BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
It's because it has the words "edge" and 'box" used in the same context. This is LSTM. Long Skip can do the same with greater separation of the words.I think DK is right, for at least one of those..
Interesting though.. I tried Googling "box on the edge" for an image of an "ordinary box" sitting on the edge of a table or something (to have a dig) and BrainChip's Edge Box, is on the first page of the search, on both Google and Firefox.
View attachment 75421
Is this because of the number of people Googling about the AKIDA Edge Box, or just the "algorithm" tuned to my search preferences?..
I guess no one "here" will know..
Ethinvestor
Regular
Is there a link so we can watch it too? Thx
HopalongPetrovski
I'm Spartacus!
Yes, yes, yes. But just exactly how much longer will my fleet of Fembot's be? hmmmmmm?
supersonic001
Regular
BrainChip on LinkedIn: #ces2025 #edgeai #innovation #akida
What an Incredible Day 1 at CES 2025! The BrainChip Suite in the Venetian Tower was buzzing with energy. We showcased live demos highlighting how Akida is…
Fullmoonfever
Top 20
Wonder if we'll get an intro to these guys as some point. Co funded by the EU and have also participated in space programs with ESA and NASA.
Like to think someone at ESA may discuss us with them sometime?
www.arquimea.com
www.arquimea.com
December 23, 2024
Neuromorphic vision is a field that draws on the workings of the human visual system to develop electronic systems that process visual information efficiently and in real time. This approach uses sensors and algorithms designed to mimic the biological properties of the eye and brain.
Instead of capturing data in fixed frames like traditional cameras, neuromorphic sensors record individual events (changes in light intensity) at each pixel. This makes them highly efficient in terms of energy consumption and processing speed.
– Robotics: enabling improved visual perception of robots for navigation and manipulation in complex environments.
– Autonomous driving: enables fast and efficient detection of both objects and obstacles.
– Medical devices: supports some technologies such as visual prostheses or biomedical analysis.
– Security and surveillance: provides highly accurate real-time detection of suspicious movements and critical events.
– Industry and automation: aiding quality inspection systems, tracking objects on assembly lines, and industrial IoT systems.
The combination of neuromorphic vision and AI will transform the way machines perceive and understand the environment, bringing them closer to human biological processing.
– Development of specialised hardware: neuromorphic sensors require advanced chips that mimic the neural activity of the brain, which are expensive and technically complex to manufacture.
– Unconventional data processing: instead of conventional images, neuromorphic sensors generate data in event format, which requires specific algorithms and new paradigms to interpret the data.
– Specialised learning algorithms: New algorithms, such as spiking neural networks (SNNs), are needed that are compatible with the asynchronous and event-driven nature of the data.
– Scalability: Algorithms and systems need to be scalable for large-scale applications, which has not yet been fully achieved.
– Lack of expertise and training: There are few experts in neuromorphic vision, and it takes time and resources to build technical teams.
In summary, neuromorphic vision has transformative potential in multiple industries. Its implementation is strategic for companies seeking technological advantage in artificial intelligence applications.
In addition, all ARQUIMEA Research Center projects belong to the QCIRCLE project, co-funded by the European Union, which aims to create a center of scientific excellence in Spain
Like to think someone at ESA may discuss us with them sometime?
Exploring the future of the Space sector
In this article we explore the challenges the space sector will face in the coming years, as well as the trends, direction and future of the space sector.
www.arquimea.com
Spanish technology for the European XFEL, the world's most important scientific X-ray facility
Neuromorphic vision is a field that draws on the workings of the human visual system to develop electronic systems that process visual information efficiently and in real time.
www.arquimea.com
What are the challenges of implementing neuromorphic vision in AI?
TrendsDecember 23, 2024
Neuromorphic vision is a field that draws on the workings of the human visual system to develop electronic systems that process visual information efficiently and in real time. This approach uses sensors and algorithms designed to mimic the biological properties of the eye and brain.
Instead of capturing data in fixed frames like traditional cameras, neuromorphic sensors record individual events (changes in light intensity) at each pixel. This makes them highly efficient in terms of energy consumption and processing speed.
Origins of Neuromorphic Vision
The term ‘neuromorphic’ was coined by Carver Mead in the 1980s. Mead, a pioneer in microelectronics, proposed to design electronic systems inspired by the structure and function of the human brain. Since then, research in neuromorphic sensors has evolved, with key milestones such as the development of event cameras (e.g. Dynamic Vision Sensor, DVS) that mimic the behaviour of the human eye.Relationship with Artificial Intelligence (AI)
Neuromorphic vision is closely linked to AI, providing highly optimised and relevant data for the training and execution of deep learning and machine learning algorithms. Some of its main contributions are:- Real-time processing: data obtained from neuromorphic sensors allows AI models to react immediately, useful in applications such as autonomous driving and robotics.
