Artificial Intelligence Helps The World Of E-Commerce

Artificial intelligence is starting to have an impact in the world of e-commerce. The IRP Commerce platform based in the Northern Ireland Science Park has developed an artificial intelligence (AI) engine called DeepAgent. PayPal has implementing deep learning artificial intelligence in order to deal with cybersecurity.

For the IRP Commerce platform, DeepAgent analyses data and find the actions that could lead to profitability. The system predicts and guides the e-commerce company's moves needed to maximize its online sales.

From e-commerce, probabilities data are collected in the IRP Cloud and the DeepAgent is using statistical and Machine Learning algorithms to analyze information and propose the steps to take. This allows the company's management to remove speculation associated with e-commerce sales.

According to Daniel Loughlin, IRP Commerce founder, cited by Belfast Telegraph, it can be challenging to find a practical use for artificial intelligence in business. However, IRP Commerce decided to us AI to increase its online revenues.

Loughlin added that the e-commerce industry is inefficient and deeply complex, but with the development of DeepAgent technology all this can change. E-commerce companies could benefit of a huge advantage over competition by using the DeepAgent AI. The artificial intelligence system informs businesses the best course of action to grow and increase their market share.

Meanwhile, PayPal is growing the reliance of its security system on deep learning artificial intelligence technology. Due to the implementation of artificial intelligence algorithms, the company can spot now possible fraud without errors. The AI algorithms review patterns of likely fraud in databases and mine data from the customer's purchasing history.

Deep learning artificial intelligence technology helps PayPal to keep ahead of cyber attacks through real-time, intensive analysis of online money transactions. According to the company's senior director of global risk sciences, Hui Wang, cited by Technology Review, the system was first put to use in the year 2013.

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