Google’s cloud Machine Learning family now adds more APIs while making the accesible and affordable.
The new Google Cloud Machine Learning group is led by two world-renowned researchers from Stanford, Fei-Fei Li and Jia Li.
Google Cloud Jobs API
The boffins at Mountain View, CA want to use machine learning to change the nature of finding jobs and hiring people.
The API, currently available as a limited alpha version is intended for job boards, career sites and applicant tracking systems.
Early adopters of the Google Cloud Jobs API include Jibe, Dice and CareerBuilder.
Dice, a career website that serves opportunities for technology and engineering professionals, is a launch tester of the API to help job candidates browse over 80,000 tech job listings. Tech jobs tend to be complex and skill specific. For example, if a tech professional enters “front-end engineer” in a job search without using typical Boolean standards, search results will also return UI engineer, UI developer, web developer, and UX engineer. Complicated, right? By using the API, Dice will be able to better understand a candidate’s background and preferences and match the tech pro to the right roles.
CareerBuilder, using a prototype that they created with Cloud Jobs API in just 48 hours, found improved, more accurate results when compared to its existing search algorithm. In one test, CareerBuilder chose a top 100 term, “part time,” and compared results using the Google Cloud Jobs API versus their existing solution. Jobs API returned a richer set of results by applying an expanded set of synonyms including “PT.” Another test showcased how Jobs API can refine search results. CareerBuilder has one of the largest repositories of healthcare industry jobs. CareerBuilder tested the terms “CNA psych” (Certified Nurses Assistant) against a dataset and reduced the results returned — delivering only CNA roles in a psychiatric setting — to notably increase accuracy for the job seeker. Based on these results, CareerBuilder is making plans to leverage the API for its customers in the near future.
Beginning in 2017, Google Cloud will offer more hardware choices for businesses that want to use Google Cloud Platform (GCP) for their most complex workloads, including machine learning.
In other words, you’ll be able to strap your ML-powered applications to a rocket engine, resulting in faster and more affordable machine learning models. To learn more, visit our GPU page.
Google Cloud Vision API
Image analysis, the core capability of Vision API, is fundamentally changing how businesses operate and interact with their end-users.
Google has been leveraging the latest hardware and tuned algorithms to significantly improve the performance of our Cloud Machine Learning services. Cloud Vision API now takes advantage of Google’s custom TPUs, our custom ASIC built for machine learning, to improve performance and efficiency.
By offering the API at a more affordable price-point, more organizations than ever will be able to take advantage of Cloud Vision API to power new capabilities. Along with the price reductions, we have made significant improvements to our image recognition capabilities over the last six months. For example: the logo detection feature can identify millions of logos and label detection can identify an expanded number of entities, such as landmarks and objects in images.
Google has thousands of customers using the product to do amazing things. For example, the e-discovery firm Platinum IDS uses Cloud Vision API to power content relevancy for millions of paper and digital files and deliver its new e-Discovery app, and Disney has leveraged Vision API as the basis of innovative marketing campaigns.
Google Cloud Translation API
With the launch of Google’s Neural Machine Translation system (GNMT) that uses state-of-the-art training techniques and runs on TPUs to achieve some of the largest improvements for machine translation in the past decade, there have been some changes to the Google Translate service, namely a split to Standard and Premium services.
This new edition provides:
Highest-quality model that reduces translation errors by more than 55%-85% on several major language pairs
Support for up to eight languages (English to Chinese, French, German, Japanese, Korean, Portuguese, Spanish, Turkish) and 16 language pairs.
The Premium edition is tailored for users who need precise, long-form translation services. Examples include livestream translations, high volume of emails and detailed articles and documents. The Standard edition continues to offer translation in over 100 languages and price-performance that’s ideal for short, real-time conversational text.
Google Cloud is offering these capabilities to all partners, developers and businesses with a Premium edition of Cloud Translation API (formerly Google Translate API).
Google Cloud Natural Language API
The text analysis machine learning service, is now generally available for all businesses.
Evernote, a Google partner provide a productivity service used by over 200 million people to store billions of notes and attachments has provided massive amounts of valuable feedback.
Google continues to invest in research and models that will bring new scenarios to life. We’re committed to quickly delivering new machine learning solutions for businesses in 2017 and beyond.