Conférence
Notice
Langue :
Anglais
Crédits
Allen Malony (Intervention)
Conditions d'utilisation
Droit commun de la propriété intellectuelle
DOI : 10.60527/ef3q-m539
Citer cette ressource :
Allen Malony. UVSQ. (2017, 22 février). From Computable Numbers to Curing Cancer : Supercomputing and the Frontiers of Human Discovery , in Leçon inaugurale de la Chaire Tocqueville-Fulbright. [Vidéo]. Canal-U. https://doi.org/10.60527/ef3q-m539. (Consultée le 20 septembre 2024)

From Computable Numbers to Curing Cancer : Supercomputing and the Frontiers of Human Discovery

Réalisation : 22 février 2017 - Mise en ligne : 15 mars 2017
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Descriptif

On the 80th anniversary of the most fundamental technological advancement of humankind, computers are omnipresent in our daily reality. To themajority of people, it might be said that what computers "are" is "indistinguishable from magic" since they do not really know "how" computers work. Infact, Turing showed us that "how" they work is quite simple. What they "do" is indeed nothing short of giving humankind themost powerful "tool" ever for amplifying our (individual and collective) intelligence, creativity, and knowledge. How do we understand and quantify theamazing potential ("power") that computers bring to human discovery ?

Interestingly, both the computational complexity of a problem and the performance of the computer are important in answering the question.High-performance computers (a.k.a. "supercomputers") are the present embodiment of this potential, combining state-of-the-art (parallel) computingtechnology, with the latest approaches to computation-driven and data-driven science and humanities. The Fulbright Distinguished Chair talk willexplore the nature of supercomputing from its fundamental concepts, to the advances it is realizing today, to the opportunities for improving our lives inthe future. The talk will highlight the progress in science and engineering made possible by high-performance computational modeling andsimulation, as well as new opportunities opening up in data science through machine learning and big data. Examples from human brain research andthe ambitious "cancer moonshot" challenge will be highlighted.

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