The Allen Institute For Artificial Intelligence

RESEARCH INFRASTRUCTURE: NSF MID-SCALE RI-2: OPEN MULTIMODAL AI INFRASTRUCTURE TO ACCELERATE SCIENCE -LANGUAGE MODELS WITH BILLIONS OF POSSIBLE ADJUSTMENTS AND TRAINED ON TRILLIONS OF WORDS ARE NOW POWERING THE FASTEST-GROWING COMPUTING APPLICATIONS IN HISTORY. LARGE LANGUAGE MODELS (LLM) ARE BUILT USING MASSIVE AMOUNTS OF TEXT, USUALLY OBTAINED BY PULLING DATA FROM MULTIPLE SOURCES ON THE INTERNET. RECENT ADVANCES ENABLE THESE MODELS TO PROCESS OTHER KINDS OF DATA, INCLUDING IMAGES, GRAPHS AND TABLES. MODELS WITH THESE ABILITIES ARE KNOWN AS MULTIMODAL LLMS. THE BEST-PERFORMING LLMS CURRENTLY DEPLOYED ARE PROPRIETARY, SO THEIR PARAMETERS, TRAINING DATA, CODE AND DOCUMENTATION ARE NOT OPENLY AVAILABLE. THUS, MOST ARTIFICIAL INTELLIGENCE (AI) SCIENTISTS CANNOT STUDY, EXPERIMENT DIRECTLY WITH, OR IMPROVE THESE STATE-OF-THE-ART MODELS. THIS PROJECT ? OPEN, MULTIMODAL ARTIFICIAL INTELLIGENCE (OMAI) - WILL PROVIDE INFRASTRUCTURE IN THE FORM OF A SUITE OF POWERFUL, WELL-DOCUMENTED, UP-TO-DATE, OPEN MODELS, AND OPEN-SOURCE INTERFACES DESIGNED FOR SCIENTIFIC WORK. SCIENTISTS WILL BE ABLE TO ACCESS THE MODELS, USE DISCIPLINE-SPECIFIC DATA AND OPTIMIZE THE MODELS. THE PROJECT EMPOWERS RESEARCHERS, PROVIDES DOCUMENTATION TO ACCELERATE RESEARCH AND EDUCATION, AND HAS AN ACTIVE PROGRAM IN EARLY-CAREER TRAINING TO ADVANCE US ECONOMIC AND SCIENTIFIC COMPETITIVENESS. IN ADDITION, OPPORTUNITIES PROVIDED THROUGH PARTNERSHIPS WITH A RANGE OF INSTITUTIONS AND PROGRAMS WILL ENHANCE TRAINING. THE LONG-TERM PLAN IS TO MAKE THE INFRASTRUCTURE AVAILABLE AS A LOW- OR ZERO-COST SERVICE TO THE RESEARCH COMMUNITY IN A MANNER LIKE OPEN-SOURCE CODE REPOSITORIES AND SCIENCE-FOCUSED DIGITAL LIBRARIES, TO MAXIMIZE USAGE. THE OMAI RESEARCH INFRASTRUCTURE CONSISTS OF A SERIES OF OPEN, MULTIMODAL LANGUAGE MODELS KEPT UP TO DATE WITH RECENT SCIENTIFIC PUBLICATIONS AND OPEN-SOURCE APPLICATION PROGRAMMING INTERFACES THAT ENABLE SCIENTISTS TO USE, EXPAND, AND MODIFY THOSE MODELS. IT ADDRESSES PRIORITIES SET FORTH IN THE WHITE HOUSE AI ACTION PLAN (HTTPS://WWW.WHITEHOUSE.GOV/WP-CONTENT/UPLOADS/2025/07/AMERICAS-AI-ACTION-PLAN.PDF) TO ACCELERATE AI-ENABLED SCIENCE AND ENSURE THE UNITED STATES IS PRODUCING THE LEADING OPEN MODELS. THE INFRASTRUCTURE AIMS TO ACCELERATE SCIENTIFIC DISCOVERY ACROSS DISCIPLINES RANGING FROM MATERIALS TO PROTEIN FUNCTION PREDICTION AND WEATHER MODELS. IT WILL ALSO ENABLE NEW UNDERSTANDING AND IMPROVEMENT OF FUTURE LLMS WHILE CONTRIBUTING TO THE DEVELOPMENT OF A WELL-TRAINED WORKFORCE CAPABLE OF BUILDING, CUSTOMIZING, AND MAINTAINING SUCH MODELS. IN ALLOWING RESEARCHERS TO FINE TUNE THE MODELS, RESEARCHERS CAN OPTIMIZE PERFORMANCE AND UNDERSTAND DESIGN DECISIONS THAT INFLUENCE TRAINING SPEED AND STABILITY, WHICH CAN IMPACT THE SHORT-TERM AND LONG-TERM ECONOMIC COSTS OF LLM DEVELOPMENT. THE PROJECT EMPHASIZES REPRODUCIBILITY, TRANSPARENCY, OPEN DATA, OPEN AND EVOLVING EVALUATIONS, MULTIMODALITY, AND SCIENTIFIC USE-CASES. IT WILL ENABLE A BROAD POPULATION OF SCIENTIST-USERS ACROSS ALL DISCIPLINES TO USE AND ADAPT ARTIFICIAL INTELLIGENCE MODELS TO THEIR OWN NEEDS AND LAYS THE FOUNDATION FOR FUTURE RESEARCH IN AI FOR SCIENCE. BY SUPPORTING WORK IN THESE NOVEL, CRITICAL RESEARCH AREAS, OMAI CAN ULTIMATELY BENEFIT BOTH SCIENCE AND THE PUBLIC. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE PLANNED FOR THIS AWARD.

