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ingrid kolderup – Software Engineer @ Cisco , kari mo – Software Engineer @ Cisco

In this talk, we will share insights into the use of ML techniques, such as object detection and classification, to improve video meetings on our Cisco devices. We'll discuss our wide range of ML models and their respective use cases. The session will include a focused examination of our head detection model, detailing the fundamental principles and demonstrating the specific functionalities it facilitates to refine the video meeting experience.

machine learning deep learning object detection classification computer vision
peter kemp – Principal Consultant & Digital Transformation @ FSP

Copilot for Microsoft 365 has the power to positively transform the modern workplace. Using LLMs and integrating your data and Microsoft 365 Apps, Copilot for M365 supports employees to be more productive, creative and collaborative. Pete will shared some of our experiences working with a number of organisations on launching Copilot for M365, including some of benefits and challenges it presents.

llms microsoft 365 copilot
ian osvald – Principal Data Scientist @ Mor Consulting

Running models locally on the CPU and possibly a GPU means we can experiment with the latest quantised models on real client data without anything leaving the machine. We can explore text question answering, image analysis and calling these tools via a Python API for rapid PoC experimentation. This quickly exposes the ways that LLMs go weird and maybe that helps us avoid some of the examples of early LLM deployments making embarrassing mistakes!

llama.cpp llms Python cpu gpu quantised models
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