2537075

CATEGORY II: SAGEBRUSH - AN AI INFERENCE RESOURCE FOR ACCESS, NAIRR, AND THE NATION -SAGEBRUSH IS A TRANSFORMATIVE GENERATIVE ARTIFICIAL INTELLIGENCE (AI) INFERENCE PLATFORM, DESIGNED TO ACCELERATE SCIENTIFIC DISCOVERY BY PROVIDING RESEARCHERS WITH A POWERFUL TOOL FOR AI-DRIVEN DISCOVERY. AS FIELDS SUCH AS GENOMICS, HEALTH CARE, AND CIVIL ENGINEERING REQUIRE THE MOST ADVANCED REAL-TIME ANALYSIS, TRADITIONAL GPU-BASED SYSTEMS STRUGGLE TO MEET THE DEMANDS FOR SPEED, SCALABILITY, AND SUSTAINABILITY. SAGEBRUSH ADDRESSES THESE CHALLENGES BY LEVERAGING CUTTING-EDGE SAMBANOVA AI PROCESSORS, WHICH DELIVER UNMATCHED PERFORMANCE WHILE MINIMIZING ENERGY CONSUMPTION. HOSTED AT THE TEXAS ADVANCED COMPUTING CENTER (TACC) - A LEADER IN HIGH-PERFORMANCE COMPUTING AND HOME TO THE NSF?S LEADERSHIP CLASS COMPUTING FACILITY (LCCF) - SAGEBRUSH INTEGRATES SEAMLESSLY WITH EXISTING NSF RESOURCES TO ENSURE BROAD ACCESS FOR RESEARCHERS ACROSS DISCIPLINES. THE PLATFORM IS OPTIMIZED FOR AI INFERENCE WORKLOADS, ENABLING SCIENTISTS TO INTERACT WITH LARGE-SCALE AI MODELS IN REAL TIME. BY OFFERING USER-FRIENDLY TOOLS LIKE JUPYTER NOTEBOOKS AND WEB-BASED CHATBOT INTERFACES, THE PLATFORM LOWERS TECHNICAL BARRIERS, EMPOWERING RESEARCHERS OF ALL BACKGROUNDS TO HARNESS AI FOR TRANSFORMATIVE DISCOVERIES. 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.

University Of Texas At Austin

THE GOAL OF THIS FUNDING OPPORTUNITY, "ADVANCED COMPUTING SYSTEMS & SERVICES: ADAPTING TO THE RAPID EVOLUTION OF SCIENCE AND ENGINEERING RESEARCH 2.0", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF24583

47.070 - Computer and Information Science and Engineering

NSF Office of Advanced Cyberinfrastructure (OAC) [NSF]

Austin, Texas 78712-1139 United States

Single Zip Code

Advanced Computing Systems & Services: Adapting to the Rapid Evolution of Science and Engineering Research 2.0 (24-583)