CCRI: RESEARCH INFRASTRUCTURE: NEW: SEMANTIC SCHOLAR OPEN DATA PLATFORM: ENABLING RESEARCH INTO SCIENTIFIC SEARCH AND DISCOVERY -THE EXPONENTIAL GROWTH OF SCIENTIFIC PUBLICATION MAKES IT DIFFICULT FOR SCIENTISTS TO TRACK DEVELOPMENTS IN THEIR FIELD AND MAKE CONNECTIONS BETWEEN DIFFERENT ADVANCES. IN RESPONSE, ARTIFICIAL-INTELLIGENCE RESEARCHERS HAVE STARTED TO DEVELOP TECHNIQUES THAT ALLOW COMPUTERS TO ?READ? SCIENTIFIC PAPERS AND AUTOMATICALLY CLASSIFY TOPICS, EXTRACT KEY RESULTS, SUMMARIZE CONTRIBUTIONS, IDENTIFY CONNECTIONS, AND SELECT A PERSONALIZED SET OF PAPERS THAT MAY BE OF SPECIAL INTEREST TO EACH SCIENTIST. THE ENDURING VISION IS TO BUILD AI SYSTEMS THAT CAN PROCESS AN IMMENSE CORPUS OF SCHOLARLY DOCUMENTS AND AUGMENT THE CAPABILITIES OF HUMAN SCIENTISTS ? ACCELERATING SCIENTIFIC DISCOVERY AND HELPING HUMANITY QUICKLY CONFRONT DISASTERS SUCH AS THE COVID-19 PANDEMIC. THE PROPOSED SEMANTIC SCHOLAR OPEN DATA PLATFORM BUILDS INFRASTRUCTURE TO SUPPORT THIS RESEARCH BY FIRST GATHERING A COMPREHENSIVE SET OF PAPERS AND ARRANGING FOR EFFICIENT INDEXING. THE SYSTEM PROCESSES PDF-FORMATTED PAPERS TO EXTRACT INFORMATION AND USE ADVANCED ANALYTIC PROCESSING APPROACHES TO PROVIDE RESEARCHERS ACCESS TO RESULTS. THE INFRASTRUCTURE WILL DRAMATICALLY LOWER THE BARRIER TO ENTRY FOR NEWCOMERS TO THE FIELD OF SCHOLARLY DOCUMENT PROCESSING, IMPROVE REPRODUCIBILITY OF EXPERIMENTS, AND ACCELERATE INNOVATION IN THE IMPORTANT AREA OF AI-AUGMENTED SCIENTIFIC DISCOVERY THE INFRASTRUCTURE PROPOSED IS UNIQUE, BECAUSE ALTERNATIVE SOURCES OF ACADEMIC PAPERS ARE EITHER CLOSED, INCOMPLETE, HAVE LIMITED PROGRAMMATIC ACCESS, OR HAVE BEEN RETIRED. THE PROPOSED SEMANTIC SCHOLAR OPEN DATA PLATFORM HAS THREE PARTS: 1) A COMPREHENSIVE SET OF ONLINE SERVICES ENABLING RESEARCHERS TO PROGRAMMATICALLY SEARCH, FILTER, EXTRACT, SUMMARIZE, AND ANALYZE A LARGE AND CONTINUALLY-UPDATED CORPUS OF DOCUMENTS; 2) A NEW MECHANISM THAT ENABLES RESEARCHERS TO CURATE THEIR OWN DOMAIN-SPECIFIC TEXT CORPORA, AS THE TEAM PREVIOUSLY CREATED THE CORD-19 DATASET FOR CORONAVIRUS RESEARCH; 3) OPEN SOURCE SOFTWARE, INCLUDING PRETRAINED LANGUAGE MODELS AND USER INTERFACE TEMPLATES TO SERVE AS RESEARCH BUILDING BLOCKS. TOGETHER THE INFRASTRUCTURE WILL DRAMATICALLY LOWER THE BARRIER TO ENTRY FOR NEWCOMERS TO THE FIELD OF SCHOLARLY DOCUMENT PROCESSING, IMPROVE REPRODUCIBILITY OF EXPERIMENTS, AND ACCELERATE INNOVATION IN THE IMPORTANT AREA OF AI-AUGMENTED SCIENTIFIC DISCOVERY. FORTUNATELY, THE RECENT INCREASE IN RESEARCH IN SCHOLARLY DOCUMENT PROCESSING (E.G., THE RAPID UPTAKE OF OUR CORD-19 DATASET) SHOWS THAT THE COMPUTER AND INFORMATION SCIENCE COMMUNITY HAS THE INTEREST AND CAPABILITY TO DEVELOP NEW TECHNOLOGIES THAT ACCELERATE SCIENCE AND HELP MEET GLOBAL SOCIETAL CHALLENGES, SUCH AS PANDEMICS AND CLIMATE CHANGE. THE RESULTING ADVANCES IN AI-AUGMENTED SCIENTIFIC DISCOVERY WILL BENEFIT ALL AREAS OF SCIENCE, SPURRING MEDICAL ADVANCES, CREATING NEW JOBS, AND IMPROVING ACCESS FOR BLIND RESEARCHERS. WE WILL IMPROVE GLOBAL INFRASTRUCTURE BY PROVIDING OPEN SERVICES, DATA SETS, CODE, AND ASSOCIATED EDUCATIONAL MATERIALS. THE TEAM WILL ALSO ENGAGE WITH UNDERREPRESENTED STEM STUDENTS AND THROUGH K-12 OUTREACH. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.

