International Cloud Computing Awards Program Announces Shortlist out of hundreds of organizations that applied from the Americas, Australia, Europe, and the middle east.
For the third time in a row, we have been declared a finalist in the international Cloud Computing Awards program, The Cloud Awards.
Since 2011, The Cloud Awards program has sought to champion excellence and innovation in cloud computing. Entries are accepted throughout the globe and across multiple industry sectors.
We are very proud that John Snow Labs has been shortlisted in the 2 categories: Best Cloud Business Intelligence or Analytics Solution and Education Innovation of the Year.
John Snow Labs’ Head of Marketing, Ida Lucente, said: “To be shortlisted for our work in this international program is not only an honor, but clear recognition of the successes and customer satisfaction we strive to achieve with our industry-leading Spark NLP and AI Platform.”
Head of Operations for the Cloud Awards, James Williams, said: “Simply, John Snow Labs has recognized the importance of adopting and pioneering leading cloud technologies in order to deliver outstanding client success, which is why they’re a deserving finalist in the Cloud Awards program.“
“The Cloud Awards team already had a near-impossible task sorting the exceptional from the excellent and the bleeding-edge from the cutting-edge. Weighing both proven successes and exceptional promise across several unique categories is a constant challenge.”
John Snow Labs’ Spark NLP and was highlighted in February 2019 as the most widely used NLP library in the enterprise in the “AI in the Enterprise” global study conducted by O’Reilly. It is the only AI software library to date to be adopted by 16% of enterprises within less than two years of its first release. Since then, John Snow Labs was recognized as the “Most Significant Open Source Project” at the Strata Data Awards, “AI Platform of the Year” by CIO Applications, and “NLP Company to Watch” by Technology Headlines.
Our Spark NLP for Healthcare’s fast pace of innovation is key to its success. Spark NLP had 28 new releases in 2019, on top of 26 releases in 2018. New functionality this year includes the first production-grade named entity recognition models backed by BERT embeddings; tools to evaluate and monitor deep-learning NLP model training; improved spell checking algorithms; major speed gains across all pipelines, in both local and cluster modes; optimized builds for the latest Nvidia and Intel chips; and 30+ new pre-trained NLP models and pipelines in four languages.
Beyond the core functionality of the library, Spark NLP became more accessible to a wider audience in 2019, thanks to the publication of a self-guided tutorial, a how-to video series, revamped documentation, new examples, and a new interactive user interface. The growing team also directly supports the community in an open Slack channel, answering questions daily in order to help newcomers succeed and get constant feedback from the community.