- Energy efficiency: neuromorphic vision significantly reduces energy consumption compared to traditional cameras, improving the sustainability of AI-based applications.
- Non-redundant data: event-specific detection allows AI systems to work with non-redundant data, improving accuracy in tasks such as object recognition or navigation.
Current and Future Impact
The implementation of neuromorphic vision is highly recommended in sectors where low latency and energy efficiency are essential and robust real-time event processing is required. Therefore, neuromorphic vision has promising applications in sectors such as:– Robotics: enabling improved visual perception of robots for navigation and manipulation in complex environments.
– Autonomous driving: enables fast and efficient detection of both objects and obstacles.
– Medical devices: supports some technologies such as visual prostheses or biomedical analysis.
– Security and surveillance: provides highly accurate real-time detection of suspicious movements and critical events.
– Industry and automation: aiding quality inspection systems, tracking objects on assembly lines, and industrial IoT systems.
The combination of neuromorphic vision and AI will transform the way machines perceive and understand the environment, bringing them closer to human biological processing.
What are the challenges of implementing neuromorphic vision in AI?
Implementing neuromorphic vision in artificial intelligence presents several challenges, whether technical, economic or practical:– Development of specialised hardware: neuromorphic sensors require advanced chips that mimic the neural activity of the brain, which are expensive and technically complex to manufacture.
– Unconventional data processing: instead of conventional images, neuromorphic sensors generate data in event format, which requires specific algorithms and new paradigms to interpret the data.
– Specialised learning algorithms: New algorithms, such as spiking neural networks (SNNs), are needed that are compatible with the asynchronous and event-driven nature of the data.
– Scalability: Algorithms and systems need to be scalable for large-scale applications, which has not yet been fully achieved.
– Lack of expertise and training: There are few experts in neuromorphic vision, and it takes time and resources to build technical teams.
In summary, neuromorphic vision has transformative potential in multiple industries. Its implementation is strategic for companies seeking technological advantage in artificial intelligence applications.
Neuromorphic Vision and Artificial Intelligence in ARQUIMEA
ARQUIMEA, from its research center located in the Canary Islands, has a research orbital dedicated to robotics and another to Artificial Intelligence that develops projects that explore the potential of neuromorphic vision.In addition, all ARQUIMEA Research Center projects belong to the QCIRCLE project, co-funded by the European Union, which aims to create a center of scientific excellence in Spain
then I thought wow an announcement 
Humble Genius
Regular
I was contemplating $6.78, but I'm trying to be realistic.
Bravo
If ARM was an arm, BRN would be its biceps💪!
Hey Gang!
I took some time out from my undercover ops - hiding behind pot plants at CES 2025, to do some reading and stumbled upon this NASA article published yesterday.
From the areas I've highlighted in orange, you can see that NASA's recently updated inventory consists of a few AI use cases describing autonomous navigation for the Perseverance Rover on Mars. I hadn't heard the term "Mars2020 Rover" referenced before and so I searched for it on TSEx and sure enough nothing came up.
What I thought of immediately was the 2020 SBIR, which I have posted below for your convenience, which described how AKIDA was to potentially be utilised to make autonomous rovers travel faster. So it occurred to me that this 2020 SBIR which AKIDA was featured in might be part of the whole "Mars2020 Rover" thingamajig.
I had a quick Google search under "Mars2020 Rover" and I found this NASA Fact Sheet from 2019. The second page states "A new autonomous navigation system will allow the rover to drive faster in challenging terrain", which 100% ties into the goals described in the 2020 SBIR!
Oh, and I might as well also add that the whole NASA High Performance Spaceflight Computer (HPSC) that I've been so obsessed about and in which I'm convinced our tech will be incorporated into at some point in time, well... the HPSC runs the software that controls the spacecraft's various subsystems, such as navigation, communication, power management, etc.
The HPSC processor which is being built by Microchip and will be utilising SiFive's 'Intelligence' X280 core. NASA has stated previously that initial availability will be sometime in 2024 (which didn't occur obviously, so maybe it will be ready this year) and the chip won't just be for space missions but is also expected to be utilised in applications on Earth such as defense, commercial aviation, robotics and medical equipment.