TRAVEL: NSF STUDENT GRANT FOR 2025 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) -THIS AWARD PROVIDES TRAVEL SUPPORT FOR STUDENTS ENROLLED AT U.S. INSTITUTIONS TO PARTICIPATE IN THE DOCTORAL CONSORTIUM AT THE 2025 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), TO BE HELD IN HONOLULU, HAWAII. NOW IN ITS 20TH YEAR, ICCV IS A PREMIER INTERNATIONAL CONFERENCE THAT CONVENES LEADING RESEARCHERS AND STUDENTS WORKING ON COMPUTER VISION, A FOUNDATIONAL AREA OF ARTIFICIAL INTELLIGENCE (AI) WITH BROAD APPLICATIONS IN FIELDS SUCH AS HEALTHCARE, SECURITY, ROBOTICS, AND AUTONOMOUS SYSTEMS. THE DOCTORAL CONSORTIUM HELPS CULTIVATE FUTURE LEADERS IN AI AND COMPUTER VISION BY PROVIDING EARLY-CAREER RESEARCHERS WITH OPPORTUNITIES TO ENGAGE IN TECHNICAL DISCOURSE, REFINE THEIR RESEARCH DIRECTIONS, AND BUILD PROFESSIONAL NETWORKS. BY ENABLING APPROXIMATELY 20 PH.D. STUDENTS FROM A DIVERSE RANGE OF ACADEMIC INSTITUTIONS TO ATTEND THE CONSORTIUM, THE AWARD PROMOTES ACCESS TO MENTORSHIP, CAREER DEVELOPMENT, AND SCHOLARLY EXCHANGE. IN DOING SO, THIS AWARD DIRECTLY SUPPORTS THE PROGRESS OF SCIENCE AND THE DEVELOPMENT OF THE U.S. SCIENTIFIC WORKFORCE. THE AWARD PROVIDES TRAVEL SUPPORT FOR 20 STUDENTS FROM US INSTITUTIONS TO PARTICIPATE IN A STRUCTURED PROGRAM HELD IN CONJUNCTION WITH ICCV 2025. THE DOCTORAL CONSORTIUM INCLUDES POSTER SESSIONS, MENTORSHIP SESSIONS WITH SENIOR RESEARCHERS, AND FOCUSED DISCUSSIONS ON CAREER PATHWAYS IN ACADEMIA AND INDUSTRY. STUDENT APPLICANTS WILL BE EVALUATED BY THE CONSORTIUM CHAIRS BASED ON THE QUALITY AND RELEVANCE OF THEIR RESEARCH, THEIR POTENTIAL FOR LEADERSHIP IN THE FIELD, AND THE EXPECTED IMPACT OF THEIR PARTICIPATION. THE TRAVEL AWARDS WILL HELP STUDENTS COVER KEY EXPENSES SUCH AS AIRFARE, LODGING, AND LOCAL TRANSPORTATION. BY PROVIDING THIS SUPPORT, THE AWARD ENSURES THAT PROMISING YOUNG RESEARCHERS CAN CONTRIBUTE TO AND BENEFIT FROM ONE OF THE MOST INFLUENTIAL VENUES IN COMPUTER VISION AND ARTIFICIAL INTELLIGENCE RESEARCH. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

GOVERNING COOPERATIVE AGREEMENT: NSF MID-SCALE RI-2: OPEN MULTIMODAL AI INFRASTRUCTURE TO ACCELERATE SCIENCE -- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.