Artificial Intelligence
Pursuing computing advances to create intelligent machines that complement human reasoning to augment and enrich our experience and competencies.
Podcast
Abstracts: NeurIPS 2024 with Weizhu Chen
Next-token prediction trains a language model on all tokens in a sequence. VP Weizhu Chen discusses his team’s 2024 NeurIPS paper on how distinguishing between useful and “noisy” tokens in pretraining can improve token efficiency…
Dataset Source Code
HeurAgenix
HeurAgenix is a novel framework based on LLM, designed to generate, evolve, evaluate, and select heuristic algorithms for solving combinatorial optimization problems. It leverages the power of large language models to autonomously handle various optimization…
Podcast
Abstracts: NeurIPS 2024 with Dylan Foster
Can existing algorithms designed for simple reinforcement learning problems be used to solve more complex RL problems? Researcher Dylan Foster discusses the modular approach he and his coauthors explored in their 2024 NeurIPS paper on…
Podcast
Abstracts: NeurIPS 2024 with 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…
Podcast
Ideas: Economics and computation with Nicole Immorlica
When research manager Nicole Immorlica discovered she could use math to make the world a better place for people, she was all in. She discusses working in computer science theory and economics, including studying the…
Microsoft Research Blog
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.
Microsoft Research Blog
MarS: A unified financial market simulation engine in the era of generative foundation models
Microsoft Research presents a new large market model and Financial Market Simulation Engine (MarS) to help empower financial researchers with enhanced efficiency and more accurate insights for downstream tasks in financial markets.
Dataset Source Code
MarS
MarS is a cutting-edge financial market simulation engine powered by the Large Market Model (LMM), a generative foundation model.
Publication