Aiming for the deployment and expansion of AI, including generative and agentic AI, we sought insights from leading figures in government, academia, and industry to map out a road to achievement
**NASA Goddard Space Flight Center Embraces Generative AI for Operational Efficiency and Innovation**
NASA Goddard Space Flight Center (GSFC) is expanding its use of artificial intelligence (AI) beyond science and technology, with a focus on improving operational efficiency, training, communication, and collaboration.
One innovative application of AI at GSFC is the use of generative models to optimize operational workflows, predict maintenance needs, and streamline project management processes. This can help reduce downtime and improve resource allocation across various facilities and projects.
AI-driven chatbots and virtual assistants are also being used to provide personalized learning experiences for employees. These chatbots create customized training modules, offer real-time feedback, and enhance knowledge retention in complex fields like space exploration and AI itself.
An internal chatbot is facilitating better communication among teams by providing quick access to information, automating routine inquiries, and helping in organizing meetings and schedules. This improves collaboration and reduces the time spent on administrative tasks.
The internal chatbot at NASA Goddard is designed to assist in disseminating information across departments, fostering a sense of engagement among employees, and helping analyze the ROI of various AI initiatives. However, specific details about the chatbot's features or contributions are not yet fully disclosed.
In the science and technology areas, NASA has already been using AI extensively. AI is used for data analysis, autonomous systems, and environmental studies. AI helps analyse vast amounts of data from satellites and deep space missions, identify patterns and trends, and make autonomous decisions for spacecraft.
NASA Goddard is also developing a product called "text to structures," which is not specified further in the available information. The agency is focusing on creating "thinking models," maintaining a "living AI strategy," and doing extensive outreach.
Ryan Simpson, from NVIDIA, emphasizes the importance of getting employees to use and evaluate AI tools to measure return on investment (ROI) and job satisfaction. He suggests that organizations should quantify their investment in AI to determine the best use cases and measure the impact of AI on productivity, quality of work life, and long-term retention rates.
AI is expected to create documents and reduce duplicative efforts in creating documents and testing reports. The next evolution of the chatbot will be connected to big datasets and databases, leading to an entire system of AI-connected tools called "text to spaceship."
examples like the Department of Veterans Affairs (VA) have reported that 80% of users feel more productive after using generative AI. The AI Policy Lab at Georgetown University's McCourt School of Public Policy serves as a platform for public and private sector experts, academia, and others to collaborate on AI challenges and propose tangible solutions.
The AI Policy Lab approaches its problem sets as public service projects, considering governance, trust, and transparency requirements. One of the first issues the AI Policy Lab tackled was election security, resulting in the creation of a public service announcement (PSA) addressing deep fake audio.
As NASA continues to explore AI's potential, integrating generative AI into operational areas could lead to significant improvements in efficiency and innovation across the agency. NASA Goddard's development of an internal chatbot for its workforce is a step towards this goal.
At NASA Goddard Space Flight Center, the internal chatbot is being used to optimize operational workflows, employing generative AI models to streamline project management processes and predict maintenance needs. This AI-driven chatbot is also designed to provide personalized training experiences, create customized modules, and enhance knowledge retention in complex fields.
