Putting artificial intelligence and machine learning workloads in the cloud

Artificial intelligence (AI) and machine learning (ML) are some of the most hyped enterprise technologies and have caught the imagination of boards, with the promise of efficiencies and lower costs, and the public, with developments such as self-driving cars and autonomous quadcopter air taxis. Of course, the reality is rather more prosaic, with firms looking to AI to automate areas such as online product recommendations or spotting defects on production lines. Organisations are using AI in vertical industries, such as financial services, retail and energy, where applications include fraud prevention and analysing business performance for loans, demand prediction for seasonal products and crunching through vast amounts of data to optimise energy grids. All this falls short of the idea of AI as an intelligent machine along the lines of 2001: A Space Odyssey's HAL. But it is still a fast-growing market, driven by businesses trying to drive more value from their data, and automate business intelligence and analytics to improve decision-making. Industry analyst firm Gartner, for example, predicts that the global market for AI software will reach US$62bn this year, with the fastest growth coming from knowledge management.