Google is set to launch the Agricultural Landscape Understanding (ALU) Research API, a tool to enhance agricultural practices through data-driven insights. Jeanine Banks, Vice President and General Manager of Developer X at Google, announced this at the Google I/O Connect event in Bengaluru in 2024.
The ALU Research API is designed to improve farm yields, enhance access to capital, and provide market access for farm products. Google is already working with several technology partners,, such as Ninjacart, Skymet, Team-Up, IIT Bombay, and the Government of India,, to explore the use of ALU information.
Ambharish Kenghe, Google’s Vice President, emphasized the company’s commitment to empowering Indian innovators to harness AI’s full potential, creating solutions that address India’s unique needs,, and shaping the future of AI globally. He highlighted the vast opportunities with multimodal, mobile, and multilingual AI and expressed excitement about being part of India’s AI journey.
The ALU tool aims to provide detailed landscape insights at the farm field level, essential for transforming the agricultural ecosystem. Currently, insights are available at an aggregate level, but interventions at an individual farm level are needed.
The ALU API can demarcate field boundaries using high-resolution satellite imagery and machine learning. This helps address issues like drought preparedness, irrigation problems, and market access challenges. The tool can offer granular details, including crop type, field size, and distances to water, roads, and markets.
In addition to advancements in agriculture, Google is also making significant strides in the Indian language space. The Google DeepMind team in India has shared updates that would empower developers to build language-based solutions for India. This includes expanding Project Vaani with the Indian Institute of Science (IISc). Project Vaani, for example, provides developers with over 14,000 hours of speech data across 58 languages, collected from 80,000 speakers from over 80 districts.
The team also introduced IndicGenBench, a comprehensive benchmark designed to evaluate the generation capabilities of large language models (LLMs) in Indic languages. IndicGenBench covers 29 languages, many of which have never been benchmarked before. This provides a valuable resource for assessing and fine-tuning language models.
Google is also open-sourcing the CALM (Composition of Language Models) framework. This allows developers to combine their specialized language models with Gemma models, creating better solutions for India’s linguistic variations.
Google has recently announced a significant price cut for its API services on the Maps platform, specifically for Indian developers. This move is part of Google’s strategy to reinforce its dominance in the mapping services market by making its tools more accessible and affordable.
The company is reducing API prices by up to 70 percent, aiming to facilitate more accessible and cost-effective integration of Google Maps into various applications developed in India. This initiative not only enhances accessibility but also serves as a competitive response to Ola’s recent efforts to promote Ola Maps. Ola has been enticing developers with its platform by offering specialized features and localized solutions at a more affordable rate.
By significantly lowering API costs, Google aims to maintain its competitive edge and appeal to a broader base of Indian developers, ensuring that its Maps platform remains a top choice for integration into apps.
