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Tuesday, January 28, 2020

AI and Web Development

Like to see more specific examples of this, since it bears on the elements of complex goal directed process. Also the specific elements of efficiency.   But would not it expect to add to transparency.

AI Is Changing Web Development 
January 13, 2020 by Gilad David Maayan

According to Accenture, 77 percent of smart devices include at least one AI feature. It is anticipated that by 2025 the global AI market will reach $60 billion. The growth of AI has created greater demand for this technology from consumers and organizations alike. Both are embracing AI technology and driving further innovation with their adoption.

There is a range of tools for incorporating AI into your workflows and products. From plug-and-play components to machine learning-as-a-service (MLaaS), these functionalities enable developers to build AI into their sites and applications through an API or library integration. No longer do you need AI expertise to include it in your products. Unsurprisingly, this increased accessibility is affecting web development.

AI and ML are influencing web development in a variety of ways—from improving efficiency to increasing customer engagement. Below are the most prominent influences.

Coding and Testing

AI and ML can be used to speed development processes and improve the overall quality of applications, such as through AI integration with Integrated Development Environments (IDEs) or AI-based testing. IDEs are tools that combine code writing, editing, building and debugging features within a single platform. IDEs can help improve code quality with automatic vulnerability identification and auto-suggestions for coding best practices. These tools can speed coding with autofill features and real-time code analysis.

With the inclusion of AI and ML models in application testing procedures, these models can be used to analyze user interfaces, optimize test coverage and evaluate application or user behavior patterns, enabling streamlined testing. You can also use AI models to help minimize hard-coding in your applications, helping to reduce vulnerabilities and enable you to work from a smaller code base.

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