The company says more than 600,000 developers are currently using Brain 3.0 - the newest version, released in July 2018 - for 110 AI services across 20 industries.Īlso in July, Baidu took the wraps off Kunlun, an AI chip designed to handle models for on-device edge computing and datacenter processing. It is our hope that by opening up the platform and democratizing AI capabilities, we will help developers and businesses around the world achieve greater success.”īaidu’s made its AI ambitions clear in the two years since it launched Baidu Brain, its eponymous platform for enterprise AI. Through our Global Business Unit, we are devoted to sharing Baidu’s core technologies, capabilities, and resources with the global community … We are excited to see innovative use cases from the global community. “Baidu has continued to lead and promote the development and applications of AI. “As one of global leaders in AI, Baidu embodies its mission of making a complex world simpler through technology,” Yu said. And a security monitoring firm used it to make a sound-detecting algorithm that can recognize “abnormal” audio patterns that might signal a break-in. An unnamed medical institution tapped it to build a detection model for blood test microscope imagery. Home decorating website Idcool used EZDL to train systems that automatically identify the design and style of a room with 90 percent accuracy, Yu said.
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It’s aimed at small and medium-sized businesses, with the goal of “breaking down the barrier” to allow everyone to access AI “in the most convenient and equitable way,” Yu said. Luckily, for folks who don’t have the wherewithal to wade through the jargon, Baidu this week launched an online tool in beta - EZDL - that makes it easy for virtually anyone to build, design, and deploy artificial intelligence (AI) models without writing a single line of code.īaidu’s EZDL was built with performance, ease of use, and security in mind, said Youping Yu, general manager of Baidu’s AI ecosystem division, and it targets three broad categories of machine learning: image classification, object detection, and sound classification. Without the technical know-how and the right tools, training machine learning algorithms can be an exercise in frustration.
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