MACHINE LEARNING IN EVERYDAY APPLICATIONS

Machine Learning has been around for decades and is already used in various spam filters, speech recognition, and self-driving cars. It is defined as a subset of artificial intelligence (AI) that specifically deals with algorithms that they can learn. It is estimated that today, 80% of all organizations use Machine Learning in some capacity, even if that is not directly evident to the end-user.

Understanding the basics of Machine Learning

Machine Learning is an integral part of the future of mobile and web applications. Software that can learn to aid the user intelligently will revolutionize the industry.

Without a doubt, we are on the verge of a learning breakthrough that will make machines intelligent enough to do tasks for us that they can learn to do better than us, just like humans have done for other humans for centuries.

There is a fascinating concept called the "intelligence explosion" gaining traction in the scientific community. It's based on the theory that superintelligent AI will be created. As it gets smarter, it will create new AIs, which will eventually lead to an event horizon (aka singularity) when the system becomes so intelligent that it's beyond human comprehension.

Why is Machine Learning important for every software app?

Machine learning is an important technology that enhances software performance and makes it faster and more efficient for the end-user.

Simply put, ML is nothing but the process of a computer algorithm gaining insight into data by detecting patterns and extracting knowledge without being explicitly programmed. Thus, machine learning techniques can be applied to various domains like classification, optimization, regression, and clustering.

Cool cases of Machine Learning in everyday applications

Machine learning is being used in a variety of industries to perform tasks from routine to complex. The following are a few examples of cool cases that demonstrate machine learning in everyday applications.

1. With machine learning, you can optimize your advertising campaigns by understanding consumer behavior. A majority of marketers rely on Google Adwords to drive traffic to their websites. However, there's a catch - it's difficult to identify which keywords will bring in the most conversions without spending a fortune on testing different variations. Machine learning can help with this process by "learning" from past advertising campaigns and delivering insights about which words, phrases, and landing pages are the most effective.

2. You can also use it to classify images. In the medical field, machine learning has been used to aid medical diagnosis and treatment for decades. For example, it can take hours for a radiologist to examine the X-rays of patients with brain tumors, but it only takes seconds for an AI algorithm to make the same assessment.

3. The retail industry is also benefitting from machine learning as they can predict customer needs before making their purchase decision. With this knowledge, retailers can provide tailored deals for customers with specific product preferences or offer personalized recommendations based on previous purchases and browsing history.

4. ML has applications in education, for example, in natural language processing or grading essays. One could also use ML in an educational setting to identify bad habits from essay answers such as missing or incorrect punctuation. It could also be used to identify and correct mistakes made by students when writing essays, like switching between first and third-person points of view.

Future of Machine Learning in software applications - What to expect?

As these technologies continue to grow, they will assist humans in ways that they traditionally couldn't. In the future, we will be able to use the help of AI assistants for everything from programming (Github’s Copilot is the first example already) to marketing or business intelligence.

 

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Feature Image “Recycling” by Brian J. Matis on Flickr – Licenced under creative commons