Google Feels Machine Learning Pressure, Cuts Prices

Machine Learning Concept

The heat is on! Google has drastically slashed the prices of its cloud based machine learning tool, in response to some intense pressure from AWS on this highly dynamic front.

Amazon Web Services has ended the year with machine learning front square and center, unveiling a number of new technologies and services in the process, as it tries to catch up with cloud rivals in the machine learning and artificial intelligence fields.

This price cut is basically a signal from Google that it plans to protect its early lead in machine learning services for the cloud. Google already offers its ML Engine service designed to help developers and enterprises leverage machine learning via the use of prebuilt systems and automatic algorithm tuning.

But Amazon, in launching its SageMaker service has put new pressure on Google.

Apparently, Google put up a blog post laying out the new prices, but later removed that for one reason or another. And according to this report customers are now essentially charged 43% less than before for basic tier compute services for training machine learning algorithms.

As detailed:

“The company has introduced massive price reductions for its Cloud Machine Learning Engine managed services. For example, customers using basic-tier compute for training a machine learning system will pay 43 percent less than they did earlier this year. Google also offered customers more clarity on what they’ll be paying for those jobs.

Information of the price reductions was first included in a blog post that appeared briefly yesterday on Google’s website, then vanished. A representative for the company declined to comment further on the news when reached for comment.”

Since its release in November, SageMaker has received a lot of industry buzz, with Amazon CEO claiming that no other solution other there is as easy as this.

Aside from AWS, Google is also facing competition in the ML space from Microsoft and Facebook, both of which have partnered on an open source machine learning project.

It is only a matter of time before the industry pickup follows, considering just how much emphasis being placed on this field. Improvements and price cuts like these across the board will simply pave the way for user acceptance of machine learning in the cloud.