Tractica, a market intelligence firm that focuses on human interaction with technology, forecasts that annual worldwide artificial intelligence revenue will grow from $643.7 million in 2016 to $38.8 billion by 2025.
This extraordinary growth can be largely attributed to advances in machine learning, a type of artificial intelligence that automates analytical model building, allowing computers to adapt to new circumstances and to detect and extrapolate patterns, as explained by Peter Norvig and Stuart J. Russell in Artificial Intelligence: A Modern Approach.
Artificial Intelligence revenue will grow from $643.7 million in 2016 to $38.8 billion by 2025
Already, some of the world’s largest smartphone manufacturers, such as Huawei, are using advanced machine-learning algorithms to make their devices run faster and smoother. Bo Begole, VP and Global Head of Huawei Technologies’ Media Lab, thinks that “these and other as-yet-unpredicted applications of machine intelligence will change how to live and work.”
Machine learning fundamentally relies on a steady supply of vast quantities of data, and no other company has access to more data than Google. Unsurprisingly, Google is at the cutting-edge of machine learning. Last year, the company announced that Google Translate is switching to Google Neural Machine Translation (GNMT), which is a new translation system based on sophisticated machine learning algorithms that provide significant improvements in translation quality. Similar algorithms also improve the accuracy of Google’s turn-by-turn navigation, voice search, or image recognition.
Google Translate is switching to Google Neural Machine Translation (GNMT)
But it’s not just Google who uses machine learning to develop state-of-the-art solutions to a wide variety of problems. With machine learning, mobile app developers don’t need to spend long hours programming knowledge into logic frameworks. Instead, they can create machine learning systems capable of analyzing data for statistical correlations, patterns, probabilities, and other features. This means smarter apps for less money.
Machine learning will generate smarter apps for less money
As we move closer to the connected era powered by billions of IoT (Internet of Things) devices, it will be easier than ever to gather accurate data, which is the key to machine learning. According to CMO — a provider of marketing insights, expertise, and inspiration aimed at helping CMOs, senior marketers, and their teams — the number of Internet-connected things will reach 50 billion by 2020. Annual revenues for IoT vendors are expected to exceed $470 billion.
The number of Internet-connected things will reach 50 billion by 2020
In just a few years, machine learning will play just as important role when it comes to the success of mobile applications as user experience design and polish do today. It makes sense to hire a mobile app developer who is at the cutting edge of technological progress and understands how to use machine learning to develop mobile apps that are guaranteed to stand out and attract users. You guessed it right! Someone like bromin7.