To cap off a week of AI announcements from OpenAI, Anthropic, and Google, Microsoft announced Copilot for their 365 productivity suite yesterday.
Today, we are bringing the power of next-generation AI to work. Introducing Microsoft 365 Copilot — your copilot for work. It combines the power of large language models (LLMs) with your data in the Microsoft Graph and the Microsoft 365 apps to turn your words into the most powerful productivity tool on the planet.
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Copilot is integrated into Microsoft 365 in two ways. It works alongside you, embedded in the Microsoft 365 apps you use every day — Word, Excel, PowerPoint, Outlook, Teams and more — to unleash creativity, unlock productivity and uplevel skills. Today we’re also announcing an entirely new experience: Business Chat. Business Chat works across the LLM, the Microsoft 365 apps, and your data — your calendar, emails, chats, documents, meetings and contacts — to do things you’ve never been able to do before. You can give it natural language prompts like “Tell my team how we updated the product strategy,” and it will generate a status update based on the morning’s meetings, emails and chat threads.
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AI-powered LLMs are trained on a large but limited corpus of data. The key to unlocking productivity in business lies in connecting LLMs to your business data — in a secure, compliant, privacy-preserving way. Microsoft 365 Copilot has real-time access to both your content and context in the Microsoft Graph. This means it generates answers anchored in your business content — your documents, emails, calendar, chats, meetings, contacts and other business data — and combines them with your working context — the meeting you’re in now, the email exchanges you’ve had on a topic, the chat conversations you had last week — to deliver accurate, relevant, contextual responses.
This entire announcement presents an incredibly corporate version of the AI integration I hope to see from Apple someday.
My dream is to ask Siri, “What was I doing last Saturday?” and receive an accurate summary based on all the data from my devices – including calendar events, geolocation, photos, web browsing history, and more. Siri should function as a continuously fine-tuned personal assistant with the ability to answer queries and generate content in a freeform manner. However, this all poses significant privacy concerns. For that reason, it would be crucial that all aspects – training, inference, and storage – occur exclusively on-device. This would really make all of Apple’s Neural Engine development look prescient.