AboutTermsPrivacyContact
 
Updating
The Data Flowcast: Mastering Airflow for Data Engineering & AI

The Data Flowcast: Mastering Airflow for Data Engineering & AI

Released: 2024-05-29
© All rights reserved
The Data Flowcast: Mastering Airflow for Data Engineering & AI - QR Code
18 Episodes
Audio
Listen on Apple Podcasts
18 Episodes
Audio
Listen on Apple Podcasts
Released: 2024-05-29
© All rights reserved
Most Recent Episode
The Future of AI in Data Engineering With Astronomer’s Julian LaNeve and David Xue

The Future of AI in Data Engineering With Astronomer’s Julian LaNeve and David Xue

The world of data orchestration and machine learn…
Time: 23:36
The world of data orchestration and machine learning is rapidly evolving, and tools like Apache Airflow are at the forefront of these changes. Understanding how to effectively utilize these tools can significantly enhance data processing and AI model deployment.
This episode features Julian LaNeve, CTO at Astronomer, and David Xue, Machine Learning Engineer at Astronomer. They delve into the intricacies of data orchestration, generative AI and the practical applications of these technologies in modern data workflows.
Key Takeaways:
(01:51) The pressure to engage in the generative AI space.
(02:02) Generative AI can elevate data utilization to the next level.
(02:43) The transparency issues with commercial AI models.
(04:27) High-quality data in model performance is crucial.
(06:40) Running new models on smaller devices, like phones.
(12:19) Fine-tuning LLMs to handle millions of task failures.
(16:54) Teaching AI to understand specific logs, not general passages, is a goal.
(21:56) Using Airflow as a general-purpose orchestration tool.
(22:00) Airflow is adaptable for various use cases, including ETL and ML systems.
Resources Mentioned:
Julian LaNeve - https://www.linkedin.com/in/julianlaneve/
Atronomer - https://www.linkedin.com/company/astronomer/
David Xue - https://www.linkedin.com/in/david-xue-uva/
Apache Airflow - https://airflow.apache.org/
Meta’s Open Source Llama 3 model: https://ai.meta.com/blog/meta-llama-3/https://ai.meta.com/blog/meta-llama-3/
Microsoft’s Phi-3 model: https://www.microsoft.com/en-us/research/publication/phi-3-technical-report-a-highly-capable-language-model-locally-on-your-phone/
GPT-4 - https://www.openai.com/research/gpt-4
Thanks for listening to The Data Flowcast: Mastering Airflow for Data Engineering & AI. If you enjoyed this episode, please leave a 5-star review to help get the word out about the show. And be sure to subscribe so you never miss any of the insightful conversations.
#ai #automation #airflow #machinelearning
Episode ID: 1000657209143
GUID: tag:soundcloud,2010:tracks/1833134607
Release Date: 29/05/2024, 20:49:32

Description

Welcome to The Data Flowcast: Mastering Airflow for Data Engineering & AI — the podcast where we keep you up to date with insights and ideas propelling the Airflow community forward.
Join us each week, as we explore the current state, future and potential of Airflow with leading thinkers in the community, and discover how best to leverage this workflow management system to meet the ever-evolving needs of data engineering and AI ecosystems.
Podcast Webpage: https://www.astronomer.io/podcast/

Apple Podcasts: Customer Reviews

No Entry