Microsoft Technology Licensing, LLC

Adrian Bonar

Edmund Bernard Nightingale

Reuben R Olinsky

Shawn Cantin Callegari

Devis Lucato

Thales Paulo De Carvalho

Sang Eun Kim

Umesh Madan

Samuel Edward Schillace

Nicholas Becker

Brian Scott Krabach

Ryan H Volum

Mark Karle

Tara Eve Walker

LeRoy F Miller

Mollie Munoz

Jennifer Fox

Nicole E Berdy

Alexander Chao

Abby Harrison

Gina Elizabeth Triolo

The techniques disclosed herein enable systems for spoken natural stylistic conversations with large language models. In contrast to many existing modalities for interacting with large language models that are limited to text, the techniques presented herein enable users to carry a fully spoken conversation with a large language model. This is accomplished by converting a user speech audio input to text and utilizing a prompt engine to analyze a sentiment expressed by the user. A large language model, having been trained on example conversations, by generating a text response as well as a style cue to express emotion in response to the sentiment expressed by speech audio input. A text-to-speech engine can subsequently interpret the text response and style cue to generate an audio output which emulates the sensation of human conversation.

Real-time system for spoken natural stylistic conversations with large language models

In accordance with examples of the present disclosure, a collaborative platform provides a digital collaboration assistant that continuously monitors and analyzes shared meeting contents (e.g., voice, text chat messages, shared links and documents, presentation materials, and the like) by participants during a collaborative meeting in near real-time, periodically updates a structure summary log of the meeting contents that are deemed important during the collaborative meeting, and interacts with the participants throughout the collaborative meeting in near real-time, for example, to answer questions or provide additional information.

Meeting insights with large language models

The disclosed technology is generally directed to updating of applications, firmware and/or other software on IoT devices. In one example of the technology, a request that is associated with a requested update is communicated from a normal world of a first application processor to a secure world of the first application processor. The secure world validates the requested update. Instructions associated with the validated update are communicated from the secure world to the normal world. Image requests are sent from the normal world to a cloud service for image binaries associated with the validated update. The secure world receives the requested image binaries from the cloud service. The secure world writes the received image binaries to memory, and validates the written image binaries.

Secure IoT device update

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Kenmore, WA, United States of America

Adrian Bonar