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Artificial Intelligence is shaping how modern organizations make decisions, drive critical business outcomes, and support their customers and stakeholders. But behind the innovation is a continually changing set of requirements and best practices that are key to the success of getting AI into production.

Join us for this webinar where resident AI/ML experts from AWS and Astronomer will explore:

● Real world applications driven by Apache Airflow, including conversational AI, code generation, automated troubleshooting, and practical examples of model deployment and operational LLMs ● The unique opportunities and challenges around adopting and deploying generative AI at scale ● How they are also helping their collective customers drive their own AI initiatives ● Top strategies to harness the potential of AI and natural language processing to drive innovation

Panelists:

Steven Hillion \| SVP of Data and AI @ Astronomer David Xue \| Machine Learning Engineer @ Astronomer Parnab Basak Solutions Architect @ Amazon Web Services

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Driving Next-Gen AI Applications with AWS and Astronomer
David Xue – Machine Learning Engineer @ Astronomer , Julian LaNeve – Chief Technology Officer at Astronomer @ Astronomer

Julian and David will cover the Hackathon project they worked on that won at the New York Stock Exchange— fine tuning an LLM to generate summaries for airflow task failures.

llms fine-tuning NLP Airflow
Jarek Potiuk – Independent Open-Source Contributor and Advisor @ Apache Software Foundation

Apache Airflow relies on a silent symphony behind the scenes: its CI/CD (Continuous Integration/Continuous Delivery) and development tooling. This presentation explores the critical role these tools play in keeping Airflow efficient and innovative. We'll delve into how robust CI/CD ensures bug fixes and improvements are seamlessly integrated, while well-maintained development tools empower developers to contribute effectively.

Airflow ci/cd dev tools
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