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Train Your Own Private ChatGPT Model for the Cost of a Starbucks Coffee

The birth of ChatGPT has undoubtedly filled us with anticipation for the future of AI. Its sophisticated expression and powerful language understanding ability have amazed the world. However, because ChatGPT is provided as a Software as a Service (SaaS), issues of personal privacy leaks and corporate data security are concerns for every user and company. More and more open-source large-scale models are emerging, making it possible for individuals and companies to have their own models. However, getting started with, optimizing, and using large-scale open-source models have high barriers to entry, making it difficult for everyone to use them easily. To address this, we use Apache DolphinScheduler, which provides one-click support for training, tuning, and deploying large-scale open-source models. This enables everyone to train their own large-scale models using their data at a very low cost and with technical expertise.

Who Is It For? Anyone in Front of A Screen

Our goal is not only for professional AI engineers but for anyone interested in GPT to enjoy the joy of having a model that “understands” them better. We believe that everyone has the right and ability to shape their own AI assistant. The intuitive workflow of Apache DolphinScheduler makes this possible. As a bonus, Apache DolphinScheduler is a big data and AI scheduling tool with over 10,000 stars on GitHub. It is a top-level project under the Apache Software Foundation, meaning you can use it for free and modify the code without worrying about any commercial issues.

Whether you are an industry expert looking to train a model with your own data, or an AI enthusiast wanting to understand and explore the training of deep learning models, our workflow will provide convenient services for you. It solves complex pre-processing, model training, and optimization steps and only requires 1–2 hours of simple operations, plus 20 hours of running time to build a more “understanding” ChatGPT large-scale model.

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Tribute to the Passing of Teradata Automation

On February 15, 2023, Teradata officially withdrew from China after 26 years. As a professional data company like Teradata, I feel so regretful about this. As an editor of WhaleOps, I am also a fan of Teradata, and keep an eye on the development of Teradata’s various product lines. When everyone is thinking about the future of the Teradata data warehouse, they ignore that Teradata actually has a magic weapon, that is, the data warehouse scheduling suite Teradata Automation that comes with the Teradata data warehouse.

The rapid development of Teradata in the world, especially in Greater China, is inseparable from the assistance of Teradata Automation. Today, we are here to remember the history of Teradata Automation and the prospect of the future. We also hope that DolphinScheduler and WhaleScheduler, which have paid tribute to Automation since their birth, can take over the mantle and continue to benefit the next generation of schedulers.