Microsoft Research Cambridge

Machine Intelligence

Advanced machine learning research, grounded in trust, efficiency, capability.

KBLaM blog | A flowchart illustrating the process of handling a prompt using a language model. The process begins with documents being used to construct and summarize a knowledge base (KB) offline. The summarized KB is then encoded and fed into the main process. A prompt goes through a tokenizer, followed by rectangular attention, and then into the large language model (LLM). The LLM retrieves information from the encoded KB to generate an answer.

Introducing KBLaM: Bringing plug-and-play external knowledge to LLMs

Layered image of Phi Silica, a state-of-the-art small language model integrated into Windows 11 Copilot+PCs

Phi Silica, small but mighty on-device SLM

A Ladder of Reasoning: Testing the power of imagination in LLMs

キャリアの機会

Principal Research Manager/Senior Principal Research Manager

Posted: September 2, 2026

場所: Microsoft Research Lab – Cambridge

研究分野: Artificial intelligence, Search and information retrieval

The Machine Intelligence team at Microsoft Research Cambridge conducts foundational research aimed at understanding and advancing machine intelligence. We explore the principles that enable intelligent systems to learn, reason, remember,…