From Compute to Competitiveness (Paperback)
Idioma: inglés
Editorial: Warrington Press, 2026
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- Nuevo
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Vendedor de IberLibro desde 22 de junio de 2007
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Paperback. At the University of Florida, advances across medicine, education, engineering, and national security increasingly depended on a shared institutional capability: compute. From Compute to Competitiveness examines how UFs investment in HiPerGator AI led Vice President for Research David Norton to view competitiveness not simply in terms of research funding, but as the institutional capacity to support and win AI-enabled research. Real gains depended on seed funding, technical talent, faculty readiness, and organizational support.As UFs AI research portfolio expanded across colleges, centers, and sponsor ecosystems, the university gained evidence that its growth was outpacing several national and institutional benchmarks. The case follows UFs effort to measure its own transformation through IntelliGator, an LLM-based classifier developed by the Artificial Intelligence and Informatics Research Institute (AIIRI) to provide a more systematic view of the research activity tied to UFs AI capabilities. Ultimately, the case asks a question every research leader faces after a major technology investment: what can you confidently prove, what can you reasonably argue, and what should you leave unclaimed? Its deeper lesson is that equally important to what AI infrastructure enables is how rigorously leaders can measure and defend the claims they make about it. Learning Objectives Evaluate how a major technology investment can strengthen research competitiveness only when paired with complementary capabilities such as seed funding, technical staffing, faculty support, and organizational coordination. Distinguish among different types of return-on-investment claimscapability creation, measurable portfolio growth, and causal attributionand assess the evidence required for each. Analyze how measurement systems, including AI-enabled classification tools, can help complex organizations assess strategic outcomes under conditions of incomplete information. Assess the limits of attribution when institutional performance improves alongside broader shifts in funding, policy, and technological adoption. Appropriate Courses Digital transformation strategy, technology and information management, organizational change and leadership, higher education strategy and governance, strategic partnerships and alliance management, and public sector innovation. This case follows the University of Florida's effort to measure its own transformation as a result of its investment in HiPerGator AI using IntelliGator, an LLM-based classifier developed by the Artificial Intelligence and Informatics Research Institute to provide a more systematic view of the research activity tied to UF's AI capabilities. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…
N° de ref. del artículo 9798950151927
- Título
- From Compute to Competitiveness (Paperback)
- Autor
- Michael Carrillo
- Editorial
- Warrington Press
- Año de publicación
- 2026
- Estado
- new
- Encuadernación
- Paperback
- Idioma
- inglés
- ISBN 13
- 9798950151927
Abstract
At the University of Florida, advances across medicine, education, engineering, and national security increasingly depended on a shared institutional capability: compute. From Compute to Competitiveness examines how UF's investment in HiPerGator AI led Vice President for Research David Norton to view competitiveness not simply in terms of research funding, but as the institutional capacity to support and win AI-enabled research. Real gains depended on seed funding, technical talent, faculty readiness, and organizational support.
As UF's AI research portfolio expanded across colleges, centers, and sponsor ecosystems, the university gained evidence that its growth was outpacing several national and institutional benchmarks. The case follows UF's effort to measure its own transformation through IntelliGator, an LLM-based classifier developed by the Artificial Intelligence and Informatics Research Institute (AIIRI) to provide a more systematic view of the research activity tied to UF's AI capabilities.
Ultimately, the case asks a question every research leader faces after a major technology investment: what can you confidently prove, what can you reasonably argue, and what should you leave unclaimed? Its deeper lesson is that equally important to what AI infrastructure enables is how rigorously leaders can measure and defend the claims they make about it.
Learning Objectives
Evaluate how a major technology investment can strengthen research competitiveness only when paired with complementary capabilities such as seed funding, technical staffing, faculty support, and organizational coordination.
Distinguish among different types of return-on-investment claims--capability creation, measurable portfolio growth, and causal attribution--and assess the evidence required for each.
Analyze how measurement systems, including AI-enabled classification tools, can help complex organizations assess strategic outcomes under conditions of incomplete information.
Assess the limits of attribution when institutional performance improves alongside broader shifts in funding, policy, and technological adoption.
Appropriate Courses
Digital transformation strategy, technology and information management, organizational change and leadership, higher education strategy and governance, strategic partnerships and alliance management, and public sector innovation
This case was developed with the support of the UF AI initiative, made possible by a transformational gift from Chris Malachowsky.
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AussieBookSeller
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