Taproot
Regular
ASIC Solutions
ASICs are exceptionally well-suited for machine learning tasks that require a lot of computational power, such as deep learning and neural network training.
bascomhunter.com
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
bascomhunter.com
Fullmoonfever
Top 20
Hey DB
@FuzM discovered and kindly posted it yesterday.
We all just went dot joining off the back of that
Though, I think it was maybe @Taproot who highlighted that @uiux was also all over BH early on looking for links.
BRN Discussion Ongoing
Energy is Everything for Edge Computing By Brandon Lucia, CEO & Co-Founder, Efficient 11.28.2024 0 The need for intelligence in the physical world is pushing more sophisticated computation into edge devices. These devices, which previously were simple conduits between a sensor and the cloud...
thestockexchange.com.au
Taproot
Regular
Actually !, to clarify my own post,Hey DB
@FuzM discovered and kindly posted it yesterday.
We all just went dot joining off the back of that
Though, I think it was maybe @Taproot who highlighted that @uiux was also all over BH early on looking for links.
BRN Discussion Ongoing
Energy is Everything for Edge Computing By Brandon Lucia, CEO & Co-Founder, Efficient 11.28.2024 0 The need for intelligence in the physical world is pushing more sophisticated computation into edge devices. These devices, which previously were simple conduits between a sensor and the cloud...
All credit needs to go to @Quatrojos for the original Bascom Hunter dot join.
@uiux started the Bascom thread as well as many other threads to organise his extensive research.
@FuzM put the nail in the coffin.
Taproot
Regular
Just in case you missed it earlier.
bascomhunter.com
ASIC Solutions
ASICs are exceptionally well-suited for machine learning tasks that require a lot of computational power, such as deep learning and neural network training.
bascomhunter.com
Intel news
(Reuters) -Chipmaker Intel said on Monday CEO Pat Gelsinger retired from the chipmaker, effective Dec. 1.
The company named CFO David Zinsner and senior executive Michelle Johnston Holthaus as interim co-chief executive officers while its board conducted a search for a new CEO.
Shares of the company rose nearly 3% in premarket trading.
(Reuters) -Chipmaker Intel said on Monday CEO Pat Gelsinger retired from the chipmaker, effective Dec. 1.
The company named CFO David Zinsner and senior executive Michelle Johnston Holthaus as interim co-chief executive officers while its board conducted a search for a new CEO.
Shares of the company rose nearly 3% in premarket trading.
Fullmoonfever
Top 20
Current ESA project with the "Prime Contractor" at the end. Wonder what neuromorphic Edgx might be using
Approaching the Phase Completion Review stage.
connectivity.esa.int
The proposed activity entails the definition (definition phase) of an onboard neuromorphic AI data processing unit designed for satellite communication (satcom) Low Earth Orbit (LEO) constellations, targeting smallsats. The activity contains three main high level chapters:
Challenges
The key challenges of the project include integrating diverse processing elements into a cohesive system, ensuring high performance with low power consumption, and overcoming the limitations of traditional computing architectures. Addressing the harsh space environment requirements, such as radiation tolerance and reliability, is critical. Developing a flexible and user-friendly framework for rapid customisation and deployment of AI models, achieving real-time data processing and onboard learning, and ensuring the system's robustness against radiation-induced errors are significant hurdles to overcome.
Benefits
The proposed onboard data processing unit offers significant advantages over existing competitor systems. It integrates a flexible, heterogeneous computing platform, combining traditional and neuromorphic processing elements to enhance real-time data processing and reduce latency. This results in a high performance-to-watt ratio and low Size, Weight, and Power (SWaP) characteristics, crucial for space applications. The system's design allows for easy customisation and rapid deployment of AI models, providing superior flexibility. It addresses existing bottlenecks in data processing, ensuring faster, more efficient operations. Overall, the DPU’s robust, reliable performance in space environments sets it apart from current AI processing solutions, offering a competitive edge in satellite communications.
Features
The product includes a high-performance processing system combining traditional and neuromorphic computing elements to ensure efficient and real-time data processing. The modular design allows for flexible and scalable integration into various satellite architectures.
