Google beefs up cloud machine learning offerings with new groups and APIs
Google has been pushing the message of machine learning as it aims to tempt more customers onto its cloud – and this push continues with the launch of a new group focused on delivering cloud-based machine learning solutions to businesses, as well as a new API.
“Building a centralised team within Google Cloud will accelerate our ability to deliver machine learning products and services to enterprise customers in every industry,” wrote Rob Craft, group lead for Google’s cloud machine learning arm in a blog post. “Today also marks an exciting next step in Google Cloud’s product commitment to make machine learning more accessible for all businesses.”
The new cloud machine learning group will be led by Fei-Fei Li, who had been director of the artificial intelligence lab at Stanford University, and Jia Li, formerly head of research at Snapchat.
One of the new launches involves GPUs (graphics processing units) for Google Cloud Platform, offering more hardware flexibility. In a separate blog post, product manager John Barrus noted the importance of providing GPUs to give more computing power when compared against CPUs. “You’ll be able to strap your ML-powered applications to a rocket engine, resulting in faster and more affordable machine learning models”, as Google puts it.
Regarding APIs, the Cloud Natural Language API is now generally available, which also includes expanded entity recognition, granular sentiment analysis with expanded language support, as well as improved syntax analysis. Similarly, the Google Cloud Jobs API also utilises machine learning to provide businesses with ‘Google strength’ candidates for recommended jobs.
Plenty of research has taken place on how cloud is enabling greater power in machine learning; not least due to the economic impact of digital storage and cloud computing making machine learning more affordable for all businesses. “Enterprises looking to become competitive leaders are going after the insights in these unstructured data sources and turning them into a competitive advantage with machine learning,” wrote Louis Columbus in this publication back in June.
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