Article
NASA’s 2024 AI Use Case inventory highlights the agency’s commitment to integrating artificial intelligence in its space missions and operations. The agency’s updated inventory consists of active AI use cases, ranging from AI-driven autonomous space operations, such as navigation for the Perseverance Rover on Mars, to advanced data analysis for scientific discovery.
By maintaining a strong commitment to both technological innovation and ethical responsibility, NASA is not only advancing space exploration but also setting an industry standard for the responsible use of artificial intelligence in scientific and space-related endeavors.
Mars2020 Fact Sheet
www.nasa.gov
I took some time out from my undercover ops - hiding behind pot plants at CES 2025, to do some reading and stumbled upon this NASA article published yesterday.
From the areas I've highlighted in orange, you can see that NASA's recently updated inventory consists of a few AI use cases describing autonomous navigation for the Perseverance Rover on Mars. I hadn't heard the term "Mars2020 Rover" referenced before and so I searched for it on TSEx and sure enough nothing came up.
What I thought of immediately was the 2020 SBIR, which I have posted below for your convenience, which described how AKIDA was to potentially be utilised to make autonomous rovers travel faster. So it occurred to me that this 2020 SBIR which AKIDA was featured in might be part of the whole "Mars2020 Rover" thingamajig.
I had a quick Google search under "Mars2020 Rover" and I found this NASA Fact Sheet from 2019. The second page states "A new autonomous navigation system will allow the rover to drive faster in challenging terrain", which 100% ties into the goals described in the 2020 SBIR!
Oh, and I might as well also add that the whole NASA High Performance Spaceflight Computer (HPSC) that I've been so obsessed about and in which I'm convinced our tech will be incorporated into at some point in time, well... the HPSC runs the software that controls the spacecraft's various subsystems, such as navigation, communication, power management, etc.
The HPSC processor which is being built by Microchip and will be utilising SiFive's 'Intelligence' X280 core. NASA has stated previously that initial availability will be sometime in 2024 (which didn't occur obviously, so maybe it will be ready this year) and the chip won't just be for space missions but is also expected to be utilised in applications on Earth such as defense, commercial aviation, robotics and medical equipment.
NASA’s AI Use Cases: Advancing Space Exploration with Responsibility
Kate Halloran
Jan 07, 2025Article
Contents
NASA's 2024 AI Use Case inventory highlights the agency’s commitment to integrating artificial intelligence in its space missions and operations. The agency’s updated inventory consists of active AI use cases, ranging from AI-driven autonomous space operations, such as navigation for the Perseverance Rover on Mars, to advanced data analysis for scientific discovery.NASA’s 2024 AI Use Case inventory highlights the agency’s commitment to integrating artificial intelligence in its space missions and operations. The agency’s updated inventory consists of active AI use cases, ranging from AI-driven autonomous space operations, such as navigation for the Perseverance Rover on Mars, to advanced data analysis for scientific discovery.
AI Across NASA
NASA’s use of AI is diverse and spans several key areas of its missions:Autonomous Exploration and Navigation
- AEGIS (Autonomous Exploration for Gathering Increased Science): AI-powered system designed to autonomously collect scientific data during planetary exploration.
- Enhanced AutoNav for Perseverance Rover: Utilizes advanced autonomous navigation for Mars exploration, enabling real-time decision-making.
- MLNav (Machine Learning Navigation): AI-driven navigation tools to enhance movement across challenging terrains.
- Perseverance Rover on Mars – Terrain Relative Navigation: AI technology supporting the rover’s navigation across Mars, improving accuracy in unfamiliar terrain.
Mission Planning and Management
- ASPEN Mission Planner: AI-assisted tool that helps streamline space mission planning and scheduling, optimizing mission efficiency.
- AWARE (Autonomous Waiting Room Evaluation): AI system that manages operational delays, improving mission scheduling and resource allocation.
- CLASP (Coverage Planning & Scheduling): AI tools for resource allocation and scheduling, ensuring mission activities are executed seamlessly.
- Onboard Planner for Mars2020 Rover: AI system that helps the Perseverance Rover autonomously plan and schedule its tasks during its mission.
Environmental Monitoring and Analysis
- SensorWeb for Environmental Monitoring: AI-powered system used to monitor environmental factors such as volcanoes, floods, and wildfires on Earth and beyond.
- Volcano SensorWeb: Similar to SensorWeb, but specifically focused on volcanic activity, leveraging AI to enhance monitoring efforts.
- Global, Seasonal Mars Frost Maps: AI-generated maps to study seasonal variations in Mars’ atmosphere and surface conditions.