Key components include high-speed and low-speed interfaces for versatile connectivity and dual storage options for handling large data volumes. The system is built to withstand the harsh conditions of space, with robust hardware and software designed for reliability and resilience. The DPU supports easy customisation and rapid deployment of AI models, facilitating continuous updates and improvements. This combination of advanced processing capabilities, flexible design, and robust construction ensures superior performance and adaptability in space applications.
System Architecture
The system architecture to be developed consists of a modular design with two main interconnected boards: the core board and the neuron board. The core board is responsible for handling high-performance computing tasks, while the neuron board focuses on efficient, low-power AI processing. The architecture integrates multiple processing units, including CPUs, GPUs, AI accelerators and NPU’s, to support diverse and intensive computational requirements. It includes various high-speed and low-speed interfaces for flexible connectivity and robust storage solutions to manage large data volumes. Designed to withstand harsh space environments, the system incorporates safety and reliability features. The software framework facilitates easy deployment and updates, ensuring the system can adapt to evolving mission needs and technological advancements.
Plan
The Definition Phase of the project includes two key milestones. The first is the Mid-Term Review, where use cases are analysed, a shortlist is selected and proposed, and a revised set of product requirements along with the DPU architecture is presented. Additionally, a preliminary analysis of neuromorphic processors and algorithms is performed.
The second milestone is the Phase Completion Review, which involves consolidating the business case, proposing the hardware and software architecture for the product, and completing the analysis of the neuromorphic processor. This phase also includes preliminary benchmarking of neuromorphic algorithms and demonstrations of selected use cases.
Current status
The project is approaching the Phase Completion Review. Achievements include the analysis and selection of use cases, a revised set of product requirements, and the initial DPU architecture. Trade-off and selection of neuromorphic processors and algorithms has been conducted, with the overall hardware and software architecture now proposed. The business plan has been consolidated. Preliminary benchmarking of algorithms with demonstrations of selected use cases have been designed.
https://www.edgx.space/
Last update
2024-12-02 13:41
Approaching the Phase Completion Review stage.
Neuromorphic AI Onboard
Our mission is to connect Europe. We join engineers, entrepreneurs and investors to forge strong links between institutions, industries, and businesses.
Neuromorphic AI Onboard
- Status
Ongoing - Status date
2024-10-08
The proposed activity entails the definition (definition phase) of an onboard neuromorphic AI data processing unit designed for satellite communication (satcom) Low Earth Orbit (LEO) constellations, targeting smallsats. The activity contains three main high level chapters:
- Identification of potential neuromorphic satcom applications and scenarios.
- Preliminary benchmarking of neuromorphic algorithms.
- Define the product architecture, user requirements and technical specifications.
- Consolidate user requirements and technical specifications: Gather and refine detailed user requirements and technical specifications to ensure that all stakeholder needs are clearly understood and documented.
- Establish a technical baseline: Develop a foundational technical framework that will serve as the reference point for all subsequent development activities.
- Complete an initial design concept: Create a preliminary design concept that outlines the overall architecture and key components of the product, ensuring alignment with user requirements and technical specifications.
- Assess system-level performance: Evaluate the initial design to identify potential performance issues and areas for improvement, ensuring that the system meets expected performance standards.
- Consolidate the initial business case: Develop and refine the business case for the project, including an analysis of market needs, potential revenue streams, cost estimates, and return on investment projections.
Challenges
The key challenges of the project include integrating diverse processing elements into a cohesive system, ensuring high performance with low power consumption, and overcoming the limitations of traditional computing architectures. Addressing the harsh space environment requirements, such as radiation tolerance and reliability, is critical. Developing a flexible and user-friendly framework for rapid customisation and deployment of AI models, achieving real-time data processing and onboard learning, and ensuring the system's robustness against radiation-induced errors are significant hurdles to overcome.
Benefits
The proposed onboard data processing unit offers significant advantages over existing competitor systems. It integrates a flexible, heterogeneous computing platform, combining traditional and neuromorphic processing elements to enhance real-time data processing and reduce latency. This results in a high performance-to-watt ratio and low Size, Weight, and Power (SWaP) characteristics, crucial for space applications. The system's design allows for easy customisation and rapid deployment of AI models, providing superior flexibility. It addresses existing bottlenecks in data processing, ensuring faster, more efficient operations. Overall, the DPU’s robust, reliable performance in space environments sets it apart from current AI processing solutions, offering a competitive edge in satellite communications.
