Google Enhances AI Focus in India with Language, Agri Tools
Currently, the chatbot supports nine Indian languages - Hindi, Bengali, Gujarati, Kannada, Malayalam, Marathi, Tamil, Telugu and Urdu.
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Google introduced IndicGenBench, a comprehensive benchmark designed specifically for Indian languages. This initiative aims to assess and fine-tune language models for more accurate and effective use in India. (Image: Freepik)
Kolkata: Google is intensifying its focus on India with the introduction of advanced AI tools aimed at breaking down language barriers and enhancing agricultural practices, a senior company official said.
Abhishek Bapna, Director of Product Management at Google DeepMind, highlighted the importance of reducing language barriers in India's economic development.
"Language is very essential for economic development. For instance, a language barrier should not hinder someone from explaining their medical issues to a doctor or accessing banking services," Bapna said during his short visit to IIM Calcutta.
The tech giant has launched Google Gemini, formerly known as Bard, an artificial intelligence chatbot that supports more than 40 global languages, including nine Indian languages.
Bapna added that Google's ongoing focus is on continuously improving language quality and expanding support for more Indian languages in the future. Currently, the chatbot supports nine Indian languages - Hindi, Bengali, Gujarati, Kannada, Malayalam, Marathi, Tamil, Telugu and Urdu. Bapna noted the complexity of India's multilingual environment, where people often use multiple languages simultaneously.
This presents unique challenges for AI models, as they must correctly identify and apply the appropriate dictionaries to understand and generate accurate responses, Bapna said.To empower developers in India, Google is expanding Project Vaani in collaboration with the Indian Institute of Science (IISc).
The project offers developers over 14,000 hours of speech data across 58 languages, collected from 80,000 speakers in 80 districts.
Additionally, Google introduced IndicGenBench, a comprehensive benchmark designed specifically for Indian languages. This initiative aims to assess and fine-tune language models for more accurate and effective use in India.
In a parallel effort to support India's agricultural sector, Google is working towards launching the Agricultural Landscape Understanding (ALU) Research API. This limited availability tool is designed to make agricultural practices more data-driven and efficient.
The ALU API aims to enhance farm yields, improve access to capital, and provide better market access for farm products.
"On agriculture, right now we are conducting a pilot with the Telangana government that is already underway. Once the pilot is complete, we plan to scale it up and engage actively with state governments," Bapna said.
He emphasized that Google's agricultural initiatives are driven by two major goals: improving livelihoods and addressing climate change through necessary interventions.
"Banks and insurance companies could also be end users. Right now our focus is to make sure that the technology works properly," Bapna said.
By offering granular landscape insights at the farm field level, the ALU API is expected to transform India's agricultural ecosystem.
Abhishek Bapna, Director of Product Management at Google DeepMind, highlighted the importance of reducing language barriers in India's economic development.
"Language is very essential for economic development. For instance, a language barrier should not hinder someone from explaining their medical issues to a doctor or accessing banking services," Bapna said during his short visit to IIM Calcutta.
The tech giant has launched Google Gemini, formerly known as Bard, an artificial intelligence chatbot that supports more than 40 global languages, including nine Indian languages.
Bapna added that Google's ongoing focus is on continuously improving language quality and expanding support for more Indian languages in the future. Currently, the chatbot supports nine Indian languages - Hindi, Bengali, Gujarati, Kannada, Malayalam, Marathi, Tamil, Telugu and Urdu. Bapna noted the complexity of India's multilingual environment, where people often use multiple languages simultaneously.
This presents unique challenges for AI models, as they must correctly identify and apply the appropriate dictionaries to understand and generate accurate responses, Bapna said.To empower developers in India, Google is expanding Project Vaani in collaboration with the Indian Institute of Science (IISc).
The project offers developers over 14,000 hours of speech data across 58 languages, collected from 80,000 speakers in 80 districts.
Additionally, Google introduced IndicGenBench, a comprehensive benchmark designed specifically for Indian languages. This initiative aims to assess and fine-tune language models for more accurate and effective use in India.
In a parallel effort to support India's agricultural sector, Google is working towards launching the Agricultural Landscape Understanding (ALU) Research API. This limited availability tool is designed to make agricultural practices more data-driven and efficient.
The ALU API aims to enhance farm yields, improve access to capital, and provide better market access for farm products.
"On agriculture, right now we are conducting a pilot with the Telangana government that is already underway. Once the pilot is complete, we plan to scale it up and engage actively with state governments," Bapna said.
He emphasized that Google's agricultural initiatives are driven by two major goals: improving livelihoods and addressing climate change through necessary interventions.
"Banks and insurance companies could also be end users. Right now our focus is to make sure that the technology works properly," Bapna said.
By offering granular landscape insights at the farm field level, the ALU API is expected to transform India's agricultural ecosystem.
( Source : PTI )
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