Making Agent Memory Better and Agent Actions Faster with TypeAgent | DEM575

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โ€‹ย We are trying to create human-like memory with super-human precision and recall for agent conversations. We will demo our memory implementation outperforming current systems at answering questions about past conversations such as “what step were we on in building the photo montage?”

We are trying to apply agent interfaces to all applications. To make this possible, we have created a system that can distill language models into logical systems that can handle most user requests.

๐—ฆ๐—ฝ๐—ฒ๐—ฎ๐—ธ๐—ฒ๐—ฟ๐˜€:
* Umesh Madan
* Steven Lucco

๐—ฆ๐—ฒ๐˜€๐˜€๐—ถ๐—ผ๐—ป ๐—œ๐—ป๐—ณ๐—ผ๐—ฟ๐—บ๐—ฎ๐˜๐—ถ๐—ผ๐—ป:
This is one of many sessions from the Microsoft Build 2025 event. View even more sessions on-demand and learn about Microsoft Build at https://build.microsoft.com

DEM575 | English (US) | AI, Copilot & Agents

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