Google Hopes to Attract Cloud Customers with Machine Learning

Although Amazon and Microsoft are already dabbling in machine learning in their cloud offerings, Google hopes its technology can set it apart.

Google is hoping that machine learning technology will help it compete in the cloud services market and win business from large enterprises. Machine learning — the idea that an artificial intelligence can learn from and make predictions based upon data it accesses — is “what’s next” in technology, Eric Schmidt, chairman of Google parent Alphabet, said last week when Google announced its plans, according to TechCrunch.

Google says its Cloud Machine Learning product will offer machine learning services, including both “pre-trained models and a platform to generate your own tailored models.” The company says its technology “has better training performance and increased accuracy compared to other large scale deep learning systems” and that its services “are fast, scalable and easy to use.”

Several well-known Google applications already use machine learning, the search giant notes. “Cloud Machine Learning will take machine learning mainstream, giving data scientists and developers a way to build a new class of intelligent applications. It provides access to the same technologies that power Google NowGoogle Photos and voice recognition in Google Search as easy to use REST APIs,” Fausto Ibarra, Google's director of product management, says in a blog post. “It enables you to build powerful Machine Learning models on your data using the open-source TensorFlow machine learning library.” TensorFlow is Google’s open-source artificial intelligence (AI) technology, which is now being brought to the cloud.

Will all of this redound to Google’s benefit? It’s hard to say. The Cloud Machine Learning product is only available to developers in preview form right now. 

As Re/code notes, Google is hoping that companies will choose it for their cloud needs and be lured by its artificial intelligence prowess. However, Re/code also points out that moving data to the cloud is an expensive proposition for large firms, and that they likely care about security and customer service more than machine learning.

Mar 28 2016

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