Machine learning (ML) is one of the most powerful tools in today’s professional world. The technology consists of algorithms that allow devices to learn patterns and trends from large datasets. Then, a company can leverage an ML mobile app that uses this data to develop valuable business insights.
Businesses of all sizes know that the key to successfully selling a product or service is how you market it, who you market it to and when you do so. Machine learning and predictive analytics (PA) play an important role in marketing campaigns by using clusters of data to determine factors regarding consumer behavior.
A surprising number of apps are starting to use machine learning and artificial intelligence (AI) technology to do everything from predicting purchase behaviors to adjusting a home’s thermostat to the resident’s ideal temperature for a particular time of day. But what else can this technology do? Well, machine learning and AI can combine to transform many of the experiences you encounter throughout the course of everyday life. Read More
Artificial intelligence (AI) and machine learning have emerged as two technologies that could dramatically affect blockchain and all the people, organizations and companies that use this technology. But blockchain is essentially a distributed ledger which is known for its reliability and simplicity, so how does machine learning and AI improve this already-innovative technology? Well, to appreciate the potential role of artificial intelligence and machine learning, it’s essential that you understand exactly how these two technologies are used.
Machine learning has the potential to transform the healthcare industry, which routinely deals with large volumes of data, probabilities and real-time data streams from wearable sensors, along with other monitors and equipment. This technology can help us process and make sense of the data, which may then be used to improve patient care in significant ways. From improved treatment efficacy to greater insight into a patient’s condition and even reduced healthcare costs, machine learning will almost certainly prove to be a game changer for the health and wellness industry.
Flurry’s annual mobile technology round-up report revealed a surprising fact: the amount of time spent using apps grew by just 6% in 2017. This figure reflects a significantly smaller margin of growth than the 11% increase observed in 2016.
Machine learning powers many of today’s most innovative technologies, from the predictive analytics engines that generate shopping recommendations on Amazon to the artificial intelligence technology used in countless security and antivirus applications worldwide. But like any form of technology, it’s not entirely perfect. So, let’s examine the pros and cons of machine learning and how they may impact you and your company’s goals.
It’s common knowledge that security breaches can be costly and downright disastrous for a brand’s public image and trustworthiness. Think of the Starbucks app debacle of May 2017, when hackers accessed the app and loaded money using the credit cards on file for hundreds of different customers. That single incident had coffee drinkers uninstalling the app in droves, while the Starbucks customers who kept the app on their devices had their trust seriously rattled.
Machine learning algorithms have gone a long way toward transforming our digital experience, whether we’re online, using a mobile app, interacting with a piece of desktop software or leveraging the tools within an enterprise app. And while few people really appreciate the machine learning algorithm—or even realize it exists—it’s a remarkable piece of technology that is unique in terms of its adaptation capabilities and overall efficiency. As more and more mobile apps are built each month, an increasing number of developers are leveraging the many advantages of machine learning algorithms. But what are these benefits and how do they affect your mobile app, its budget and its overall capabilities?
The power of machine learning to benefit mobile apps is remarkable. Although machine learning technology was initially conceived by tech pioneer Arthur Samuel while working at IBM in 1959, it has only recently entered the mainstream. An increasing number of app developers are opting to use machine learning in conjunction with other cutting-edge technologies such as artificial intelligence and predictive analytics.