Machine Learning at a Glance: Highlights from Google Cloud Research

Computer scientists have been seriously exploring artificial intelligence — the idea that machines can mimic the cognitive functions of the human brain — for more than 60 years. No longer the stuff of science fiction, AI now has practical applications across industries and functions, and businesses are adopting it for everything from marketing personalisation and image classification to supply- chain optimisation and fraud detection. One technique in particular forms the backbone of many organisations’ AI strategies: machine learning, which uses large volumes of data to train sophisticated algorithms to self-improve. Machine learning enables businesses to make sense of the unprecedented amounts of data now available to them, unlocking insights and efficiencies that can deliver competitive advantage.

For more than a decade, Google has been working to make machine learning solutions more powerful, accessible, and secure, developing open-source tools and cloud-based services that can help businesses solve complex problems. In addition to publishing groundbreaking scientific research of its own, Google regularly commissions independent studies on vital aspects of the evolving machine learning landscape, including enterprise adoption rates, typical use cases, expected and achieved benefits, and success factors. Below, Google has put together some of its most compelling recent findings to guide you on your journey, whether you’re new to machine learning or want to get more value from your existing program.