|By Lliane Hunter | 2 years ago|
Amazon, Google, and Microsoft all want to dominate the business of providing artificial-intelligence services through cloud computing, and for the past several years these titans have been working to make machine learning more accessible. In an article published in MIT Technology Review, Peter Burrows discusses how the AI cloud could produce the richest companies ever. For the leading AI cloud providers, making machine learning more accessible could provide unprecedented financial rewards, says Burrows.
Amazon, Google, and Microsoft have been folding features such as face recognition in online photos, and language translation for speech into their respective cloud services—AWS, Google Cloud, and Azure for the past three years. “Ultimately, the cloud is how most companies are going to make use of AI—and how technology suppliers are going to make money off of it,” says Nick McQuire, an analyst with CCS Insight. The nature of machine learning will likely culminate in customers becoming locked in to an initial vendor because the more data the system gets, the better the decisions it will make. Thus, AI could double the size of the $260 billion cloud market in coming years, says Rajen Sheth, senior director of product management in Google’s Cloud AI unit.
Whoever gets out to the early lead will be very difficult to unseat, that’s why thousands of AI-related startups have ambitions to become tomorrow’s AI leaders. Puneet Shivam, president of Avendus Capital US agrees, asserting that the leaders in the AI cloud will become the most powerful companies in history. Google, Amazon, and Microsoft continue to work on ways to make machine learning accessible even to total AI novices. The goal is to make building machine-learning apps not much more complicated than creating a website.
“There are 20 million organizations in the world that could benefit from machine learning, but they can’t hire people with the necessary background,” says Jeff Dean, head of Google Brain. “To get even 10 million of them using machine learning, we have to make this stuff much easier to use.”