All Things Open AI 2025

AIOS AI SuperUser Bootcamp

by Mark Hinkle

Become a ChatGPT SuperUser & Build AI Agents for 2025

GenAI RAG Workshop

by John Willis

The “GenAI RAG Workshop” is an immersive, full-day training designed for engineers seeking to harness the power of Retrieval-Augmented Generation (RAG) for AI-driven solutions. Participants will explore foundational concepts, including embeddings, vector databases, and advanced RAG techniques while delving into practical applications of tools like MongoDB Atlas Vector Search. Through a blend of lectures and hands-on labs, this workshop equips attendees with the skills to effectively design, implement, and evaluate RAG pipelines, focusing on optimizing AI systems for precision, scalability, and relevance. By the end of the session, participants will understand how to integrate RAG with cutting-edge vector database tools and frameworks to enhance AI-driven workflows.

Lunch – Day 1

Lunch and a drink will be served on site. We strongly encourage attendees to bring their own bottles and utilize the water bottle filling stations throughout the day. The concession stands on the 2nd floor will also be open from 2:00pm to 4:00pm so that attendees can purchase beverages or snacks if they choose to. The concession stands only take cards – no cash!

Build GCP certification tutor with Gemini, LangChain and Vector Search

by Rishab Kumar

Learn how to architect and implement an AI-powered study companion using Google Cloud’s Vertex AI with Gemini and Vector Search. We’ll dive into the technical implementation of embedding generation, vector storage, and prompt engineering to create a dynamic certification preparation system. This session will cover practical code examples, architecture decisions, and deployment patterns for building production-ready AI applications on Google Cloud.

Hallucinations, Prompt Manipulations, and Mitigating Risk: Putting Guardrails around your LLM-Powered Applications

by Don Shin

Large Language Models (LLMs) offer a future where we can interact with computers naturally like we interact with humans. However amazing this potential, enterprise adoption is still hindered by the risk of hallucinations – the propensity of LLMs to respond inaccurately but in a voice of complete confidence. Also, LLMs by themselves can be easily manipulated by end-user prompts to respond in ways that can damage trust or create liability. In order for LLM-powered applications to be fully utilized in real-world production settings, risk must be mitigated through effective guardrail strategies.

You Don’t Need an AI Strategy, But You Do Need to Be Strategic About AI

by Jessica Hall

There’s so much noise about creating an “AI strategy,” it’s easy to feel like you’re already behind. But here’s the thing: you don’t need an AI strategy or a data strategy. Those things need to serve your business strategy and that requires strategic thinking.