Features
The product includes a high-performance processing system combining traditional and neuromorphic computing elements to ensure efficient and real-time data processing. The modular design allows for flexible and scalable integration into various satellite architectures.
Key components include high-speed and low-speed interfaces for versatile connectivity and dual storage options for handling large data volumes. The system is built to withstand the harsh conditions of space, with robust hardware and software designed for reliability and resilience. The DPU supports easy customisation and rapid deployment of AI models, facilitating continuous updates and improvements. This combination of advanced processing capabilities, flexible design, and robust construction ensures superior performance and adaptability in space applications.
System Architecture
The system architecture to be developed consists of a modular design with two main interconnected boards: the core board and the neuron board. The core board is responsible for handling high-performance computing tasks, while the neuron board focuses on efficient, low-power AI processing. The architecture integrates multiple processing units, including CPUs, GPUs, AI accelerators and NPU’s, to support diverse and intensive computational requirements. It includes various high-speed and low-speed interfaces for flexible connectivity and robust storage solutions to manage large data volumes. Designed to withstand harsh space environments, the system incorporates safety and reliability features. The software framework facilitates easy deployment and updates, ensuring the system can adapt to evolving mission needs and technological advancements.
Plan
The Definition Phase of the project includes two key milestones. The first is the Mid-Term Review, where use cases are analysed, a shortlist is selected and proposed, and a revised set of product requirements along with the DPU architecture is presented. Additionally, a preliminary analysis of neuromorphic processors and algorithms is performed.
The second milestone is the Phase Completion Review, which involves consolidating the business case, proposing the hardware and software architecture for the product, and completing the analysis of the neuromorphic processor. This phase also includes preliminary benchmarking of neuromorphic algorithms and demonstrations of selected use cases.
Current status
The project is approaching the Phase Completion Review. Achievements include the analysis and selection of use cases, a revised set of product requirements, and the initial DPU architecture. Trade-off and selection of neuromorphic processors and algorithms has been conducted, with the overall hardware and software architecture now proposed. The business plan has been consolidated. Preliminary benchmarking of algorithms with demonstrations of selected use cases have been designed.
Documentation
Documentation may be requestedPrime Contractor
EDGX
Belgiumhttps://www.edgx.space/
Last update
2024-12-02 13:41
Dallas
Regular
Jeff Bezos investiert in Nvidia-Angreifer Tenstorrent - die große Wette
Tenstorrent wird als Angreifer auf die KI-Marktmacht von Nvidia gehandelt. Jetzt investiert Jeff Bezos 700 Millionen Dollar investiert.
Antman0505
Member
Last edited:
I am giving myself a week's ban from the crapper. Total agenda and factless driven abuse over there.Well, I've just performed my late night community service over on the Crapper.
Posted here for posterity since it will, no doubt, have an extremely limited life span over there.
View attachment 73674
Idiocy reins Supreme on the crapper.
Boab
I wish I could paint like Vincent
TheDrooben
Pretty Pretty Pretty Pretty Good
FJ-215
Regular
Morning manny,
More interested in hearing from Sean in the quarterly podcast. Can't be far away!
Dallas
Regular
https://www.edge-ai-vision.com/2024...ssor-to-cost-sensitive-applications-with-new- ra8-entry-line-mcu-groups/
7für7
Top 20
Still holding strong
I will never buy a pizza for 1000 xrp like the dude did with his Bitcoins. By the way, Many people still don’t understand the purpose of a cryptocurrency and treat it like a stock they sell when its value goes up. However, it makes more sense to hold a trusted currency. Would anyone trade their dollars for rupees? Unfathomable.
Last edited:
7für7
Top 20
I won’t let someone like you tell me to keep my mouth shut… Who do you even think you are?
I’ve had enough of you, off to the block list. Congratulations on your multiple investments! I hope you get rich.
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