Artificial intelligence (AI) has been used in applications throughout industry and academia. Similar to electricity or computers, AI serves as a general-purpose technology that has numerous applications. Its applications span language translation, image recognition, credit scoring, e-commerce and various other domains.
New trends and technologies are emerging that will further shape the future of AI in DevOps. These include the increased use of machine learning models to predict and optimize resource allocation, the development of more sophisticated AI-driven monitoring and alerting tools, and the integration of AI with other emerging technologies such as edge computing and serverless architectures.
Best practices for using AI in DevOps:
Start small and iterate
Involve the right stakeholders
Continuously evaluate and improve
Maintain transparency and accountability
Ensure data quality and security
Incorporate human oversight
Htens AIspace is just the practices to build an AI application with DevOps, it has the practical way to build and scale generative AI applications with foundation models, includes how to use machine learning models and building the application and exposing it to end users: