Google Expands Reach to Enterprise with Machine Learning APIs
Enterprise cloud usage has been in the forefront of big players for the past few years. Amazon, IBM, Google and Microsoft are expanding their offerings to serve better the enterprise users and their needs. Google announced a set of machine learning based services focused on enterprise users.
Similar to upcoming Amazon EC2’s Elastic GPUs and Microsoft's Azure N-Series, powered by NVidia GPUs, Google will soon offer cloud based GPUs with per minute billing focused on Machine Learning tasks.
Google slashed pricing for its Cloud Vision API to 1/5 , offering face, label, OCR, company logos, explicit content and landmark and image properties recognition through off the shelf algorithms and their API. This puts it in direct comparison with Microsoft’s Computer Vision API and various startups like ClarifAI.
Cloud Natural Language API has graduated to General Availability, supporting English, Spanish and Japanese and offering entities identification and both sentiment and text syntax analysis. Microsoft offers language oriented products in its cognitive services.
The new alpha versioned Cloud Jobs API enables candidates to get more relevant job search results and employers to have better semantics around their jobs offered. Jibe is already using this API to power its platform better connecting existing ATS platforms like Taleo, Peoplesoft, Workday and others with employers.
Finally, Google is now offering premium translation services using Google Neural Machine Translation system based on Recurrent Neural Networks. Google claims better translation results, especially with long form text. Google also reduced pricing for the already available standard class service.
Overall, Google is offering ready to use machine learning models through cloud vision, cloud speech, cloud translation and cloud natural language APIs and the flexibility to use your own data to train custom models through cloud machine learning platform. More information is available in Google’s official blog post and the cloud machine learning services page.