Data Management and Automation
- NASA OCIO STI Concept Tagging Service: AI tools that organize and tag NASA’s scientific data, making it easier to access and analyze.
- Purchase Card Management System (PCMS): AI-assisted system for streamlining NASA’s procurement processes and improving financial operations.
Aerospace and Air Traffic Control
- NextGen Methods for Air Traffic Control: AI tools to optimize air traffic control systems, enhancing efficiency and reducing operational costs.
- NextGen Data Analytics: Letters of Agreement: AI-driven analysis of agreements within air traffic control systems, improving management and operational decision-making.
Space Exploration
- Mars2020 Rover (Perseverance): AI systems embedded within the Perseverance Rover to support its mission to explore Mars.
- SPOC (Soil Property and Object Classification): AI-based classification system used to analyze soil and environmental features, particularly for Mars exploration.
Ethical AI: NASA’s Responsible Approach
NASA ensures that all AI applications adhere to Responsible AI (RAI) principles outlined by the White House in its Executive Order 13960. This includes ensuring AI systems are transparent, accountable, and ethical. The agency integrates these principles into every phase of development and deployment, ensuring AI technologies used in space exploration are both safe and effective.Looking Forward: AI’s Expanding Role
As AI technologies evolve, NASA’s portfolio of AI use cases will continue to grow. With cutting-edge tools currently in development, the agency is poised to further integrate AI into more aspects of space exploration, from deep space missions to sustainable solutions for planetary exploration.By maintaining a strong commitment to both technological innovation and ethical responsibility, NASA is not only advancing space exploration but also setting an industry standard for the responsible use of artificial intelligence in scientific and space-related endeavors.
Mars2020 Fact Sheet
NASA's AI Use Cases: Advancing Space Exploration with Responsibility - NASA
NASA's 2024 AI Use Case inventory highlights the agency’s commitment to integrating artificial intelligence in its space missions and operations. The agency’s updated inventory consists of active AI use cases, ranging from AI-driven autonomous space operations, such as navigation for the...
www.nasa.gov
Last edited:
supersonic001
Regular
Agree
MD, otherwise….. another Prophesee potential ….. is anyone keeping up………..
DingoBorat
Slim
FactFinder was all over this while on the crapper, Bravo.Hey Gang!
I took some time out from my undercover ops - hiding behind pot plants at CES 2025, to do some reading and stumbled upon this NASA article published yesterday.
From the areas I've highlighted in orange, you can see that NASA's recently updated inventory consists of a few AI use cases describing autonomous navigation for the Perseverance Rover on Mars. I hadn't heard the term "Mars2020 Rover" referenced before and so I searched for it on TSEx and sure enough nothing came up.
What I thought of immediately was the 2020 SBIR, which I have posted below for your convenience, which described how AKIDA was to potentially be utilised to make autonomous rovers travel faster. So it occurred to me that this 2020 SBIR which AKIDA was featured in might be part of the whole "Mars2020 Rover" thingamajig.
I had a quick Google search under "Mars2020 Rover" and I found this NASA Fact Sheet from 2019. The second page states "A new autonomous navigation system will allow the rover to drive faster in challenging terrain", which 100% ties into the goals described in the 2020 SBIR!
Oh, and I might as well also add that the whole NASA High Performance Spaceflight Computer (HPSC) that I've been so obsessed about and in which I'm convinced our tech will be incorporated into at some point in time, well... the HPSC runs the software that controls the spacecraft's various subsystems, such as navigation, communication, power management, etc.
The HPSC processor which is being built by Microchip and will be utilising SiFive's 'Intelligence' X280 core. NASA has stated previously that initial availability will be sometime in 2024 (which didn't occur obviously, so maybe it will be ready this year) and the chip won't just be for space missions but is also expected to be utilised in applications on Earth such as defense, commercial aviation, robotics and medical equipment.
NASA’s AI Use Cases: Advancing Space Exploration with Responsibility
Kate Halloran
Jan 07, 2025
Article
Contents
NASA's 2024 AI Use Case inventory highlights the agency’s commitment to integrating artificial intelligence in its space missions and operations. The agency’s updated inventory consists of active AI use cases, ranging from AI-driven autonomous space operations, such as navigation for the Perseverance Rover on Mars, to advanced data analysis for scientific discovery.
NASA’s 2024 AI Use Case inventory highlights the agency’s commitment to integrating artificial intelligence in its space missions and operations. The agency’s updated inventory consists of active AI use cases, ranging from AI-driven autonomous space operations, such as navigation for the Perseverance Rover on Mars, to advanced data analysis for scientific discovery.
