AI & Prompt Engineering Meetup Munich

Join us for the first-ever Munich AI & Prompt Engineering Meetup, an interdisciplinary gathering for AI newbies and experts from all economic backgrounds. This new event aims to provide a common platform for knowledge sharing and networking among fans of AI and prompt engineering. We want to bring together business professionals, developers, and researchers to demonstrate the current capabilities of Generative AI and to discuss potential business applications.

We'll dive deep into exploring the world of Artificial Intelligence, its dynamic growth, innovations, applications, and emerging trends. With a special focus on Prompt Engineering, the event offers valuable insight on crafting effective prompts for enhanced responses and outcomes with generative AI tools like ChatGPT and a unique opportunity to delve into the technology that powers Large Language Models and other AI tools.

In this first event, you can look forward to two informative talks (see abstracts below) accompanied by networking opportunities over pizza and drinks.

Let's explore the future together!

Abstracts:

From Zero to ChatGPT Hero: Mastering Prompt Engineering

TNG, Martin Förtsch und Thomas Endres

Are you ready to take your prompt engineering skills to the next level? In this presentation we will dive into the fascinating world of ChatGPT.

The speakers will go into the basics of GPT and the special capabilities of one of the currently most powerful text-based dialogue systems.

One key aspect we’ll focus on is understanding how to do prompt engineering. Prompt optimization can dramatically improve the quality of ChatGPT responses. We cover some best practices for constructing prompts, such as few-shot or chain-of-thought prompting.

You'll leave this talk with a deeper understanding of ChatGPT, as well as practical tips for improving your prompt engineering skills.

Exploring H2O LLM Studio and H2O GPT for Customizing Large

Language Models

*H2O.ai*

This presentation delves into the capability of customizing large language models (LLMs) through the utilization of open-source tools provided by H2O.

To begin, we will introduce H2O LLM Studio. This UI-based framework enables the fine-tuning of LLMs using proprietary datasets. It facilitates the creation of personalized models capable of comprehending and effectively communicating within domain-specific contexts.

Subsequently, we will showcase H2O GPT, a platform designed for seamlessly integrating custom knowledge, such as information from PDFs, into language models. We will introduce vector databases, which empower the augmentation of LLMs with bespoke knowledge.