Research for Industry

Microsoft Research is exploring the use of LLMs for various industry, aiming to solve domain specific challenges. Our work, highlighted in recent projects and publications, showcases applications to demonstrate how LLMs can transform vertical industries, like agriculture.

Addressing micro-climate prediction workflows for industries and communities Knowledge of micro-climate and micro-climate predictions are of importance in agriculture, forestry, renewable energy systems, architecture, urban design, ecology conservation, maritime and many other domains. Access to high-quality micro-climate predictions is difficult…

Reducing food waste and optimizing production Through the FoodVibes, we are addressing the global food challenge by developing and deploying affordable technology that helps reduce waste and optimize production. Starting from the farms, we focus on production, harvest and post-harvest…

Driving equitable power management With solar & wind technology decentralizing energy production, a new opportunity for driving equity is arising. Communities that are marginalized on electricity grids have the opportunity to power and manage their energy requirements. This project develops…

Democratizing digital tools for sustainable agriculture As one of the biggest contributors to climate change, agriculture, along with land use degradation and deforestation, account for about a quarter of the global GHG emissions and consumes about 70% of the world’s…

By harnessing the power of 6G & Space networks, we strive to bridge the digital divide, enable lightning-fast data transmission, and unleash the potential of ubiquitous and energy-efficient connectivity.

In accordance with Microsoft’s pledge of reaching carbon negativity by 2030 and along with several promising avenues such as Energy 2.0 and agricultural carbon sequestration, we are actively contributing research towards enabling CCS as a viable and cost-efficient technique for…

This project is focused on building tools and techniques to secure the software supply chain.

One goal of Project Paidia, a collaborative research project, is to drive state of the art research in reinforcement learning to enable game agents that learn to collaborate with human players.