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PFI-TT: Prototyping a quantum-powered AI building platform

Project: Research

Abstract & Details

Description

Award ID: 2141058

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is in significant improvement of artificial intelligence (AI) systems by acceleration of the model creation, training, and operation using modern quantum computers. The project's outcomes can stimulate advances in chemistry, create new materials and new drugs, improve manufacturing and retail, reduce risks in high-tech, exploration and mission planning, and improve decision-making in arenas such as the public sector, banking, and healthcare. The project will nurture a new generation of entrepreneurs and scientists who can move easily between disciplines as varied as engineering, physics, computer science, and high-performance simulations. The proposed project will develop an AI-building software platform that enables training the models on the fly on fast-evolving and fast-growing datasets. This will significantly improve their prediction and classification functions, reducing training time on large datasets by ten-fold. With the quantum-accelerated AI, a significant part of decision-making tasks can be automated to reduce human errors, thereby reducing mission failure risks. 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.

NSF Program Director: Samir Iqbal
StatusClosed
Effective start/end date02/15/2201/31/25

Funding

  • Other Programs (Technology): $250,000.00

Active Fiscal Year

  • FY2024
  • FY2023
  • FY2022
  • FY2025

Start Fiscal Year

  • FY2022

TIP Programs

  • Other Programs (Technology)

Key Technology Areas

  • Artificial Intelligence
  • (confidence score: 100%)
  • Quantum Information Science and Technology
  • (confidence score: 97%)

Technology Foci

  • Machine Learning Training Data
  • (confidence score: 100%)
  • Machine Learning (ML)
  • (confidence score: 100%)
  • Quantum Computing Hardware
  • (confidence score: 86%)

Congressional District at Award

  • District n. 07 of New York

Current Congressional District

  • District n. 07 of New York

United States

  • New York

Core Based Statistical Area (CBSA)

  • New York-Newark-Jersey City, NY-NJ

County

  • County: Kings, NY

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