AI Across NASA
NASA’s use of AI is diverse and spans several key areas of its missions:
Autonomous Exploration and Navigation
- AEGIS (Autonomous Exploration for Gathering Increased Science): AI-powered system designed to autonomously collect scientific data during planetary exploration.
- Enhanced AutoNav for Perseverance Rover: Utilizes advanced autonomous navigation for Mars exploration, enabling real-time decision-making.
- MLNav (Machine Learning Navigation): AI-driven navigation tools to enhance movement across challenging terrains.
- Perseverance Rover on Mars – Terrain Relative Navigation: AI technology supporting the rover’s navigation across Mars, improving accuracy in unfamiliar terrain.
Mission Planning and Management
- ASPEN Mission Planner: AI-assisted tool that helps streamline space mission planning and scheduling, optimizing mission efficiency.
- AWARE (Autonomous Waiting Room Evaluation): AI system that manages operational delays, improving mission scheduling and resource allocation.
- CLASP (Coverage Planning & Scheduling): AI tools for resource allocation and scheduling, ensuring mission activities are executed seamlessly.
- Onboard Planner for Mars2020 Rover: AI system that helps the Perseverance Rover autonomously plan and schedule its tasks during its mission.
Environmental Monitoring and Analysis
- SensorWeb for Environmental Monitoring: AI-powered system used to monitor environmental factors such as volcanoes, floods, and wildfires on Earth and beyond.
- Volcano SensorWeb: Similar to SensorWeb, but specifically focused on volcanic activity, leveraging AI to enhance monitoring efforts.
- Global, Seasonal Mars Frost Maps: AI-generated maps to study seasonal variations in Mars’ atmosphere and surface conditions.
Data Management and Automation
- NASA OCIO STI Concept Tagging Service: AI tools that organize and tag NASA’s scientific data, making it easier to access and analyze.
- Purchase Card Management System (PCMS): AI-assisted system for streamlining NASA’s procurement processes and improving financial operations.
Aerospace and Air Traffic Control
- NextGen Methods for Air Traffic Control: AI tools to optimize air traffic control systems, enhancing efficiency and reducing operational costs.
- NextGen Data Analytics: Letters of Agreement: AI-driven analysis of agreements within air traffic control systems, improving management and operational decision-making.
Space Exploration
- Mars2020 Rover (Perseverance): AI systems embedded within the Perseverance Rover to support its mission to explore Mars.
- SPOC (Soil Property and Object Classification): AI-based classification system used to analyze soil and environmental features, particularly for Mars exploration.
Ethical AI: NASA’s Responsible Approach
NASA ensures that all AI applications adhere to Responsible AI (RAI) principles outlined by the White House in its Executive Order 13960. This includes ensuring AI systems are transparent, accountable, and ethical. The agency integrates these principles into every phase of development and deployment, ensuring AI technologies used in space exploration are both safe and effective.
Looking Forward: AI’s Expanding Role
As AI technologies evolve, NASA’s portfolio of AI use cases will continue to grow. With cutting-edge tools currently in development, the agency is poised to further integrate AI into more aspects of space exploration, from deep space missions to sustainable solutions for planetary exploration.
By maintaining a strong commitment to both technological innovation and ethical responsibility, NASA is not only advancing space exploration but also setting an industry standard for the responsible use of artificial intelligence in scientific and space-related endeavors.
View attachment 75442
Mars2020 Fact Sheet
View attachment 75443
View attachment 75444
NASA's AI Use Cases: Advancing Space Exploration with Responsibility - NASA
NASA's 2024 AI Use Case inventory highlights the agency’s commitment to integrating artificial intelligence in its space missions and operations. The agency’s updated inventory consists of active AI use cases, ranging from AI-driven autonomous space operations, such as navigation for the...
The posts pre-date this forum.
Or else it's because he scrubbed his account on this one.
It "was" us which were able to make the rover more than 10 times faster or something, it was literally a "crawl" before and they were even thinking of changing the name, to the Mars snail.
Good to see things are still progressing.
Last edited:
Philippe Coeurdevey on LinkedIn: #ai
BrainChip Unveils Edge #AI Box Partner Ecosystem for Gestures, Cybersecurity, Image Recognition, and Computer Vision https://lnkd.in/dGJijUmv
BrainChip Unveils Edge AI Box Partner Ecosystem for Gestures, Cybersecurity, Image Recognition, and Computer Vision
BrainChip today announced an all-star lineup of partners developing revolutionary technology demonstrations and products with the Akida™ Edge AI Box, a compact, cost-effective appliance with AI/ML processing power for a wide variety of markets such as manufacturing, warehouse, retail, hospitals...
