Neuromorphic integrated circuit (IC) hardware has enabled new ultra-low power embedded RF and radar signal processing applications implemented through deep learning neural network (DLNN) models [2-4]. Neuromorphic hardware provides an advantage of a factor of 100 in power consumption per inference relative to emulation using a traditional Graphics Processing Unit (GPU) [5]. PHASE I: As this is a Direct-to-Phase-II (D2P2) topic, no Phase I awards will be made as a result of this topic. To qualify for this D2P2 topic, the Government expects the applicant(s) to demonstrate feasibility by means of a prior Phase I-type effort that does not constitute work undertaken as part of a prior or ongoing SBIR/STTR funding agreement. The required feasibility demonstration must include successfully developing advanced AI-based radio frequency (RF) algorithms and successfully porting them to a neuromorphic chip, with the final chip performing very well. PHASE II: Using a HWIL approach, awardee(s) will measure the response of the neuromorphic hardware to RF and radar signals in real time. Awardee(s) will validate the performance of the neuromorphic hardware in terms of power consumption and timing latency. Awardee(s) will confirm that the outputs are deterministic and compare favorably to the expected values from the M&S environment. PHASE III DUAL USE APPLICATIONS: The awardee(s) will identify potential commercial and dual use neuromorphic applications for the IoT such as MIMO adaptive beamforming. REFERENCES: C. Xiao, J. Chen, and L. Wang, "Optimal Mapping of Spiking Neural Network to Neuromorphic Hardware for Edge-AI," Sensors, vol. 22, no. 19, p. 7248, 2022. A. Baietto, J. Boubin, P. Farr, T. J. Bihl, A. M. Jones, and C. Stewart, "Lean neural networks for autonomous radar waveform design," Sensors, vol. 22, no. 4, p. 1317, 2022. P. Farr, A. M. Jones, T. Bihl, J. Boubin, and A. DeMange, "Waveform design implemented on neuromorphic hardware," in 2020 IEEE International Radar Conference (RADAR), 2020, pp. 934-939: IEEE. M. Barnell, C. Raymond, M. Wilson, D. Isereau, and C. Cicotta, "Target classification in synthetic aperture radar and optical imagery using loihi neuromorphic hardware," in 2020 IEEE High Performance Extreme Computing Conference (HPEC), 2020, pp. 1-6: IEEE. C. D. Schuman, S. R. Kulkarni, M. Parsa, J. P. Mitchell, P. Date, and B. Kay, "Opportunities for neuromorphic computing algorithms and applications," Nature Computational Science, vol. 2, no. 1, pp. 10-19, 2022. (2023). RFView Family of Digital Engineering Tools. Available: https://www.islinc.com/products/rfview; KEYWORDS: AI; Neuromorphic computing; Low C-SWAP; Embedded processing
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Overview​

Agency

Department of the Air Force (USAF) [DoD]
Response Deadline
June 12, 2024 Past Due
Posted
April 17, 2024
Open
May 15, 2024
Set Aside
Small Business (SBA)
NAICS
541715 - Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)
PSC
AC32 - National Defense R&D Services; Defense-Related Activities; Applied Research
Place of Performance
Not Provided
Source
SBIR
Alt Source
SBIR Agency Source

---

Program
SBIR Phase I / II
Structure
Contract
Phase Detail
Phase I: Establish the technical merit, feasibility, and commercial potential of the proposed R/R&D efforts and determine the quality of performance of the small business awardee organization.
Phase II: Continue the R/R&D efforts initiated in Phase I. Funding is based on the results achieved in Phase I and the scientific and technical merit and commercial potential of the project proposed in Phase II. Typically, only Phase I awardees are eligible for a Phase II award
Duration
6 Months - 1 Year
Size Limit
500 Employees

DoD Doc