Baskar Ganapathysubramanian, Jessica M. P. Bell, George Kantor, Nirav Merchant, Soumik Sarkar, Patrick S. Schnable, Michelle Segovia, Arti Singh, Asheesh K. Singh
{"title":"AIIRA:人工智能抗灾农业研究所","authors":"Baskar Ganapathysubramanian, Jessica M. P. Bell, George Kantor, Nirav Merchant, Soumik Sarkar, Patrick S. Schnable, Michelle Segovia, Arti Singh, Asheesh K. Singh","doi":"10.1002/aaai.12151","DOIUrl":null,"url":null,"abstract":"<p><span>AIIRA</span> seeks to transform agriculture by creating a new AI-driven framework for modeling plants at various agronomically relevant scales. We accomplish this by designing and deploying AI-driven predictive models that fuse diverse data with siloed domain knowledge. <span>AIIRA</span>'s vision, illustrated in Figure 1, consists of four technical thrusts with cross-cutting education, training, and outreach activities. Our activities are focused on theory, algorithms, and tools for the principled creation of goal-oriented AI tools deployed at plant and field scales. Our use-inspired AI developments are tightly integrated with USDA-relevant challenges in crop improvement and sustainable crop production. Our strong social science focus ensures sustained AI adoption across the ag value chain. Our cyberinfrastructure (CI) efforts ensure cohesive, sustainable, and extensible CI to reproducibly share and manage data assets and analysis workflows to a diverse spectrum of the Ag community. Taken together, this will ensure long-term payoffs in AI and agriculture. <span>AIIRA</span> has established a new field of <i>Cyber Agricultural Systems</i> at the intersection of plant science, agronomics, and AI. Our signature activities build the workforce for this new field through formal and informal educational activities. Through these activities, <span>AIIRA</span> creates accessible pathways for underrepresented groups, especially Native Americans and women.</p>","PeriodicalId":7854,"journal":{"name":"Ai Magazine","volume":"45 1","pages":"94-98"},"PeriodicalIF":2.5000,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aaai.12151","citationCount":"0","resultStr":"{\"title\":\"AIIRA: AI Institute for Resilient Agriculture\",\"authors\":\"Baskar Ganapathysubramanian, Jessica M. P. Bell, George Kantor, Nirav Merchant, Soumik Sarkar, Patrick S. Schnable, Michelle Segovia, Arti Singh, Asheesh K. Singh\",\"doi\":\"10.1002/aaai.12151\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><span>AIIRA</span> seeks to transform agriculture by creating a new AI-driven framework for modeling plants at various agronomically relevant scales. We accomplish this by designing and deploying AI-driven predictive models that fuse diverse data with siloed domain knowledge. <span>AIIRA</span>'s vision, illustrated in Figure 1, consists of four technical thrusts with cross-cutting education, training, and outreach activities. Our activities are focused on theory, algorithms, and tools for the principled creation of goal-oriented AI tools deployed at plant and field scales. Our use-inspired AI developments are tightly integrated with USDA-relevant challenges in crop improvement and sustainable crop production. Our strong social science focus ensures sustained AI adoption across the ag value chain. Our cyberinfrastructure (CI) efforts ensure cohesive, sustainable, and extensible CI to reproducibly share and manage data assets and analysis workflows to a diverse spectrum of the Ag community. Taken together, this will ensure long-term payoffs in AI and agriculture. <span>AIIRA</span> has established a new field of <i>Cyber Agricultural Systems</i> at the intersection of plant science, agronomics, and AI. Our signature activities build the workforce for this new field through formal and informal educational activities. Through these activities, <span>AIIRA</span> creates accessible pathways for underrepresented groups, especially Native Americans and women.</p>\",\"PeriodicalId\":7854,\"journal\":{\"name\":\"Ai Magazine\",\"volume\":\"45 1\",\"pages\":\"94-98\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-02-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aaai.12151\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ai Magazine\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/aaai.12151\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ai Magazine","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/aaai.12151","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
AIIRA seeks to transform agriculture by creating a new AI-driven framework for modeling plants at various agronomically relevant scales. We accomplish this by designing and deploying AI-driven predictive models that fuse diverse data with siloed domain knowledge. AIIRA's vision, illustrated in Figure 1, consists of four technical thrusts with cross-cutting education, training, and outreach activities. Our activities are focused on theory, algorithms, and tools for the principled creation of goal-oriented AI tools deployed at plant and field scales. Our use-inspired AI developments are tightly integrated with USDA-relevant challenges in crop improvement and sustainable crop production. Our strong social science focus ensures sustained AI adoption across the ag value chain. Our cyberinfrastructure (CI) efforts ensure cohesive, sustainable, and extensible CI to reproducibly share and manage data assets and analysis workflows to a diverse spectrum of the Ag community. Taken together, this will ensure long-term payoffs in AI and agriculture. AIIRA has established a new field of Cyber Agricultural Systems at the intersection of plant science, agronomics, and AI. Our signature activities build the workforce for this new field through formal and informal educational activities. Through these activities, AIIRA creates accessible pathways for underrepresented groups, especially Native Americans and women.
期刊介绍:
AI Magazine publishes original articles that are reasonably self-contained and aimed at a broad spectrum of the AI community. Technical content should be kept to a minimum. In general, the magazine does not publish articles that have been published elsewhere in whole or in part. The magazine welcomes the contribution of articles on the theory and practice of AI as well as general survey articles, tutorial articles on timely topics, conference or symposia or workshop reports, and timely columns on topics of interest to AI scientists.