Samsung’s smart fridges will use AI to suggest groceries to buy on Instacart
More milk, please.
Chandra Maloo on LinkedIn: Samsung’s smart fridges will use AI to suggest groceries to buy on…
Back in 2019 our team always discussed grocery replenishment as the natural next step for AI Vision Inside technology in Samsung Family Hub refrigerators…
Pom down under
Top 20
Make itOh, only 5 times or so
BrainChip Unveils Edge AI Box Partner Ecosystem for Gestures, Cybersecurity, Image Recognition, and Computer Vision
BrainChip Unveils Edge AI Box Partner Ecosystem for Gestures, Cybersecurity, Image Recognition, and Computer Vision Laguna Hills, Calif. – January 7th, 2025 – BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power, fully digital...
brainchip.com
CHIPS
Regular
Hey Gang!
I took some time out from my undercover ops - hiding behind pot plants at CES 2025, to do some reading and stumbled upon this NASA article published yesterday.
From the areas I've highlighted in orange, you can see that NASA's recently updated inventory consists of a few AI use cases describing autonomous navigation for the Perseverance Rover on Mars. I hadn't heard the term "Mars2020 Rover" referenced before and so I searched for it on TSEx and sure enough nothing came up.
What I thought of immediately was the 2020 SBIR, which I have posted below for your convenience, which described how AKIDA was to potentially be utilised to make autonomous rovers travel faster. So it occurred to me that this 2020 SBIR which AKIDA was featured in might be part of the whole "Mars2020 Rover" thingamajig.
I had a quick Google search under "Mars2020 Rover" and I found this NASA Fact Sheet from 2019. The second page states "A new autonomous navigation system will allow the rover to drive faster in challenging terrain", which 100% ties into the goals described in the 2020 SBIR!
Oh, and I might as well also add that the whole NASA High Performance Spaceflight Computer (HPSC) that I've been so obsessed about and in which I'm convinced our tech will be incorporated into at some point in time, well... the HPSC runs the software that controls the spacecraft's various subsystems, such as navigation, communication, power management, etc.
The HPSC processor which is being built by Microchip and will be utilising SiFive's 'Intelligence' X280 core. NASA has stated previously that initial availability will be sometime in 2024 (which didn't occur obviously, so maybe it will be ready this year) and the chip won't just be for space missions but is also expected to be utilised in applications on Earth such as defense, commercial aviation, robotics and medical equipment.
NASA’s AI Use Cases: Advancing Space Exploration with Responsibility
Kate Halloran
Jan 07, 2025
Article
Contents
NASA's 2024 AI Use Case inventory highlights the agency’s commitment to integrating artificial intelligence in its space missions and operations. The agency’s updated inventory consists of active AI use cases, ranging from AI-driven autonomous space operations, such as navigation for the Perseverance Rover on Mars, to advanced data analysis for scientific discovery.
NASA’s 2024 AI Use Case inventory highlights the agency’s commitment to integrating artificial intelligence in its space missions and operations. The agency’s updated inventory consists of active AI use cases, ranging from AI-driven autonomous space operations, such as navigation for the Perseverance Rover on Mars, to advanced data analysis for scientific discovery.
AI Across NASA
NASA’s use of AI is diverse and spans several key areas of its missions:
Autonomous Exploration and Navigation
- AEGIS (Autonomous Exploration for Gathering Increased Science): AI-powered system designed to autonomously collect scientific data during planetary exploration.
- Enhanced AutoNav for Perseverance Rover: Utilizes advanced autonomous navigation for Mars exploration, enabling real-time decision-making.
- MLNav (Machine Learning Navigation): AI-driven navigation tools to enhance movement across challenging terrains.
- Perseverance Rover on Mars – Terrain Relative Navigation: AI technology supporting the rover’s navigation across Mars, improving accuracy in unfamiliar terrain.
Mission Planning and Management
- ASPEN Mission Planner: AI-assisted tool that helps streamline space mission planning and scheduling, optimizing mission efficiency.
- AWARE (Autonomous Waiting Room Evaluation): AI system that manages operational delays, improving mission scheduling and resource allocation.
- CLASP (Coverage Planning & Scheduling): AI tools for resource allocation and scheduling, ensuring mission activities are executed seamlessly.
- Onboard Planner for Mars2020 Rover: AI system that helps the Perseverance Rover autonomously plan and schedule its tasks during its mission.
