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DevOps for AI: Continuous deployment pipelines for machine learning systems
AI technology advancements are becoming more common in continuous development and deployment pipelines. The use of AI in these systems has the potential to greatly enhance the efficiency and effectiveness of these pipelines, but this enhancement comes with its own challenges and considerations.
One of the main challenges when considering the use of AI is the oxymoronic nature of data when it comes to machine learning systems. In the traditional software development process, the test and training data sets are created, and then used to develop and deploy the software. However, with machine learning systems, the data itself becomes the software. In other words, the data created to train the machine learning model is not static, but rather dynamic and continually changing. This change, in turn, necessitates that the machine learning system's deployment pipeline be able to respond in kind.
The deployment of AI at scale requires careful planning and the use of AI deployment models. These models work in conjunction with DevOps practices to ensure that the pipeline for a machine learning system is able to deploy code changes and data updates on a continuous basis. The impact of this development on the business is significant, as it allows for the rapid deployment of new AI models, enhanced predictive analytics, and other benefits to the business.
In summary, while there are certain challenges that come with the deployment of AI at scale, the benefits of implementing a DevOps approach with continuous deployment pipelines for machine learning systems far outweigh the drawbacks. Through careful planning and the use of the latest AI deployment models, businesses can take advantage of all that this technology has to offer and use it to drive business growth and success.
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This proposed article is an exploration of how AI can be integrated with DevOps practices to create a new type of continuous deployment pipeline. Typically, DevOps focuses on developing, delivering, and maintaining software products,
Source: AI News, Link
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Posted by ghostaidev Team