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IIT Kharagpur today announced that it will collaborate with Amazon Web Services, Inc. (AWS), an Amazon.com company, to develop a National Artificial Intelligence Resource Portal (NAIRP) platform powered by Amazon SageMaker to promote learning and development in Artificial Intelligence (AI) for all AI learners, practitioners, and researchers in India, and to make the search for AI learning resources simpler and more accessible.
IIT Kharagpur will use AWS Promotional Credits and Amazon SageMaker services to facilitate AI learning. In March 2019, IIT Kharagpur adopted the AWS Educate program to help students gain in-demand cloud computing skills, including hands-on AI experience on AWS Cloud.
NAIRP will provide access to computing facilities to users for AI learning and experimentation. Novice machine learning practitioners will be able to quickly search and get access to myriads of learning resources, and prototype the learned concepts into hands-on running modules without being held back by the lack of resources. In addition to this, the opportunity for joint research will facilitate the participation of students and researchers in contributing to open-source educational resources and workbook development for AI-related tasks.
“The contributions from AWS will enable us to provide cloud computing to all learners and reduce the high barrier to make training in AI more available,” said Professor Partha Pratim Chakrabarti, who conceptualized the development of NAIRP.
“There is already a great demand for professionals skilled in AI as well as resources, and this need will only increase in our society. The development of this platform will help boost the AI community in India,” said Professor Sudeshna Sarkar, Head, Centre for Artificial Intelligence at IIT Kharagpur.
Bratin Saha, Vice President AWS Machine Learning & Engines said, “AWS is delighted to work with IIT Kharagpur in developing the NAIRP platform powered by Amazon SageMaker, and we are excited about the opportunity to help make machine learning skills available to every developer. With more than 200 significant machine learning capabilities launched in the last two years, AWS has the broadest and deepest set of machine learning and AI services focused on solving some of the toughest challenges facing developers. We welcome the opportunity to work with IIT Kharagpur on some of those challenges.”
NAIRP was launched with initial funding from the Ministry of Human Resources Development, as part of the National Digital Library of India (NDLI) platform. NAIRP builds upon and expands NDLI to AI by indexing a wide variety of AI-specific resources such as learning materials, courses, workbooks, datasets, codes, tools and platforms. The resources will be classified by a comprehensive AI classification ontology and metadata standard which IIT Kharagpur is developing. AI resources from AWS as well as a variety of other sources such as Kaggle, GitHub, and National Programme on Technology Enhanced Learning (NPTEL) will also be indexed.
The National Artificial Intelligence Resource Portal will provide search, browse, learning and computation services. The support for learning will be in the form of several structured learning modules with instructional materials and workbooks, as well as through indexing of available courses and materials from NPTEL and other sources. Hands-on AI training will be facilitated through workbooks and the cloud. The system will start off using AWS Cloud, and will also be connected in the future with the in-house cloud developed at IIT Kharagpur.
They did this summer. And the result was the winning idea of Bits n Bytes, followed by the projects of team EduFYI and TinTEd-AI which won the 1st runner-up and 2nd runner-up prizes respectively. EduFYI proposed an AI tool to automatically guide its users through a distance learning course, helping them to learn faster and more efficiently. TinT-AI proposed an AI-based Intelligent Automated Software Applications (iASA) to replace the prevalent ASA or Applicant Tracking Systems in the recruitment industry.
Hari Chandana says, “Compared to the existing approaches that focus on traffic signal optimization for a single intersection, our approach is based on a collaborative control of traffic signal phases of multiple intersections.” As the model uses Independent Q-Learning, it takes all the other intersections as part of the environment and gets to train on a wider sample of data.
The model, the team says, is adaptable and can be used to control traffic in any area, by simulating the road network and training the model on it. The model can then be used to intelligently control the real-time traffic in that particular road network.
Divyansh, who was guided by Prof. Jiaul Paik, says, “For our task, we decided to classify the questions based on Bloom’s taxonomy.” The project termed “ConvNets with BiLSTMs for Question Category classification using ELMo Embeddings” has led to a model that has showed 80 per cent test accuracy and, it is hoped, will improve personalized learning such as in the online MOOC sector.
His ‘Tint’ has several components – Resume Job Matcher, Job Recommender System, Automatic Resume Summarizer based on NLP and Automatic Resume Scoring that takes into account not only how the resume scores across different fields of education and professional degrees but also word count per section such as experience, leadership, projects etc. Aniket says, “Strategic use of AI, combined with the personal touch of human recruiters can help companies fill open positions faster and with more qualified candidates.”
Many of the participants have plans to further develop their ideas. Kumar Aniket, for example, wants to develop a Virtual Interview Analyzer. Prof. Sudeshna Sarkar, Head of the CoE for AI, said, “Up.AI tapped into the massive interest of students in AI. I hope that in the coming days, they will develop their interests and come up with more robust solutions using AI.”