Microsoft Research Lab – India
뉴스 & 기능
Research Focus: Week of April 21, 2025
In this issue: our CHI 2025 & ICLR 2025 contributions, plus research on causal reasoning & LLMs; countering LLM jailbreak attacks; and how people use AI vs. AI-alone. Also, SVP of Microsoft Health Jim Weinstein talks rural healthcare innovation.
Aseem Rastogi and Pantazis Deligiannis talk about two technical results from ICSE 2025 on using large language models (LLMs) for safe low-level programming. The results demonstrate LLMs inferring machine-checkable memory safety invariants in legacy C code and how LLMs assist…
Microsoft Research and Physics Wallah team up to enhance AI-based tutoring
| Chris Stetkiewicz
Limited resources, geography, and economic factors present barriers to quality education for many students in India. Learn how Microsoft Research is collaborating with Physics Wallah to make AI-based tutoring more accurate, reliable, and affordable.
Over the past two decades, Microsoft Research India has achieved an extraordinary record of innovation—in areas ranging from health and education to agriculture and accessibility.
Ideas: Building AI for population-scale systems with Akshay Nambi
| Chris Stetkiewicz 그리고 Akshay Nambi
Advances in AI are driving meaningful real-world impact. Principal Researcher Akshay Nambi shares how his passion for tackling real-world challenges across various domains fuels his work in building reliable and robust AI systems.
뉴스에서 | Microsoft Source Asia
Chasing peak sugar: India’s sugar cane farmers use AI to predict weather, fight pests and optimize harvests
The technology brings in weather, soil and other data from satellites as well as farm sensors onto a Microsoft data platform called Azure Data Manager for Agriculture (previously called FarmBeats), so farmers can see precisely what’s happening at their farm…
PromptWizard: The future of prompt optimization through feedback-driven self-evolving prompts
| Akshay Nambi 그리고 Tanuja Ganu
PromptWizard from Microsoft Research is now open source. It is designed to automate and simplify AI prompt optimization, combining iterative LLM feedback with efficient exploration and refinement techniques to create highly effective prompts in minutes.
Abstracts: NeurIPS 2024 with Pranjal Chitale
| Gretchen Huizinga 그리고 Pranjal Chitale
Pranjal Chitale discusses the 2024 NeurIPS work CVQA. Spanning 31 languages and the cultures of 30 countries, this VQA benchmark was created with native speakers and cultural experts to evaluate model performance across diverse linguistic and cultural contexts.
Research Focus: Week of December 2, 2024
Can a new SOS-RMT protocol enable more efficient CL-MPC?; A fair-by-design, cloud-based algorithmic trading platform; LLM2CLIP unlocks richer visual representation; New technique enhances Low-Rank Adaptation’s expressiveness, generalization capabilities.