As Apache Airflow has become the standard for both data processing and machine learning pipelines, it has been foundational in supporting AI applications by providing an easy-to-use platform to build advanced data workflows. 

    The teams at Astronomer and Dosu know this first-hand, applying Generative AI to automate tedious tasks for developers. They use Airflow to support AI use cases with connection management, heightened visibility, and easy setup for data orchestration tasks. 

   Join us for this webinar where resident AI/ML experts will explore: 

- Best practices for successfully getting AI into production 

- Real world applications, including conversational AI, code generation, automated issue triage, and practical examples of model deployment and operational LLMs 

- Unique opportunities and challenges when deploying generative AI at scale 

- How Airflow is supporting AI data pipelines, and why dependable data orchestration is critical

Local ODSC chapter in NYC, USA

Instructor's Bio

Steven Hillion

SVP of Data and AI at Astronomer

Steven is working on applications of Apache Airflow for operational machine learning. Previously, he founded Alpine Data, acquired by TIBCO, to build a collaborative platform for data science. Before that he led engineering at a series of start-ups in open-source machine learning and enterprise analytics. Steven is originally from Guernsey, in the British Isles, and studied mathematics at Berkeley and Oxford University.

Devin Stein

Founder of Dosu

Devin started Dosu to make engineering accessible to everyone. Like an engineering teammate, Dosu uses its understanding of code and code changes to answer undocumented questions from sales, triage customer-facing bugs with support, collaborate on release notes with product, and more. Previously Devin has held positions ranging from product lead, head of engineering, software engineer, data scientist, and developer.


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    ON-DEMAND WEBINAR: "Reliable Data Orchestration for AI Applications"

    • Ai+ Training

    • Webinar recording