Environmental Monitoring and Analysis
- SensorWeb for Environmental Monitoring: AI-powered system used to monitor environmental factors such as volcanoes, floods, and wildfires on Earth and beyond.
- Volcano SensorWeb: Similar to SensorWeb, but specifically focused on volcanic activity, leveraging AI to enhance monitoring efforts.
- Global, Seasonal Mars Frost Maps: AI-generated maps to study seasonal variations in Mars’ atmosphere and surface conditions.
Data Management and Automation
- NASA OCIO STI Concept Tagging Service: AI tools that organize and tag NASA’s scientific data, making it easier to access and analyze.
- Purchase Card Management System (PCMS): AI-assisted system for streamlining NASA’s procurement processes and improving financial operations.
Aerospace and Air Traffic Control
- NextGen Methods for Air Traffic Control: AI tools to optimize air traffic control systems, enhancing efficiency and reducing operational costs.
- NextGen Data Analytics: Letters of Agreement: AI-driven analysis of agreements within air traffic control systems, improving management and operational decision-making.
Space Exploration
- Mars2020 Rover (Perseverance): AI systems embedded within the Perseverance Rover to support its mission to explore Mars.
- SPOC (Soil Property and Object Classification): AI-based classification system used to analyze soil and environmental features, particularly for Mars exploration.
Ethical AI: NASA’s Responsible Approach
NASA ensures that all AI applications adhere to Responsible AI (RAI) principles outlined by the White House in its Executive Order 13960. This includes ensuring AI systems are transparent, accountable, and ethical. The agency integrates these principles into every phase of development and deployment, ensuring AI technologies used in space exploration are both safe and effective.
Looking Forward: AI’s Expanding Role
As AI technologies evolve, NASA’s portfolio of AI use cases will continue to grow. With cutting-edge tools currently in development, the agency is poised to further integrate AI into more aspects of space exploration, from deep space missions to sustainable solutions for planetary exploration.
By maintaining a strong commitment to both technological innovation and ethical responsibility, NASA is not only advancing space exploration but also setting an industry standard for the responsible use of artificial intelligence in scientific and space-related endeavors.
View attachment 75442
Mars2020 Fact Sheet
View attachment 75443
View attachment 75444
NASA's AI Use Cases: Advancing Space Exploration with Responsibility - NASA
NASA's 2024 AI Use Case inventory highlights the agency’s commitment to integrating artificial intelligence in its space missions and operations. The agency’s updated inventory consists of active AI use cases, ranging from AI-driven autonomous space operations, such as navigation for the...
The project ended 2021
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...
Frangipani
Regular
Hey Gang!
I took some time out from my undercover ops - hiding behind pot plants at CES 2025, to do some reading and stumbled upon this NASA article published yesterday.
From the areas I've highlighted in orange, you can see that NASA's recently updated inventory consists of a few AI use cases describing autonomous navigation for the Perseverance Rover on Mars. I hadn't heard the term "Mars2020 Rover" referenced before and so I searched for it on TSEx and sure enough nothing came up.
What I thought of immediately was the 2020 SBIR, which I have posted below for your convenience, which described how AKIDA was to potentially be utilised to make autonomous rovers travel faster. So it occurred to me that this 2020 SBIR which AKIDA was featured in might be part of the whole "Mars2020 Rover" thingamajig.
I had a quick Google search under "Mars2020 Rover" and I found this NASA Fact Sheet from 2019. The second page states "A new autonomous navigation system will allow the rover to drive faster in challenging terrain", which 100% ties into the goals described in the 2020 SBIR!
NASA’s AI Use Cases: Advancing Space Exploration with Responsibility
Kate Halloran
Jan 07, 2025
Article
Contents
NASA's 2024 AI Use Case inventory highlights the agency’s commitment to integrating artificial intelligence in its space missions and operations. The agency’s updated inventory consists of active AI use cases, ranging from AI-driven autonomous space operations, such as navigation for the Perseverance Rover on Mars, to advanced data analysis for scientific discovery.
NASA’s 2024 AI Use Case inventory highlights the agency’s commitment to integrating artificial intelligence in its space missions and operations. The agency’s updated inventory consists of active AI use cases, ranging from AI-driven autonomous space operations, such as navigation for the Perseverance Rover on Mars, to advanced data analysis for scientific discovery.
AI Across NASA
NASA’s use of AI is diverse and spans several key areas of its missions:
Autonomous Exploration and Navigation
- AEGIS (Autonomous Exploration for Gathering Increased Science): AI-powered system designed to autonomously collect scientific data during planetary exploration.
