There were plenty of creative tech innovations this year. Technology is evolving at an unprecedented pace in our world. It's hard not to be wowed by the incredible innovations that human creativity and ingenuity have produced this past year. From conversational AI to robots, from flying sports cars to electric flying craft, we have seen some of the most remarkable breakthroughs in history. As 2023 comes to a close, let's review some of the most fascinating and influential technology that made this year unforgettable.

One of the challenges in text generation is to control text generation as intended by the user. Previous studies proposed specifying the keywords that should be included in the generated text. However, this approach is insufficient to generate text that reflect the user's intent. For example, placing an important keyword at the beginning of the text would help attract the reader's attention; however, existing methods do not enable such flexible control. In this paper, we tackle a novel task of controlling not only keywords but also the position of each keyword in the text generation. To this end, we propose a task-independent method that uses special tokens to control the relative position of keywords. Experimental results on summarization and story generation tasks show that the proposed method can control keywords and their positions. The experimental results also demonstrate that controlling the keyword positions can generate summary texts that are closer to the user's intent than baseline.

Emergency personnel respond to various situations ranging from fire, medical, hazardous materials, industrial accidents, to natural disasters. Situations such as natural disasters or terrorist acts require a multifaceted response of firefighters, paramedics, hazmat teams, and other agencies. Engineering AI systems that aid emergency personnel proves to be a difficult system engineering problem. Mission-critical "edge AI" situations require low-latency, reliable analytics. To further add complexity, a high degree of model accuracy is required when lives are at stake, creating a need for the deployment of highly accurate, however computationally intensive models to resource-constrained devices. To address all these issues, we propose an agent-based architecture for deployment of AI agents via 5G service-based architecture.

The market for AI (artificial intelligence) technologies is going to expand tremendously in the next decade. Grand View Research says the global AI market will reach $733.7 billion by 2027, growing at a CAGR (compound annual growth rate) of 42.2%. One of the many sectors that will increasingly look to leverage AI technologies between now and 2027 (and beyond) is first response. In fact, in some cases, the first-response industry is already engaged in piloting AI technologies for use on the front lines. What AI-related innovations are to come, and how will they make first responders' jobs easier?

Valley Insights is the result of the partnership between Valley Irrigation and Prospera, which was announced earlier this year. According to Valley Irrigation, the Valley Insights limited release "has demonstrated successful results this growing season, turning data into useful, actionable information for growers in Washington and Nebraska. The service has exceeded expectations by already reaching its targeted goal of one million acres by 2020." We are gaining traction with the initial launch of Valley Insights. The partnership between Valley and Prospera has exceeded expectations by already reaching its targeted goal of one million acres by 2020.

As astronauts move deeper into space they must also become more autonomous from mission control on Earth. As a result, astronauts must take on additional responsibilities for jobs typically performed by flight controllers today, and crew workload and training requirements are expected to increase. Robotic automation has potential to reduce crew workload and training needs. Additionally robots with some level of autonomy can reduce human risk by per-forming hazardous tasks that crew would otherwise have to perform. We are working with NASA to investigate new concepts of operation for astronauts interacting with autonomous robots in space, including remote supervision of a planetary robot by an astronaut orbiting the planet and remote understanding of robotic activities without eyes-on monitoring. We also are developing techniques for computing and analyzing agent performance for the roles and responsibilities needed for these ConOps, and have developed software to compute these performance measures for humans and robots in-line during mission operations. We describe results of using this software to monitor rover performance during multiple NASA robotic field tests and analog mission simulations.