artificial intelligence
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Autonomous Databases: Self-Driving, Self-Securing, and Self-Repairing Autonomous databases, like Oracle's, automate management tasks, eliminating the need for DBAs. They are self-driving, self-securing, and self-repairing, using AI and machine learning for optimal performance and high availability. |
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The AI Revolution in Software Quality Assurance: A New Era of Quality Engineering and Productivity State-of-the-art AI platforms are transforming SQA. Automation, improved visibility, and streamlined processes are boosting efficiency and effectiveness for QA teams today. As AI evolves, embracing it and developing the necessary skills will be crucial for QA professionals to thrive in the future. |
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Machines and Humans: Finding the Balance in Software Development The rise of AI in software development brings efficiency and innovation, but raises concerns about maintaining a human-centered approach. The key is to find a balance where AI tackles repetitive tasks, freeing up human developers to focus on creativity, empathy, and user-centric design. |
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Generative AI: Pushing Software Development Forward? Generative AI is fundamentally changing software development by automating tasks and improving code quality, but developers need to be aware of its limitations and biases. |
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Exploring the Features of CodeWhisperer and Its Role in the Future of Coding Learn how Amazon CodeWhisperer is uniquely designed to help you develop better code faster, improve security, protect your privacy, and strengthen—not threaten—your career as a coder. |
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How AI and Machine Learning Are Revolutionizing the Manufacturing Industry Manufacturing tasks used to be manual up until the Industrial Revolution. We’re now experiencing another revolution, with technology making processes easier, faster, and more efficient. Today, artificial intelligence and machine learning are automating machine maintenance, optimizing inventory, and even helping out humans. |
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5 Pitfalls to Avoid When Developing AI Tools Developing a tool that runs on artificial intelligence is mostly about training a machine with data. But you can’t just feed it information and expect AI to wave a magic wand and produce results. The type of data sets you use and how you use them to train the tool are important. Here are five pitfalls to be wary of. |
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Machine Learning and Deep Learning: What's the Difference? Many people think that machine learning and deep learning are each just a fancy way to say artificial intelligence, but that is a misconception. Both terms represent subsets of AI technology, but they are different, and their differences dictate the functionality and application of these two software solutions. |
