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AI in DevOps: Streamlining Software Deployment and Operations

Unite.AI

As emerging DevOps trends redefine software development, companies leverage advanced capabilities to speed up their AI adoption. That’s why, you need to embrace the dynamic duo of AI and DevOps to stay competitive and stay relevant. How does DevOps expedite AI?

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Code Evolution: Transforming Software Development with Generative AI Adoption

Becoming Human

In software development, staying ahead of the curve is vital for businesses that needs to deliver innovative and efficient solutions. The use of Generative AI is one of the most exciting technological developments that is changing the pattern for software development.

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Top 6 Kubernetes use cases

IBM Journey to AI blog

Overview of Kubernetes Containers —lightweight units of software that package code and all its dependencies to run in any environment—form the foundation of Kubernetes and are mission-critical for modern microservices, cloud-native software and DevOps workflows.

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MLOps and the evolution of data science

IBM Journey to AI blog

The paper suggested creating a systematic “MLOps” process that incorporated CI/CD methodology commonly used in DevOps to essentially create an assembly line for each step. MLOps aims to streamline the time and resources it takes to run data science models using automation, ML and iterative improvements on each model version.

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Top Online Courses on Google Gemini

Marktechpost

Google Gemini AI Course for Beginners This beginner’s course provides an in-depth introduction to Google’s AI model and the Gemini API, covering AI basics, Large Language Models (LLMs), and obtaining an API key. It’s ideal for those looking to build AI chatbots or explore LLM potentials.

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10 Ways Artificial Intelligence is Shaping Secure App Development

Unite.AI

Additionally, AI can benchmark an app's security features against established industry standards and best practices. For example, if an app's encryption protocols are outdated, AI can suggest the necessary upgrades. AI recommends safer libraries, DevOps methods, and a lot more.

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What is MLOps

Towards AI

Pietro Jeng on Unsplash MLOps is a set of methods and techniques to deploy and maintain machine learning (ML) models in production reliably and efficiently. Thus, MLOps is the intersection of Machine Learning, DevOps, and Data Engineering (Figure 1). Background Saying that MLOps is in a state of flux would be an understatement [7].

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