Hike partners with IIT Delhi on Artificial Intelligence and Machine Learning
Hike has forged a research collaboration with Indraprastha Institute of Information Technology, Delhi (IIIT-D) on artificial intelligence and machine learning. The goal of the research collaboration initiative is to work with stakeholders and academia to help enable more deep-rooted research in AI & ML in the country. As part of this initiative, Hike is looking to collaborate with Indian institutions to help boost the AI & ML ecosystem in India.
This partnership by Hike is also aimed at enabling an ecosystem of research within the country that will help advance technological competence and know-how in the field of AI & ML. This will include new age research-led innovation in the field of Natural Language Processing (NLP), Speech, Link Prediction, Deep Learning and Computer Vision.
“We are extremely excited about the talent & innovation present in this country, through our research collaborations we aim to help nourish this talent further. By facilitating this research opportunity, we want to help enable the Indian academia to connect to early-stage research and support the translation of that research to fuel advancement in the AI & ML ecosystem,” added Anshuman Misra, VP Operations, Hike.
“We are extremely proud to be beginning this partnership with Hike. A project of this depth is one of the first in the AI & ML ecosystems, and we hope this encourages more Indian academia to partner with Hike. We believe this will play a huge role in facilitating our students to help create a future shaped by open research,” said Tanmoy Chakraborty, Director, Laboratory for Computational Social Systems (LCS2), Indraprastha Institute of Information Technology, Delhi.
The company is currently building one of the largest repositories of AI & ML enabled stickers for its recently announced local messaging platform, Hike Sticker Chat. The platform already has over 30,000 stickers across 40 + languages & dialects and aims to have almost 100,000 stickers by the end of the year covering a large chunk of popular local languages & dialects.
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