I know all the new shareholders have done all of their own...

I know all the new shareholders have done all of their own research and of course know everything about Brainchip that an investor/shareholder would want to know so this post is not for those investor/shareholders. On the off chance that there is someone about to buy or someone who turned two pages and missed out the history related to NASA and Brainchip I thought the following might be useful.

If you have read in various posts that while NASA was announced officially as an EAP customer on the ASX on 23 December, 2020 that it is widely believed by shareholders that Brainchip and NASA were known to each other from as early as 2019 the following extract taken from the provided NASA SBIR in 2019 provides some of the explanation for this belief:

https://sbir.nasa.gov/printpdf/61636

"NASA SBIR 2019 Phase I Solicitation

H6.22 Deep Neural Net and Neuromorphic Processors for In-SpaceAutonomy and Cognition

The goal of this subtopic is to develop deep neural net and neuromorphic processing hardware, software, algorithms, architectures, simulators, and techniques as an enabling capability for autonomy in the space environment. Additional areas of interest for research and/or technology development include:

Deep neural net and neuromorphic processing approaches to enhance data processing, computing performance, and memory conservation.

Spiking neural net algorithms that learn from the environmentand improve operations.
New brain-inspired chips and breakthroughs in machineunderstanding and intelligence.

Novel memristor, MRAM, and other radiation tolerant devices that can be incorporated in neuromorphic processors which show promise for space applications.

This subtopic seeks innovations focusing on low size, weight, and power (SWaP) processing suitable for CubeSat operations or direct integration with sensors in the harsh space environment. Focusing on SWaP-constrained platforms opens the potential for applying neuromorphic processors in spacecraft control situations traditionally reserved for power-hungry general-purpose processors. This technology will allow for increased speed, energy efficiency, and higher performance for computing in unknown and uncharacterized space environments.

Background, State of the Art, and References

The current state-of-the-art (SOA) for in-space processing is the High-Performance Spaceflight Computing (HPSC) processor being developed by Boeing for NASA Goddard Space Flight Center (GSFC). The HPSC, called the Chiplet, contains 8 general purpose processing cores in a dual quad-core configuration; initial hardware delivery is expected by December 2020. In a submission to the Space Technology Mission Directorate (STMD) Game Changing Development (GCD) program, the highest computational capability required by current typical space mission is 35-70 GFLOPS (billion floating-point operations per second).

The current SOA does not address the capabilities required forartificial intelligence and machine inferencing and learning applications inthe space environment. These applications require significant amounts of multiply and accumulate operations, in addition to a substantial amount of memory to store data and retain intermediate states in a neural network computation. Terrestrially, these operations require general-purpose graphics processing units (GP-GPUs), which are capable of TFLOPS (1012) -- approximately 3 orders of magnitude above the anticipated capabilities of the HPSC.

Neuromorphic processing offers the potential to bridge this gapthrough novel hardware approaches. Existing research in the area showsneuromorphic processors to be up to 1000 times more energy efficient thanGP-GPUs in artificial intelligence applications. Obviously, the true performance depends on the application, but nevertheless neuromorphic processing has demonstrated characteristics that make it well adapted to the power-constrained space environment. Neuromorphic computing is a technology to tackle the explosion in computing performance and memory requirements to meet growing demands for artificial intelligence and machine learning.

While the commercial market for these processors is in itsinfancy, there is a growing community of small businesses that have been fundedby Air Force and Department of Energy grants toward development of neuromorphiccapabilities. These companies continue to make great strides in neuromorphic processor technology including new devices such as memristors. This subtopic would put NASA in a position to join its partners in the DoD and DoE to enable a research area that shows tremendous application for space. The Cognitive Communications Project, through the Human Exploration and Operations Mission Directorate (HEOMD) Space Communications and Navigation (SCaN) Program, is one potential customer of work from this subtopic area.

Neuromorphic processors are a key enabler to the cognitiveradio and system architecture envisioned by this project. As communications become more complex, cognition and automation will play a larger role to mitigate complexity and reduce operations costs. Machine learning will choose radio configurations, adjust for impairments and failures. Neuromorphic processors will address the power requirements that traditional computing architectures now struggle to meet."

My opinion only DYOR
FF

AKIDA BALLISTA