Samsung Electronics Wins at Two Top Global AI Machine Reading Comprehension Challenges
Samsung Research, the advanced R&D hub of Samsung Electronics’ business, has ranked first in two of the world’s top global artificial intelligence (AI) machine reading comprehension competitions.
Samsung Research recently placed first in the MS MARCO (Microsoft MAchine Reading Comprehension) competition, as well as showing the best performance in the University of Washington’s ongoing competition for TriviaQA*, a challenge dataset for AI reading comprehension.
With intense competition in developing AI technologies globally, machine reading comprehension competitions such as MS MARCO are booming around the world. MS MARCO and TriviaQA are among the actively researched and used machine reading comprehension competitions along with SQuAD (Stanford Question Answering Dataset) of Stanford University and NarrativeQA developed by the University of Oxford and Google’s DeepMind. Distinguished universities around the world and global AI firms, including Samsung, are competing in these challenges.
Machine reading comprehension is where an AI algorithm is tasked with analyzing data and finding an optimum answer to a query on its own accord. For MS MARCO and TriviaQA, AI algorithms are tested on their capabilities of processing natural language from real anonymized user queries and also providing written text in various types of documents such as news articles and blog posts.
For example in MS MARCO, ten web documents are presented for a certain query to let an AI algorithm create an optimum answer. Queries are randomly selected from a million queries from Bing (MS search engine) users. Answers are evaluated statistically by estimating how close they are to human answers.
Samsung Research took part in the competitions with ConZNet, an AI algorithm developed by the company’s AI Center. ConZNet features skillful capabilities through adopting the Reinforcement Learning** technique, which advances machine intelligence by giving reasonable feedback for outcomes, similar to a carrot-and-stick strategy to reinforce learning outcomes.
With the recent acceleration in global competition to develop AI technologies, contests are widespread in the areas of computer vision (technologies to analyze characters and images) and visual Q&A to solve problems using recognized images of characters as well as machine reading comprehension.
The Beijing branch of Samsung Research won the International Conference on Document Analysis and Recognition (ICDAR) hosted by the International Association of Pattern Recognition (IAPR) in March, putting them in a top-tier group for global computer vision tests. The ICDAR is the most influential competition in Optical Character Recognition (OCR) technologies.
“We are developing an AI algorithm to provide answers to user queries in a simpler and more convenient manner, for real life purposes,” said Jihie Kim, Head of Language Understanding Lab at Samsung Research. “Active discussion is underway in Samsung to adopt the ConZNet AI algorithm for products, services, customer response and technological development.”