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Google has unveiled a series of new AI-powered partnerships aimed at advancing healthcare, sustainability, and agriculture in India.
The tech giant is collaborating with both local and international organisations to implement AI-driven solutions in diabetic retinopathy screening, urban waste management, and agricultural development. According to Google, these announcements were made during a roundtable in Bengaluru, marking the fifth anniversary of Google's Research Lab in the city. This follows the 10th edition of the Google for India event, which showcased the potential of AI to benefit individuals, businesses, and society at large. Dr Manish Gupta, Research Director of Google DeepMind, stated, "Collaborating with key Indian organisations, our focused research in India across language understanding, healthcare, agriculture, and sustainability is helping tackle many of the country's unique challenges and creating AI-led solutions that will improve billions of lives." Google is working with Forus Health and AuroLab in India and Perceptra in Thailand to provide 6 million AI-assisted screenings for diabetic retinopathy over the next decade. These screenings aim to detect and prevent blindness in diabetic patients, particularly in resource-limited communities. The AI model has already supported over 600,000 screenings worldwide, with initial research and deployment carried out in India. Sunny Virmani, Group Product Manager, Health AI Research at Google, remarked, "From our initial research to the first patient screening in Madurai, India, we've been committed to translating AI's potential into meaningful change for people globally. And now the partnerships with Forus Health, AuroLab, and Perceptra are helping us expand on this commitment, as a global network of innovators comes together to eradicate preventable blindness due to diabetic retinopathy." Google's CircularNet, an AI-driven computer vision model for waste management, is being deployed in partnership with Bengaluru-based Saahas Zero Waste. CircularNet helps identify and sort plastic waste, facilitating recycling and reducing the strain on landfills. Powered by Google's TensorFlow, the model has shown approximately 85% accuracy in detecting plastic waste during a pilot programme, potentially boosting revenue for material recovery facilities by 10-12%. To support data-driven decision-making in agriculture, Google is also opening its Agricultural Landscape Understanding (ALU) Research API to developers. The API leverages satellite imagery and machine learning to provide farm-level insights, such as field boundaries, water bodies, and vegetation. The technology aims to optimise resource allocation and guide sustainable farming practices in India. (ANI)
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