How machine learning is impacting the world

Society and science-fiction writers have long been enamored with the concept of Artificial Intelligence. While general Artificial Intelligence has yet to be achieved, there have been significant innovations in AI. Machine Learning and predictive analytics, which are subsets of AI, have been used in a diverse range of tasks ranging from healthcare to banking.

It might seem like AI is out of reach for many businesses and their applications, but that is not true. Software developers like Koombea build and implement Machine Learning algorithms to improve software performance.

You likely won’t be seeing machines with human-like intelligence soon, but Machine Learning tools that can make better decisions in less time than human experts already exist. Here are some of the ways Machine Learning is already impacting the world:

Machine learning in home sales and protection

Home is one of the most sacred places. Modern home security systems do more than monitor which doors open and set intruder alarms. Machine Learning is combined with facial recognition and surveillance cameras to build a database of frequent visitors to the home. Integrated security systems that combine Machine Learning and facial recognition can send alerts when unauthorized people are detected on the property.

Machine Learning has been improving the home buying process for many people too. Machine Learning algorithms are being used to help buyers determine whether a home is a good value based on historic and projected market data. Real estate websites also use these algorithms to help buyers estimate their potential mortgage payments and project future rental values.

Machine learning in marketing

Machine Learning is being put to good use in the marketing industry. These algorithms analyze the immense amount of data associated with digital marketing campaigns in real-time. As a result, they help marketers make better decisions on the fly to adjust their marketing campaigns to maximize their value.

Whether you want to run a national campaign or a highly targeted B2B marketing campaign, Machine Learning algorithms can be used to quickly optimize campaign settings so more time can be spent designing assets and being creative.

Machine Learning in medicine

Machine Learning makes valuable contributions in the medical field. For example, pharmaceutical companies use these finely tuned algorithms to analyze immense amounts of biological and drug interaction data to formulate better medicines and drug therapies. Machine Learning is also used to help doctors identify cancerous skin and tissue growths before a specialist would normally detect anything was wrong.

Machine learning in banking

Banks have too many customers and daily transactions to manually track them. However, without monitoring, fraud and theft would be able to flourish. This is where Machine Learning plays a significant role in modern banking. Machine Learning algorithms are used to monitor transaction trends, location data, and more to pinpoint and stifle fraudulent behavior and theft before they can charge a customer's account.

Anomaly detection is a valuable service banks can offer their customers. The financial institutions that fail to offer this type of protection will lose customers to their competition. In addition, without Machine Learning and predictive analytics, banks would have a difficult time protecting their customers from theft and fraud.

Machine learning and the environment

Machine Learning is not just for corporations. For example, environmental researchers and activists use Machine Learning algorithms to analyze complex weather data and predict future climate change. The insights generated by these tools can help policymakers, businesses, and citizens make better choices to lessen the human impact on the environment.

Final thoughts

Machine Learning is capable of some incredible things. Already this technology is being put to good use in various fields and applications. Machine Learning is not out of your reach. You might be surprised to learn how affordable and accessible this technology is. You need to find a skilled development partner who has experience writing Machine Learning algorithms.