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Aloha Pythonistas!

We have another jam packed meeting for July. This time, Ka’imi will give a keynote on LLM Frameworks and Agentic workflows (details below), Chris will report back on everything he saw at the AI Engineer World Fair, and we’ll top it off with lightning talks from the community. As always, we’ll have food and drinks as well.

**UPDATE:** we will have a Zoom link for this meeting: https://us02web.zoom.us/j/83723771019?pwd=8uaBK85mfDxjbAH7PQD2vGCbW59Yfs.1

5-5:20 – introductions
5:20: AI Engineer World Fair recap (Chris)
5:45: LLM Frameworks (Ka’imi)
6:30: Lightning Talks ([submit talk topic](https://docs.google.com/forms/d/1l3P4ZcCm6DZRQsy4HQytmGujN13p7XAr4AHg07xIj6E/edit))
7:00: open networking

**Keynote Description**
Join us for an insightful session on Large Language Models (LLMs) and Generative AI, designed for software developers of all skill levels. We’ll cover the essentials of LLM frameworks like LangChain and LlamaIndex, exploring their roles and unique features. You’ll see a live demonstration of rapid GenAI prototyping and learn how to use LLM tools and agent functionalities, enabling LLMs to interact with various systems and perform tasks such as querying APIs, accessing databases, and conducting web searches to augment responses. We’ll also discuss different framework options and share advanced tips for developing mature projects. This event is a great opportunity to expand your knowledge and skills in AI development.

**About Ka’imi**
Kaʻimi Kahihikolo, a data scientist at Booz Allen Hamilton, brings extensive expertise in developing AI-powered applications, encompassing computer vision, natural language processing, and reinforcement learning. With a background in astrophysics and a strong foundation in mathematics, he specializes in creating proprietary machine learning and artificial intelligence algorithms. He has conducted award-winning research across diverse fields such as astrophysics, bioinformatics, and geology. A three-time NASA research fellow and experienced public speaker, Kaʻimi is passionate about applying machine learning techniques to intellectually challenging tasks and learning new technologies and tools. (https://www.kaimi.dev/)

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