Welcome to the monthly in-person AI meetup in Austin, in collaboration with PMG. Join us for deep dive tech talks on AI/ML, food/drink, networking with speakers and fellow developers.

Agenda:
* 5:30pm~6:00pm: Checkin, Food/drink and networking
* 6:00pm~6:10pm: Welcome/community update
* 6:10pm~8:00pm: Tech talks and Q&A
* 8:00pm~9:00pm: Open discussion and Mixer

Tech Talk: Data Strategy for Gen AI
Speaker: Milan McGraw @AWS
Abstract: Most companies already possess massive silos of valuable data that can serve to train advanced generative AI if properly utilized. However, simply having vast amounts of data is not enough. Companies will only achieve superior generative AI capabilities by implementing a focused data strategy. This requires carefully auditing existing data, identifying gaps for additional collection, eliminating biases, ensuring data quality and diversity, establishing solid data governance policies, and investing in data annotation and other preparations tailored to feeding generative models. With thoughtful data strategies to transform dispersed corporate data into ideal training sets, companies can maximize the performance of state-of-the-art generative algorithms while gaining a marked competitive edge. Even with ample existing data, generative AI dominance relies on strategic and intentional data management uniquely suited to leveraging generative tools.

Tech Talk: Selecting the Right LLM for Organizations: The Importance of Context Length and Benchmark Scores
Speaker: Suprabath Chakilam @Symbl.ai
Abstract: The integration of Large Language Models (LLMs) into diverse industries necessitates a strategic selection of the most suitable model for specific organizational workflows and long-term objectives. A critical factor in this decision-making process is the model context length, which greatly influences its performance and applicability in various scenarios. As the market sees an influx of LLMs, organizations must adeptly navigate this expanding field. A key approach to efficiently assessing and comparing these models is through the analysis of benchmark scores. These scores provide standardized evaluations, helping organizations determine which models optimally align with their specific needs and goals. The combined understanding of a model context length and its benchmark performance offers a comprehensive framework for selecting the most appropriate LLM for an organization unique requirements.

Speakers/Topics:
Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

Venue:
PMG, 515 Congress Ave. #1800, Austin, TX 78701

Sponsors:
* PMG : PMG is the creator of Alli: an AI-powered suite of cloud-based tools for digital marketers. Last year, PMG Alli enabled ad delivery to over 1 Bln consumers in 80+ countries for some of the world’s most iconic brands, including Apple, Nike, and McDonald’s. Established in Fort Worth in 2010, PMG was profitable from day one, and has grown with no outside investment to 700+ employees currently working in 7 offices and remotely. The company is defined by its people-centered culture, and has led AdAge’s annual Best Places to Work list for 8 years in a row.

We are actively seeking sponsors to support AI developers community.  Whether it is by offering venue spaces, providing food, or cash sponsorship. Sponsors will have the chance to speak at the meetups, receive prominent recognition, and gain exposure to our extensive membership base of 5,000+ local or 300K+ developers worldwide.

Community on Slack/Discord
- Event chat: chat and connect with speakers and attendees
- Sharing blogs, events, job openings, projects collaborations
Join Slack (search and join the #austin channel) | Join Discord