DES Pune University Joins Hands with Yotta Data Services for AI-Powered Data Lab

The AI lab will also improve computational efficiency, allowing rapid extraction of critical insights from large data sets valuable for academic and research pursuits.
DES Pune University
DES Pune UniversityAsmita Patil / The Bridge Chronicle
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Pune: Deccan Education Society’s DES Pune University (DES PU) has signed a Memorandum of Understanding (MoU) with Yotta Data Services to launch an Artificial Intelligence (AI) lab that will provide advanced data analysis capabilities for students and faculty.

This collaboration aims to equip the university community with practical knowledge in data science by offering hands-on access to advanced GPU technology in Yotta’s Shakti AI Lab.

As part of the partnership, approximately 1,800 students and faculty members will have access to Yotta’s AI-powered resources, enabling them to analyze extensive datasets quickly.

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The AI lab will also improve computational efficiency, allowing rapid extraction of critical insights from large data sets, which is increasingly valuable for academic and research pursuits.

Dr. Ravindra Acharya, President of DES Pune University, highlighted during a press conference that the collaboration will significantly boost the university’s capabilities in data analytics, offering a competitive edge to students in fields reliant on AI and big data.

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University Vice-Chancellor Dr. Prasad Khandekar, alongside Yotta representatives Sandeep Pathak, Vishal Agarwal, Mangesh Shigwan, and Vishal Patil, discussed how this AI lab will address the technical needs for data aggregation, cloud computing, and server support.

As a key component of the agreement, Yotta will provide DES Pune University with a fully-equipped AI lab, with all necessary infrastructure hosted at Yotta’s Shakti Data Center.

Dr. Khandekar noted that while complex data analysis traditionally takes several days, the advanced capabilities of the AI lab will allow students and researchers to perform such analysis in significantly shorter time frames.

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