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JIMMY
WATSON
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His mother, Marion, teases her son about his dreams to build a large robot ant with a
drawing of her son riding on the ant's back. Then it comes true.
AI
- Artificial Intelligence,
is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals.
High-profile applications of AI include advanced web search engines (e.g., Google Search); recommendation systems (used by YouTube, Amazon, and Netflix); virtual assistants (e.g., Google Assistant, Siri, and Alexa); autonomous vehicles (e.g., Waymo); generative and creative tools (e.g., language models and AI art); and superhuman play and analysis in strategy games (e.g., chess and Go). However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labeled AI anymore."
Various subfields of AI research are centered around particular goals and the use of particular tools. The traditional goals of AI research include learning, reasoning, knowledge representation, planning, natural language processing, perception, and support for robotics. To reach these goals, AI researchers have adapted and integrated a wide range of techniques, including search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, operations research, and economics. AI also draws upon psychology, linguistics, philosophy, neuroscience, and other fields. Some companies, such as OpenAI, Google DeepMind and Meta, aim to create artificial general intelligence (AGI)—AI that can complete virtually any cognitive task at least as well as a human.
Artificial intelligence was founded as an academic discipline in 1956, and the field went through multiple cycles of optimism throughout its history, followed by periods of disappointment and loss of funding, known as AI winters. Funding and interest vastly increased after 2012 when graphics processing units started being used to accelerate neural networks and deep learning outperformed previous AI techniques. This growth accelerated further after 2017 with the transformer architecture. In the 2020s, an ongoing period of rapid progress in advanced generative AI became known as the AI boom. Generative AI's ability to create and modify content has led to several unintended consequences and harms, which has raised ethical concerns about AI's long-term effects and potential existential risks, prompting discussions about regulatory policies to ensure the safety and benefits of the technology.
AI
IN SPACE - 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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