PromptWizard: The future of prompt optimization through feedback-driven self-evolving prompts
| Akshay Nambi and 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.
Moving to GraphRAG 1.0 – Streamlining ergonomics for developers and users
| Nathan Evans, Alonso Guevara Fernández, and Joshua Bradley
GraphRAG helps advance AI use in complex domains like science. Thanks to enthusiastic adoption and community engagement, we’ve upgraded the pre-release version. Check out the major ergonomic and structural updates in GraphRAG 1.0.
In the news | Harvard Business Review
How Generative AI Improves Supply Chain Management
Over the past few decades, advances in information technologies have allowed firms working to optimize their supply chains to move from decision-making on the basis of intuition and experience to more automated and data-driven methods, which has increased efficiency and…
In the news | MARKTECHPOST
This AI Paper from Microsoft and Novartis Introduces Chimera: A Machine Learning Framework for Accurate and Scalable Retrosynthesis Prediction
Chemical synthesis is essential in developing new molecules for medical applications, materials science, and fine chemicals. This process, which involves planning chemical reactions to create desired target molecules, has traditionally relied on human expertise. Recent advancements have turned to computational…
NeurIPS 2024: AI for Science with Chris Bishop
| Christopher Bishop and Eliza Strickland
From the Microsoft Booth at NeurIPS 2024, Microsoft Research AI for Science Director Chris Bishop discusses how AI is changing approaches to scientific advancement—from drug discovery to weather forecasting—and the profound impact it can have on the world.
Abstracts: NeurIPS 2024 with Jindong Wang and Steven Euijong Whang
| Gretchen Huizinga, Jindong Wang, and Steven Euijong Whang
Researcher Jindong Wang and Associate Professor Steven Euijong Whang explore the NeurIPS 2024 work ERBench. ERBench leverages relational databases to create LLM benchmarks that can verify model rationale via keywords in addition to checking answer correctness.
Rho-1：基于选择token建模的预训练方法
在自然语言处理领域，预训练语言模型常因大规模噪声数据而面临挑战。对此，微软亚洲研究院的研究员们提出了一种新型的基于选择 token 建模的预训练方法。该方法通过选择性语言建模（Selective Language Modeling, SLM）策略，精准筛选出对模型训练有价值的 token，有效提升了数据效率和模型性能。这一突破不仅优化了模型训练过程，也为自然语言处理技术的进一步发展提供了新思路。本...
NeurIPS上新 | 加强多模态协同，提高行业基础模型精度
编者按：欢迎阅读“科研上新”栏目！“科研上新”汇聚了微软亚洲研究院最新的创新成果与科研动态。在这里，你可以快速浏览研究院的亮点资讯，保持对前沿领域的敏锐嗅觉，同时也能找到先进实用的开源工具。 12月10日至12月15日，全球最负盛名的人工智能盛会之一 NeurIPS 大会在加拿大温哥华举办。因此，我们通过三期“科研上新”为大家带来多篇微软亚洲研究院入选 NeurIPS 2024 的精选论文解读，涉...
In the news | Science News Explores
A new frontier awaits — computing with light
In the guts of a new type of computer, a bunch of tiny LEDs emit a green glow. Those lights have a job to do. They’re performing calculations. Right now, this math is telling the computer how to identify handwritten…