Golang for AI Applications

Artificial Intelligence computer programs are taking technological solutions by storm. AI Applications help to improve User Experience, Customer Interaction, healthcare accessibility, Financial planning, purchase experience and more. Through Machine Learning, Logical Reasoning and self-correction these applications are able to mimic human intelligence and human knowledge. Neural Networks create high-level abstractions for a variety of industries and disciplines. AI-powered applications help businesses improve the use of their resources, with visible effects on their bottom line.

Gowitek is riding the AI boom. We have assisted several clients in AI-powered chatbots, product recommendation engines and more for several types of industries. We are leveraging the power of Go Artificial intelligence. Golang is Google’s programming language that was developed by Google engineers Rob Pike, Ken Thompson and Robert Greismer. It was designed with the purpose to handle modern computing requirements.

Why Go Artificial Intelligence?

Superior error handling and easier debugging

Artificial Intelligence as the name suggests must mimic human intelligence. As a result input and output must be simultaneous due to which error handling must be quick. Also, downtime due to debugging cannot take long.Golang has many good machine learning, reinforcement learning and deep learning libraries focussed on all parts of the pipeline. Some of these are for Natural language processing, tensor operations, and even a GPU-accelerated deep learning stack. The resultant applications are refined and functionality rich.

Speed and Accuracy

Golang’s concurrency model and simple syntax have helped to improve the speed of the language. This allows it to handle multiple concurrent requests simultaneously. With Accuracy that tops the list Golang source code is also fast, thread ready, easy, clean, compiled, and simple. It has a vast number of support for libraries for Natural Language Processing, machine learning, data analysis, extraction, processing, and visualization. This makes it perfectly suitable for developing comprehensive real world AI Applications.

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