Well if we are not going to talk about it then let’s all see it-
please open up the link and check it / read it and see it-remember with the MERCEDES scenario- the CEO said “it is something he cannot talk about”
CNN RNN Processor
FIRM: SILICON SPACE TECHNOLOGY CORPORATION PI: Jim Carlquist Proposal #:H6.22-4509
NON-PROPRIETARY DATA
Objectives
The goal of this project is the creation of a radiation-hardened Spiking Neural Network (SNN) SoC based on the BrainChip Akida Neuron Fabric IP. Akida is a member of a small set of existing SNN architectures structured to more closely emulate computation in a human brain. The rationale for using a Spiking Neural Network (SNN) for Edge AI Computing is because of its efficiencies. The neurmorphic approach used in the Akida architecture takes fewer MACs per operation since it creates and uses sparsity of both weights and activation by its event-based model. In addition, Akida reduces memory consumption by quantizing and compressing network parameters. This also helps to reduce power consumption and die size while maintaining performance.
Spiking Neural Network Block Diagram
ACCOMPLISHMENTS
Notable Deliverables Provided
• Design and Manufacturing Plans
• Radiation Testing Plan (included in Final report)
• Technical final report
Key Milestones Met
• Understand Akida Architecture
• Understand 28nm Implementation
• Evaluate Radiation Vulnerability of the IP Through the Akida
Development Environment
• Define Architecture of Target IC
• Define how HARDSIL® will be used in Target IC
• Create Design and Manufacturing Plans
• Define the Radiation Testing Plan to Establish the Radiation
Robustness of the IC
FUTURE PLANNED DEVELOPMENTS
Planned Post-Phase II Partners
We received five Letters of Support for this project. Two of which will provide capital infusion to keep the project going, one for aid in radiation testing, and the final two for use in future space flights.
Planned/Possible Mission Infusion
NASA is keen to increase the performance of its autonomous rovers to allow for greater speeds. Current routing methodologies limit speeds to 4cm/sec while NASA has a goal to be able to have autonomous rovers traverse at speeds up to 20km/hr. Early calculations show the potential for this device to process several of the required neural network algorithms fast enough to meet this goal.
Planned/Possible Mission Commercialization
A detailed plan is included in the Phase I final submittal to commercialized a RADHARD flight ready QML, SNN SoC to be available for NASA and commercial use.
View attachment 10797
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AKIDA BALLISTA UBQTS