Language can be frustratingly ambiguous. Or delightfully ambiguous. When you read the title of this blog, did you parse it as Google is a machine that is learning to compete? Or that machine learning will be how "the Google" competes? Both work, and both are true.
First meaning: there is clear evidence Google is making huge progress in cloud services to better compete against its rivals. Executives at the Google Next 17 conference cited a competitive win rate of 60% in the last quarter, with best results when the company gets a fair shot and customers dig deep into the technical differentiation. Sure, Microsoft is entrenched in most enterprises, and AWS has ridiculous momentum, but Google has invested $29 billion over the last three years to innovate in its own way. Many of the services' advantages are subtle but impactful, such as more granular billing for data warehouse consumption with BigQuery, custom configured compute instances, or the potential for API access to data services already within Google's domain. These have real benefits in reducing costs and increasing value of data. Machine learning even helps Google be more efficient, like finding ways to reduce data center cooling costs by 50%. As ESG research shows the financial cost/benefit equation is still the top perceived advantage for cloud-based databases, then Google should win simply on price efficiency for compute and storage resources. See a past comparison of costs here. Assuming buyers take the time to understand this and don't default to their Microsoft sales teams or Amazon's DevOps audience dominancy.