Generative Large Language Models (LLMs) have achieved remarkable advancements in various NLP tasks. In this work, our aim is to explore the multilingual capabilities of large language models by using machine translation as a task involving English and 22 Indian languages. We first investigate the translation capabilities of raw large language models, followed by exploring the in-context learning capabilities of the same raw models. We fine-tune these large language models using parameter efficient fine-tuning methods such as LoRA and additionally with full fine-tuning. Through our study, we have identified the best performing large language model for the translation task involving LLMs, which is based on LLaMA. Our results demonstrate significant progress, with average BLEU scores of 13.42, 15.93, 12.13, 12.30, and 12.07, as well as CHRF scores of 43.98, 46.99, 42.55, 42.42, and 45.39, respectively, using 2-stage fine-tuned LLaMA-13b for English to Indian languages on IN22 (conversational), IN22 (general), flores200-dev, flores200-devtest, and newstest2019 testsets. Similarly, for Indian languages to English, we achieved average BLEU scores of 14.03, 16.65, 16.17, 15.35 and 12.55 along with chrF scores of 36.71, 40.44, 40.26, 39.51, and 36.20, respectively, using fine-tuned LLaMA-13b on IN22 (conversational), IN22 (general), flores200-dev, flores200-devtest, and newstest2019 testsets. Overall, our findings highlight the potential and strength of large language models for machine translation capabilities, including for languages that are currently underrepresented in LLMs.

Hyderabad: Select Government school complexes (a cluster of high school, middle and primary schools) in the State may soon get to use some artificial intelligence based tools that will automate a few of the time and resources consuming processes like formative assessments, marking attendance, logging mid-day meals data among others. They will even be put to use to teach English and later other languages too. These artificial intelligence-based tools will be implemented in select school complexes in Moinabad as a pilot project through the Prof Raj Centre at IIIT-H, which is working to create artificial technologies and technology solutions for the grassroots. A team from the IIIT-H had initial meetings with select school complex head masters, resource persons and officials of the Education Department to understand problems at the grass-root level. "We plan to meet the concerned people once again and make specific plans for the technology interventions possible. We want to keep the technologies ready for the coming academic year. These will be short term projects of three to six months that aim to address the issues at the earliest," said Ramesh Loganathan, Co-Innvation Professor at IIIT-H.

Arka Media Works, the makers of the movie Bahubali, has tied up with the Centre for Innovation and Entrepreneurship (CIE) at IIIT Hyderabad to set up Media-Tech Accelerator to promote startups working in media technologies. "Movie production in the country now leverages many of the latest technologies available globally," Shobu Yarlagadda, Co-Founder and Chief Executive Officer of of Arka Media Works, has said. "This accelerator will support Indian innovators and start-ups in creating new technology driven solutions for the media and entertainment sector. The possibilities are immense," he said. The accelerator will help the shortlisted start-ups to benefit from cutting-edge research work being done at the International Institute of Information Technology (IIIT-Hyderabad).

Sign in to report inappropriate content. Docturnal is a point-of-care screening and diagnostics provider enabling non-invasive and proactive detection of diseases. Docturnal products are designed to make detection of diseases easy and hassle-free. In this #CASESTUDY, we have Rahul Pathri, Founder & CEO, talk about how Docturnal creates point-of-care, non-invasive, real-time results driven solutions leveraging AI/Deep Learning under the umbrella of telemedicine.