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Infectious diseases are frequent and could endanger public health, hence, it is essential to decrease their occurrence through effective preventive measures such as vaccination. However, the limited vaccine supply makes coping with novel infectious disease outbreaks at the initial stages difficult. The heterogeneous human activities that cause uncertainty about the spread of epidemics create a global imbalance between the demand for and supply of vaccines. Therefore, how to design an equitable and efficient vaccine prioritization and allocation plan to adapt to the spatio-temporal distribution of outbreaks has become a means for controlling the spread of infectious diseases. Considering the temporal heterogeneity of epidemic spreading across regions, this proposal aims to optimize vaccine distribution strategies for multiple regions based on AI techniques.
High Performance Computing vs Quantum Computing for Neural Networks supporting Artificial Intelligence
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.