“This is what is keeping business leaders awake at night: how to harvest and make sense of their data for competitive advantage. Machine learning is allowing companies to surface the untapped value in their data.”
- Fausto Ibarra, director of global product management for Google Cloud Platform
Google has a great whitepaper out on machine learning, and the paper’s opening statement from Fausto Ibarra sums up ML nicely. Enterprises of all kinds are indeed trying to analyze data in greater volumes and determine its real worth—and they’re turning to machine learning solutions to do it.
While the paper touches on how ML forms the “backbone” of AI strategies, it also stresses why a cloud foundation (such as Google Cloud Platform) is critical to succeeding with ML. Which is good awareness for any organization looking to implement machine learning tools in their data analysis arsenal.
But more valuable for business leaders is the case the paper makes for various machine learning tasks and everything enterprises are using ML for: Security, risk, and fraud analysis. Physical asset management. Predictive analytics. Automated marketing and transaction processing. Customer recommendation engines. Supply and logistics management…
Of the benefits ML provides for business intelligence, according to the results of an MIT study highlighted in the whitepaper, the top payoff is more extensive data analysis and insights. The second highest-rated benefit is being able to analyze data far more quickly and capitalize on market environments before competitors can.
Machine learning solutions will become more widespread—and standard
In ClearObject’s view of ML, the use of machine learning solutions will become more widespread as enterprises continue to discover the technology’s versatility and value.
Already, recommendation engines and automated marketing and robotic process automation are well on the way to becoming ML standards in retail and manufacturing. The whitepaper cites healthcare, financial services and media and gaming as currently being other top ML adopters.
But look for machine learning models to also be engineered for use in industries such as agriculture and even space exploration. The focus now is additionally on ML’s ability to augment human work to make work processes more efficient and employees more productive.
Going into 2020 we’ll have more to say about ML, since we see its continued adoption and expanded uses as a key trend. Meantime check out the whitepaper from Google Cloud research.
Then contact us to learn more about the amazing things ML can do for your enterprise, and how ClearObject can help make them happen.
Machine Learning via Google’s Cloud ML Engine
Google Cloud Platform solutions from ClearObject
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