GANs came as a breakthrough to the emerging technologies in advertisement
Advertisements are a front runner in marketing. Consumers get a hint of the product range of a company and its features mostly through advertisement strategy. It plays a vital role in improving the sales of products. However, advertisements are expensive.
Starting from choosing models to picking a shooting location and affording to the cameramen, and machinery used for the process, advertisements come with a lofty sum of money spent. It is not normal for an MSME to spend a lot on such video ads. Remarkably, video advertisements attract consumer, spiking the revenue of the company.
Like every other place where AI and its applications give a heroic entry for rescue, here too AI features come for aid. An amazing invention of Generative Adversarial Networks (GANs) in 2014 brought enthusiasm to the advertisement sector. It started a new era for AI image synthesis. GANs are an approach to generative modelling using deep learning methods, such as convolution neural networks. Generative modelling is an unsupervised learning task in machine learning that involves automatically discovering and learning the regularities or patterns in input data in such a way that the model can be used to generate or output new examples that plausibly could have been drawn from the original datasets.
The latest GAN technologies have the capability to generate high-resolution, realistic and colourful images that are almost impossible to distinguish from real photographs. AI technologies are not fenced until visual content. It has more features like Natural Language Processing (NLP) and Natural Language Generation (NLG). NLP is the automatic manipulation of a natural language like speech and text by software. NLG is a subfield of AI that automatically transforms data into plain-English content. The technology amazes users by its ability to tell a story exactly like that of a human analyst by writing sentences and paragraphs. These two technologies take part in copywriting works. The marketing message generated with AI-driven solutions is not only plausible but also data-driven. The text can reflect the brand’s voice and be written for a community of audience.
These AI applications help cut the cost and time agencies spend on advertisements. The AI technologies can make a featured advertisement look exactly like a video clip shot with all the mechanism. Here are some AI companies that are nailing the process.
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