9:30 dop. - 10:30 dop. (UTC)

In In this episode, we’ll introduce the AI Toolkit extension for VS Code a powerful way to explore and integrate the latest AI models from OpenAI, Meta, Deepseek, Mistral, and more. With this extension, you can browse state-of-the-art models, download some for local use, or experiment with others remotely. Whether you're enhancing an existing application or building something new, the AI Toolkit simplifies the process of selecting and integrating the right model for your needs.

9:30 dop. - 10:30 dop. (UTC)

In this episode, we’ll explore Small Language Models (SLMs) and how they compare to larger models. SLMs are efficient, require less compute and memory, and can run on edge devices while still excelling at a variety of tasks. We’ll dive into the Phi-3.5 and Phi-4 model series and demonstrate how to build a practical application using these models. We will also look at reasoning models like OpenAI o1,o3 and DeepSeek R1 and how they work differently as compared to regular LLMs. Learn more: https://aka.ms/Learn-Collection

9:30 dop. - 10:30 dop. (UTC)

In this episode, we’ll dive into embedding models—important tools for working with vector databases and large language models. These models convert text into numerical representations, making it easier to process and retrieve information efficiently. After covering the core concepts, we’ll apply them in practice by building a Retrieval-Augmented Generation (RAG) app using Small Language Models (SLMs) and a vector database. Learn more: https://aka.ms/Learn-Collection