Google DeepMind's Morni AI: Bridging Language Gaps Across 125 Indic Languages
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Google DeepMind's Morni AI to cover 125 Indic languages
Google DeepMind's India unit is working on an Indic language AI project called Morni (Multimodal Representation for India) which aims to cover 125 Indian languages and dialects to build inclusive and equitable Indic AI. "So India has 22 scheduled languages, which are viewed as official languages. But in our work, we are targeting over 100 Indian languages, because we find that there are 60 Indian languages which have over a billion speakers and over 125 languages that have over a lakh speakers each," said Manish Gupta, Director of Google DeepMind, Google India. He was speaking at the Global Fintech Fest in Mumbai on Thursday. He explained that 73 out of these 125 languages had zero corpus of digital data available. Even for a languages like Hindi, which is now spoken by close to 10% of the world's population, the share of Hindi text on the internet is 0.1%. Google's research lab overcame the challenge of sourcing data for these languages by launching the project Vaani, a collaboration between Google, the Indian Institute of Science (IISc), and ARTPARK (Artificial Intelligence & Robotics Technology Park). The project has completed its first phase to create an open-source database of over 14,000 hours of speech data across 58 languages, collected from 80,000 speakers in 80 districts, Gupta said. First announced in December 2022, Project Vaani aims to collect and transcribe 154,000 hours of open-source anonymised speech data from all 773 districts of India. Gupta said they are now in the middle of phase two that will cover all states in India spanning 160 districts.
[2]
Google DeepMind's Morni AI to cover 125 Indic languages
Speaking at the Global Fintech Fest, Manish Gupta, Director of Google DeepMind, Google India, said 73 out of these 125 languages had zero corpus of digital data available.Google DeepMind's India unit is working on an Indic language AI project called Morni (Multimodal Representation for India) which aims to cover 125 Indian languages and dialects to build inclusive and equitable Indic AI. "So India has 22 scheduled languages, which are viewed as official languages. But in our work, we are targeting over 100 Indian languages, because we find that there are 60 Indian languages which have over a billion speakers and over 125 languages that have over a lakh speakers each," said Manish Gupta, Director of Google DeepMind, Google India. He was speaking at the Global Fintech Fest in Mumbai on Thursday. He explained that 73 out of these 125 languages had zero corpus of digital data available. Even for a languages like Hindi, which is now spoken by close to 10% of the world's population, the share of Hindi text on the internet is 0.1%. Google's research lab overcame the challenge of sourcing data for these languages by launching the project Vaani, a collaboration between Google, the Indian Institute of Science (IISc), and ARTPARK (Artificial Intelligence & Robotics Technology Park). The project has completed its first phase to create an open-source database of over 14,000 hours of speech data across 58 languages, collected from 80,000 speakers in 80 districts, Gupta said. First announced in December 2022, Project Vaani aims to collect and transcribe 154,000 hours of open-source anonymised speech data from all 773 districts of India. Gupta said they are now in the middle of phase two that will cover all states in India spanning 160 districts.
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Google DeepMind introduces Morni AI, a groundbreaking language model designed to support 125 Indic languages. This innovation aims to enhance digital inclusion and preserve linguistic diversity in India.
Google DeepMind Unveils Morni AI for Indic Languages
In a significant leap towards linguistic inclusivity, Google DeepMind has introduced Morni AI, a cutting-edge language model designed to support an impressive array of 125 Indic languages 1. This groundbreaking development marks a pivotal moment in the realm of artificial intelligence and language processing, particularly for the diverse linguistic landscape of India.
Expanding Digital Inclusion
Morni AI's primary objective is to bridge the digital divide by providing support for languages that have historically been underrepresented in the digital sphere. By encompassing such a wide range of Indic languages, the model aims to make digital content and services more accessible to millions of users across India who primarily communicate in regional languages 2.
Technological Advancements
The development of Morni AI leverages advanced machine learning techniques and vast datasets to create a model capable of understanding and generating content in multiple Indic languages. This technological feat represents a significant advancement in natural language processing, particularly for languages with limited digital resources 1.
Preserving Linguistic Diversity
One of the key aspects of Morni AI is its potential to contribute to the preservation and promotion of India's rich linguistic heritage. By providing robust support for numerous regional languages, the model could play a crucial role in maintaining linguistic diversity in the digital age, ensuring that even less commonly spoken languages have a place in the evolving digital landscape 2.
Implications for Indian Tech Ecosystem
The introduction of Morni AI is expected to have far-reaching implications for India's technology ecosystem. It could potentially catalyze the development of more localized digital services, applications, and content, fostering innovation and entrepreneurship in the Indian tech sector 1.
Challenges and Future Prospects
While Morni AI represents a significant breakthrough, it also faces challenges such as ensuring accuracy across all 125 languages and addressing potential biases in language processing. The future development and refinement of this technology will be crucial in realizing its full potential for digital inclusion and linguistic preservation in India 2.
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