Satya Nadella

Introducing Microsoft-Decision-1, our new model for fast decision-making.

It delivers top performance on structured decision tasks, outperforming both LLMs and other decision models in latency and quality.

We’re already testing it across Microsoft for everything from incident response and quality control to scientific discovery.

Thank you, @POTUS, for this incredible honor today. I'm humbled to stand alongside so many giants of American innovation and looking forward for what we can continue to do together to advance technology and drive American prosperity.

Great to partner with NVIDIA as we kick off this next chapter for Windows.

Thank you @JensenHuang and @sriramk for joining us today!

We’re supercharging Copilot on Windows with Hybrid Intelligence.

With your permission, Copilot can tap into the context on your PC, take action for you, and use local models when it makes sense, giving you more capability while helping your tokens go further.

Today marks a new chapter for Windows, as we bring unmetered intelligence to every desk and every home, and make every PC a place where agents can work securely on your behalf.

Some highlights of what we announced:

• MAI-Code-1.1 Flash: 137B parameter coding model w/ 256K context window, which is now optimized to run on your PC!

• GitHub Copilot now hands off work to local models like MAI-Code-1.1 Flash, helping projects cost a lot less without sacrificing quality.

• With Hybrid Intelligence, Copilot can now take action directly on the PC and keep sensitive work on your device.

• And with Code in Copilot, you can essentially build any software you need on your desktop, without any cloud token spend, and it’s just super at it. You’re no longer limited to what’s in an app store! Your PC becomes an infinite software factory.

• Security is foundational to all this, which is why we are also bringing together Windows and Agent 365 so agents can work within secure boundaries on-device, including MXC a local sandbox for agent execution. Windows becomes your secure agent box!

• All this comes to life on a new generation of devices, like Surface Laptop Ultra, powered by NVIDIA RTX Spark.

Can’t wait to see what you build with all this.

The motivation behind the new Copilot: intelligence is accelerating fast. Now we need to diffuse it everywhere.

We’re building Copilot as a new OS for work that spans every model, every form factor, and every task. Today, we’re announcing our biggest update to Copilot to date, bringing four things together:

· Autopilot: proactive and long-running agent built for the enterprise
· Code: build apps with Copilot, hosted inside your company’s tenant
· Home: Chat + Cowork together
· Office: now fully embedded in Copilot (and Copilot embedded in Office, of course!)

Plus, you can invoke Copilot in Teams, and we’re introducing Today, a proactive experience that surfaces the most important information from across M365 without needing to ask for it.

The way we work is changing and so are our workflows. This update brings AI into that flow, from answering a question, to building an app, to getting work done on your behalf.

Great conversation with @chamath, @Jason, @DavidSacks, and @friedberg on all the work ahead when it comes to diffusing benefits of AI broadly, earning permission from communities, and ensuring AI safety and control.

Great example from @jeffhollan showing how Foundry makes long-running agents enterprise-ready, starting with business outcomes and building security, safety guardrails, auditability, and FinOps into the system from the start, across the entire multi-agent, multi-model workflow.

Quincy, Washington shows what’s possible when you build datacenters with communities, and grow together over time.

Any pursuit of superintelligence has to be grounded in the core principle that if the AI we build is not helping humanity and under human control, it's not worth pursuing.

We also need to accelerate and spread the benefits of AI, such that they are diffused broadly across countries, communities, and companies. This requires a frontier ecosystem in which both closed and open-source models can thrive.

And for firms, it’s imperative that they retain full control over their unique and tacit knowledge. Every organization should be able to build its own continuous learning loop/hill climbing machine, without becoming dependent on any one model provider, and have the ability to embed its own knowledge into models and weights they control.

So, in this context, we welcome the research, focus, and deliberate pacing needed to get alignment right as the design goal. We also welcome ideas like "embedded evaluators" and the broader efforts to develop the mechanisms to make this more than just talk.

The key is that this cannot be controlled by a handful of entities, but must have broad representation across the ecosystem, countries, and fields, including academia.

This is the approach we are taking: broad access and choice at every layer of the AI stack; enterprise control of learning loops and models; and the “Code of Conduct” that underlies our own first party MAI models that we’ll publish tomorrow for public consultation.

More model choice coming to Copilot. Welcome Grok!

With the @NFL back tonight, love seeing @Seahawks analyst Brian Eayrs and coaches across the league using new Copilot and Excel tools to help with decision making in the booths and on the sidelines.

This first-of-a-kind agreement will set a new standard for safe and responsible AI use in schools. We are making these protections available to every school district in the US.

It was a great week for innovation across the model ecosystem. We're bringing these new models into Copilot, enabling it to take on increasingly complex work, from quick questions to delegated tasks and, increasingly, complete long-running jobs through Autopilots.

Here's one fun example: using an Opal-powered Autopilot running on a secure Windows 365 Cloud PC, Copilot goes through a month of trail cam footage, finds every animal sighting, creates a highlight reel of the best clips, labels each one with the camera, date, and species, catalogs every sighting in a spreadsheet, builds a PowerPoint summarizing the findings, and shares everything in Teams for colleagues to review.

This is the next frontier for Copilot: software that doesn't just assist with work, but can own and complete entire tasks that unfold over hours or days.

Super excited about HydraFusion in GitHub Copilot, and what it shows about the shift from model selection to model orchestration.

By bringing together multiple models to plan, build, critique, and complete coding tasks, it can deliver outcomes at up to 67% lower cost.

It’s a great example of the value of a heterogeneous model ecosystem, and how we’re continuing to advance the cost-to-outcome frontier.

Excited to see early customers already using Astra on Azure! azure.microsoft.com/en-us/blog/gpt…

Looking forward to this ecosystem with open models continuing to flourish and grow with NVIDIA and Hugging Face, and the continued partnership. Congrats @JensenHuang and @ClementDelangue!

Delivery day at our Microsoft DCs as the first production Vera Rubins arrive. A huge thank you to our partners at @nvidia and our Azure hardware and datacenter teams for all the incredible work that brought us to this milestone!