- Enhanced AutoNav for Perseverance Rover: Utilizes advanced autonomous navigation for Mars exploration, enabling real-time decision-making.
- MLNav (Machine Learning Navigation): AI-driven navigation tools to enhance movement across challenging terrains.
- Perseverance Rover on Mars – Terrain Relative Navigation: AI technology supporting the rover’s navigation across Mars, improving accuracy in unfamiliar terrain.
Mission Planning and Management
- ASPEN Mission Planner: AI-assisted tool that helps streamline space mission planning and scheduling, optimizing mission efficiency.
- AWARE (Autonomous Waiting Room Evaluation): AI system that manages operational delays, improving mission scheduling and resource allocation.
- CLASP (Coverage Planning & Scheduling): AI tools for resource allocation and scheduling, ensuring mission activities are executed seamlessly.
- Onboard Planner for Mars2020 Rover: AI system that helps the Perseverance Rover autonomously plan and schedule its tasks during its mission.
Environmental Monitoring and Analysis
- SensorWeb for Environmental Monitoring: AI-powered system used to monitor environmental factors such as volcanoes, floods, and wildfires on Earth and beyond.
- Volcano SensorWeb: Similar to SensorWeb, but specifically focused on volcanic activity, leveraging AI to enhance monitoring efforts.
- Global, Seasonal Mars Frost Maps: AI-generated maps to study seasonal variations in Mars’ atmosphere and surface conditions.
Data Management and Automation
- NASA OCIO STI Concept Tagging Service: AI tools that organize and tag NASA’s scientific data, making it easier to access and analyze.
- Purchase Card Management System (PCMS): AI-assisted system for streamlining NASA’s procurement processes and improving financial operations.
Aerospace and Air Traffic Control
- NextGen Methods for Air Traffic Control: AI tools to optimize air traffic control systems, enhancing efficiency and reducing operational costs.
- NextGen Data Analytics: Letters of Agreement: AI-driven analysis of agreements within air traffic control systems, improving management and operational decision-making.
Space Exploration
- Mars2020 Rover (Perseverance): AI systems embedded within the Perseverance Rover to support its mission to explore Mars.
- SPOC (Soil Property and Object Classification): AI-based classification system used to analyze soil and environmental features, particularly for Mars exploration.
Ethical AI: NASA’s Responsible Approach
NASA ensures that all AI applications adhere to Responsible AI (RAI) principles outlined by the White House in its Executive Order 13960. This includes ensuring AI systems are transparent, accountable, and ethical. The agency integrates these principles into every phase of development and deployment, ensuring AI technologies used in space exploration are both safe and effective.
Looking Forward: AI’s Expanding Role
As AI technologies evolve, NASA’s portfolio of AI use cases will continue to grow. With cutting-edge tools currently in development, the agency is poised to further integrate AI into more aspects of space exploration, from deep space missions to sustainable solutions for planetary exploration.
By maintaining a strong commitment to both technological innovation and ethical responsibility, NASA is not only advancing space exploration but also setting an industry standard for the responsible use of artificial intelligence in scientific and space-related endeavors.
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Mars2020 Fact Sheet
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NASA's AI Use Cases: Advancing Space Exploration with Responsibility - NASA
NASA's 2024 AI Use Case inventory highlights the agency’s commitment to integrating artificial intelligence in its space missions and operations. The agency’s updated inventory consists of active AI use cases, ranging from AI-driven autonomous space operations, such as navigation for the...
We can 100% exclude that the 2020 NASA SBIR proposal which featured Akida has anything to do with NASA’s Mars 2020 mission and the Perseverance Mars Rover, given the fact that it embarked on its voyage to the Red Planet on July 30, 2020 (hence the mission name!) and landed on the Martian surface on February 18, 2021…
Apart from the fact that the timelines just don’t match - Perseverance left Planet Earth 4.5 years ago, the same year the SBIR proposal was published, while BrainChip celebrated Akida being first launched into space on March 4, 2024 (in ANT61’s Brain) - the 2020 SBIR proposal itself clearly indicates it is out of the question that it could have anything to do with the Perseverance Mars Rover’s autonomous navigation system: the research project relates to TRL (Technology Readiness Level) 1-2, which is considered very basic and speculative research. I’ll leave it up to you to figure out what TRL would be required for any mission-critical technology destined for Mars…
Technology Readiness Levels - NASA
Technology Readiness Levels (TRL) are a type of measurement system used to assess the maturity level of a particular technology. Each technology project is
www.nasa.gov
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