Pavan Davuluri
speaker
254 appearances
1 recordings
1 series
first heard Dec 2025
last heard 3 Dec
Pavan Davuluri’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 1 in all, peaking in Dec 2025 with 1.
Appearances
We fundamentally start with what makes most sense for the end user scenario, for the customer value proposition in itself.
We're very much anchored in what can we do to deliver, from a Microsoft perspective, the best end-to-end solution.
And we typically work backwards from there.
The reason why I find that's a helpful way to look at it is because I find the answer will change over time.
Your compute construct will change, the environment in which the device is being used will change.
Exactly.
Model capabilities will change.
How these connectors, for example, will evolve on the edge as they will in the cloud.
So we try to think about what is the end user instance and the value proposition in the use case, and we kind of work backwards from there, I would say.
So a really good example of how the cloud co-pilots work with local AI capabilities are on co-pilot plus devices.
On co-pilot plus devices, we have a capability in Windows called click to do.
And click to do essentially gives you screen understanding
under user control.
And so if you're in an instance where you have a PDF document and you're looking at tables, files, formats that are really complicated and you as a user want to be able to manipulate them, the local device capability gives you the ability to understand the screen a local model runs that takes that screen content and turns it into a tabular format for Excel.
Then you have the power of the M365 Copilot.
In Excel, you can fire up agent mode, be able to manipulate that thing, evolve it, graph it, understand it, run analytics on it.
In my mind, it's a beautiful example of an end-to-end workflow where you start with essentially a static document.
It is essentially a picture or a PDF document that is typically hard to manipulate and synthesize and draw insights from.
And in a matter of two steps with using local AI and then an agent mode in Excel, you really get to an empowered state of being able to do much richer things with that same data set.
We will take that back to our team.
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