Discussion on deep autoregressive models and transformer architectures for time-series applications.

Hands-on exercise to build, fine-tune, and apply the Lag-Llama transformer to time-series data.

Hands-on exercise building a lightweight transformer for time-series prediction.

Postgres and the Artificial Intelligence Landscape, artificial intelligence use has exploded, with much anticipation about its future. This talk explores many of the advances that has fueled this explosion, including multi-dimensional vectors, text embeddings, semantic/vector search, transformers, generative AI, and Retrieval-Augmented Generation (RAG). The talk includes semantic/vector search and RAG examples. It covers how the valuable data stored in databases can be used to enhance AI usage.

Unlock the power of AI agents—even if you’re just starting out. In this hands-on, beginner-friendly workshop, you'll go from understanding how Large Language Models (LLMs) work to building a real AI agent using Python, LangChain, and LangGraph. Live Demo: Your First AI Agent — follow along as we build an AI agent that retrieves, reasons, and responds using LangChain and LangGraph.

Session on 2025-02-23 focusing on fine-tuning techniques for a pre-trained model, in line with the series described in the description.

In this demo intensive session Alan will show you how to use Azure Open AI Service to build natural language solutions from scratch. He will explain basic concepts of natural language processing, such as tokens, embeddings, and transformers. He will demonstrate how to use the Azure Open AI Service portal to create and deploy natural language models using pre-trained or custom data. He will also show you how to use the Azure Open AI Service SDK to interact with the models programmatically and integrate them with other Azure services.

A beginner-friendly workshop covering how LLMs work, NLP basics, transformers & attention, prompt engineering, and building AI agents with Retrieval-Augmented Generation (RAG). Includes a live demo: Your First AI Agent.

Hands-on, beginner-friendly workshop covering LLM basics, Python, LangChain, LangGraph, retrieval-augmented generation (RAG), prompt engineering, LangChain introduction, and workflow automation with LangGraph, including a live demo of building your first AI agent.

We will trace 3D reconstruction from classical SfM/MVS to the deep-learning shift, transformer-based models like VGGT that tackle multiple 3D vision tasks at once. This talk is for anyone at the intersection of deep learning and 3D vision who wants to understand how these tools are redefining the state of the art and the future of spatial AI.

Foundations of LLMs and Python Basics; Understanding Natural Language Processing; Transformers and Attention; LLM Development: Fine-tuning and Prompt Engineering; Retrieval-Augmented Generation (RAG); Introduction to LLM Agents; Advanced Topics for Production LLM Application