GraphRAG: New tool for complex data discovery now on GitHub Published July 2, 2024 By Darren Edge , Senior Director Ha Trinh , Senior Data Scientist Steven Truitt , Principal Program Manager Jonathan Larson , Senior Principal Data Architect Earlier this year, we introduced GraphRAG (opens in new tab), a graph-based approach to retrieval-augmented generation (RAG) that enables question-answering ov

AI at Work Is Here. Now Comes the Hard PartEmployees want AI, leaders are looking for a path forward. The data is in: 2024 is the year AI at work gets real. Use of generative AI has nearly doubled in the last six months,1 with 75% of global knowledge workers using it. And employees, struggling under the pace and volume of work, are bringing their own AI to work. While leaders agree AI is a busines

Large language models (LLMs) have revolutionized a wide range of tasks and applications that were previously reliant on manually crafted machine learning (ML) solutions, streamlining through automation. However, despite these advances, a notable challenge persists: the need for extensive prompt engineering to adapt these models to new tasks. New generations of language models like GPT-4 and Mixtra

We are inspired by the results of our second Copilot for Security economic study, which shows that experienced security professionals are faster and more accurate when using Copilot, and they overwhelmingly want to continue using Copilot. The gains are truly amazing: Experienced security analysts were 22% faster with Copilot. They were 7% more accurate across all tasks when using Copilot. And, mos

At OpenAI’s first DevDay Conference on November 6, 2023, Microsoft Chairman and CEO Satya Nadella made a surprise appearance during OpenAI CEO Sam Altman’s keynote to deliver a powerful message: “Our job number one is to build the best systems, so you can build the best models and deliver those to developers.” This was a testament to the deep partnership between Microsoft and OpenAI. We’re excited

“Capabilities like AutoGen are poised to fundamentally transform and extend what large language models are capable of. This is one of the most exciting developments I have seen in AI recently.” Doug Burger, Technical Fellow, Microsoft Figure 1. AutoGen enables complex LLM-based workflows using multi-agent conversations. (Left) AutoGen agents are customizable and can be based on LLMs, tools, humans

Today at an event in New York, we announced our vision for Microsoft Copilot—a digital companion for your whole life—that will create a single Copilot user experience across Bing, Edge, Microsoft 365, and Windows. As a first step toward realizing this vision, we’re unveiling a new visual identity—the Copilot icon—and creating a consistent user experience that will start to roll out across all our

Today we’re on the verge of a monumental shift in the technology landscape that will forever change the security community. AI and machine learning may embody the most consequential technology advances of our lifetime, bringing huge opportunities to build, discover, and create a better world. Brad Smith recently pointed out that 2023 will likely mark the inflection point for AI going mainstream, t

Have you ever wanted to tell a robot what to do using your own words, like you would to a human? Wouldn’t it be amazing to just tell your home assistant robot: “Please warm up my lunch“, and have it find the microwave by itself? Even though language is the most intuitive way for us to express our intentions, we still rely heavily on hand-written code to control robots. Our team has been exploring

Simplifying distributed ML through a unified API Writing fault-tolerant distributed programs is complex and a process that’s prone to errors. For example, consider the distributed evaluation of a deep network. The first step is to send a multi-GB model to hundreds of worker machines without overwhelming the network. Then, data readers must coordinate to ensure that all data is queued for processin

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