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Defining Role of AI in Dynamic Predictive Analytics

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Defining Role of AI in Dynamic Predictive Analytics

Let's check out a defining role of Artificial intelligence in dynamic predictive analytics. Also, explore who is achieving results.

· AI Zone ·
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Bias comes in a variety of forms, all of them potentially damaging to the efficacy of your ML algorithm. Read how Alegion's Chief Data Scientist discusses the source of most headlines about AI failures here.

Artificial Intelligence (AI) is the latest buzzword in the world of technology with major tech corporations focusing on developing AI tools or investing in start-ups doing the same. Artificial Intelligence is the theory of machines being able to perform cognitive activities, which normally require human intelligence such as speech or text recognition, translation, visual perception, and other learning and problem-solving functions. An artificially intelligent device is the one that can perceive its environment and take appropriate action.

Predictive analytics is a dynamic process of mining copious amounts of data gathered by machines using statistical models. It can be used to predict future trends in different fields. In recent years, it has gained a lot of popularity as machines are getting smarter and sharing massive amounts of data which cannot be analyzed through mere human intervention.

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Organizations like Apple, Microsoft, Amazon, and Google are making mammoth investments in AI tools and achieving results. They are using predictive analytics and combining those with AI tools to provide better customer service, remove operational bottlenecks or get understand their customers more. For example, Amazon’s Alexa is an intelligent voice assistant that uses neural networks for natural languages and analyses human voices to give appropriate responses.

In 2014, Google bought an Artificial Intelligence start-up Deepmind for a staggering $400 million. Deepmind has been used by Google for allowing customers to find quickest routes between stations, although it has higher ambitions. By use of predictive analytics, its artificial intelligence tool has been trying to solve the problem of health deterioration of patients. They are feeding the AI tool with the medical records of patients to try and predict changes in patients’ health which can lead to death. In this way, they are developing AI tools that can erase the scope of human error due to a lack of constant care, which is Ailth-care for hospital patients. Places like Intensive Care Units in hospitals can benefit greatly from such tools. While data collection and the use of predictive analytics will help in identifying the early onset of health issues, artificial intelligence tools will help in teaching machines to take over caring duties. Image result for healthcare analytics

Another example of the relevance of artificial intelligence in dynamic predictive analytics lies in future prediction. Predictive analytics is making it possible for businesses to predict the forecasts and improve performance. Artificial Intelligence uses analytical data to be able to identify broader patterns that humans can not see due to bias. For example, based on a person’s age, gender, location, past purchases and current items in the cart, a supermarket would suggest what next to add to the cart to that person.

This will help businesses in improving their customers’ purchase experiences and thereby improve the average revenue from every customer. It will help them in deploying pricing strategies based on specific consumer patterns and customer expectations. It would also help in managing inventory or identifying the potential for new products based on statistical information rather than intuition.

In total, Artificial Intelligence makes predictive analytics an actionable tool that helps in shaping futuristic strategies and create efficient and scalable processes. AI and predictive analytics together pave way for a sophisticated handling of copious amounts of information to deliver optimum results for both humans and machines that serve humans. The applications have a wide range of use cases in healthcare, marketing, retail and governance among other domains. We can safely say that predictive analytics are leading the resurgence of AI in a manner that lets it become an essential part of various industries.

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Topics:
analytics ,machine learning ,ai tools ,predictive analytics ,technology ,data analysis ,ai

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