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Now -a day's artificial intelligence Applications are bringing massive changes in technology solutions. Artificial intelligence applications are making progress towards customer interaction, accessibility, purchase experience, user experience financial planning and many more. Features like self-correction, Machine learning, and Logical Reasoning are able to mimic human intelligence. Artificial intelligence applications also help businesses in various ways such as improve the use of their resources, with a visible effect on their bottom line. <br>
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Introduction • AI Applications help to improve User Experience, Customer Interaction, healthcare accessibility, Financial planning, purchase experience and more. • They are helping businesses improve efficiency in utilization of resources, thereby improving the bottom line profit. • So the question arises “Which programming language is best for developing AI Applications?”
Golang • Go is a new yet modern language. Though languages such as Python and Java are widely popular for developing AI applications, Golang is swiftly capturing the market due to some unique features. • AI Applications demand swift response to requests in order to mimic human intelligence. Golang not only brings speed into request execution but also introduces a host of other benefits:
Why Go Artificial Intelligence? Superior error handling and easier debugging • In order to mimic human intelligence input and output must be simultaneous and error handling must be quick. • Golang has many good machine learning, reinforcement learning and deep learning libraries focused on all parts of the pipeline. Some of these are for Natural language processing, tensor operations, and even a GPU-accelerated deep learning stack.
Why Go Artificial Intelligence? Speed and Accuracy • Golang’s concurrency model and simple syntax help to improve the speed of the language. • This allows it to handle multiple concurrent requests simultaneously. • Golang code is also fast, thread ready, easy, clean, compiled, and simple. Number of support for libraries for Natural Language Processing, machine learning, data analysis, extraction, processing, and visualization help develop feature rich AI Applications.