Skip to main content

research-grants

Affinity Groups

There are no Affinity Groups associated with this topic. View All Affinity Groups.

Announcements

There are no announcements with this tag. View All Announcements.

Upcoming Events & Trainings

No events or trainings are currently scheduled.

Topics from Ask.CI

Loading topics from Ask.CI ...

CI Links

There are no CI Links associated with this topic. View All CI Links.

Engagements

High Performance Computing vs Quantum Computing for Neural Networks supporting Artificial Intelligence
Pace University

A personalized learning system that adapts to learners' interests, needs, prior knowledge, and available resources is possible with artificial intelligence (AI) that utilizes natural language processing in neural networks. These deep learning neural networks can run on high performance computers (HPC) or on quantum computers (QC). Both HPC and QC are emergent technologies. Understanding both systems well enough to select which is more effective for a deep learning AI program, and show that understanding through example, is the ultimate goal of this project. The entry to learning technologies such as HPC and QC is narrow at present because it relies on classical education methods and mentoring. The gap between the knowledge workers needed, which is in high demand, and those with the expertise to teach, which is being achieved at a much slower rate, is widening. Here, an AI cognitive agent, trained via deep learning neural networks, can help in emergent technology subjects by assisting the instructor-learner pair with adaptive wisdom. We are building the foundations for this AI cognitive agent in this project.

The role of the student facilitator will involve optimizing a deep learning neural network, comparing and contrasting with the newest technologies, such as a quantum computer (and/or a quantum computer simulator) and a high performance computer and showing the efficiency of the different computing approaches. The student facilitator will perform these tasks at the rate described in the proposal. Milestone work will be displayed and shared publicly via posting to the Jupyter Notebooks on Google Colab and linked to regular Github uploads.

Status: Complete

People with Expertise

Adam Carlson

Wake Forest University

Programs

Campus Champions

Roles

research computing facilitator

Headshot

Expertise

Xiaoqin Huang

Rice University

Programs

ACCESS CSSN

Roles

mentor, research computing facilitator, research software engineer, cssn

xqhuang at Rice

Expertise

Ami Gaspar

University of Maine System

Programs

Campus Champions, Northeast

Roles

research computing facilitator

Placeholder headshot

Expertise

People with Interest

Henry Neeman

University of Oklahoma

Programs

Campus Champions

Roles

research computing facilitator

Placeholder headshot

Interests

c
+5 more tags

Justin Oelgoetz

Austin Peay State University

Programs

Campus Champions

Roles

mentor, researcher/educator, research computing facilitator

Placeholder headshot

Interests

Timothy Meeker

Programs

ACCESS CSSN

Roles

cssn

Headshot of T.J. Meeker

Interests