Yosemei founders give invited presentations at the China Global Software and Information Services Summit
On June 15, 2017, the fifteenth China International Global Software and Information Services Summit opened in Dalian, Liaoning, with the theme of "new IT, new ecology and new momentum ". The key forums of the conference – The Artificial Intelligence Industry Trend Forum & China IT Innovation and Development Forum - were held in the Expo square. Many industry leaders from all over the world participated in the forums, including executives, technical experts, scientific research institutions, industry organizations and so on.
Dr. Saptho Nair, founder and chief scientist of Suzhou Yosemei Intelligent Co., Ltd., and founder and CEO Qu Zhaohui were both invited to speak at this conference.
Ms. Qu Zhaohui, CEO, presented a demonstration of Yosemei’s product MLP (Machine Learning Processor) at the China IT Innovation and Development Forum, which enabled the audience to a close-up view of MLP, the machine learning based big data analysis platform. The presentation illustrated the application of machine learning to operational intelligence was well received by the audience. Thereafter, Ms. Qu provided interviews to the news media.
Dr. Saptho Nair presented a speech on the application of machine learning in IT operating data in the artificial intelligence industry trend forum, demonstrating how machine learning makes IT operation data analysis smarter, Intelligent and more valuable. This was a highlight of the AI forum.
These days, people and machines are producing more data than ever. The data generated in the current ten minutes amounts to more than the data produced in the whole year 2001. Operation and maintenance data show an exponential growth trend, which brings great challenges to IT operation and maintenance personnel. Data are generated in all aspects of the enterprise's Information Architecture: applications, network infrastructure, servers, transactions, sensors, and various social applications. The data volume, velocity and variety are very large. The data are constantly changing as well.
The operation and maintenance data are not only large and complex, but the location of the source are also different. It is very hard to analyze, but we often need to get the answer in a few seconds. We need ways or means to make sense of this massive data, find operational problems and their root causes. The massive amounts of data contain valuable information and insights for enterprises, institutions, organizations and individuals. We need a real-time big data intelligent analysis system that can process massive data in near real time, quickly find root causes, display efficiently and simply to the operation and maintenance personnel, and can also predict rare problems that have not appeared.
In the face of the above challenges, Yosemei independently developed a machine learning based big data analysis platform MLP with its rich technology experience and years of machine learning research and development experience. MLP (Machine Learning Processor) is a big data processing systems for machine learning and near real-time analysis of structured，semi-structured and unstructured data. It provides powerful data collection, intelligent analysis, search analysis, drag and drop modeling, machine learning, visualization reports, and other functions, through the collection of data generated in operational environment. Via machine learning, multi-dimensional correlation analysis, anomaly detection, cluster analysis, dynamic thresholds, intelligent prediction, etc., MLP can quickly find abnormal behavior, the root causes of the problem, greatly improve operational efficiency, and the stability and security of the system. In other words, it mines big and fast data, eliminates noise, gets the essence, provides customers with visible, easy to understand, actionable, valuable information and intelligence.
For the needs of all aspects of ITOA big data, yosemei provides a complete set of ITOA solutions. MLP has powerful extensibility and architectural flexibility. It can easily handle exponential growth of big data. It can adapt to the ever-changing and complex IT environments of large enterprises, financial and other institutions. For different types of high-speed data distributed among different devices of the infrastructure, MLP also provides local acquisition and remote acquisition, and stores the collected data centrally to achieve efficient data processing. MLP learns and models various network devices, operating systems, databases, middleware, etc. Detection of possible risks and problems, without the need for experts to formulate rules, new unknown problems and abnormal behaviors can be discovered. Ordinary operation and maintenance personnel can quickly find the root cause of the problem based on drill-down on alarms. MLP can mine intelligence from massive machine data, provide network insights, provide basis and strategy for forecasting network, computing, and storage capacity needs to ensure the stability, reliability and security of the IT production environment. MLP analyzes the logs and events of security devices in the operation and maintenance systems, enabling users to cross-correlate between systems to identify threats.
At this year's software summit, various forums were informative about how the big data and AI industry are important drivers for the transformation of various industries. ITOA big data, as the most basic and important aspect in all industries, extracts valuable intelligence information, plays an important role in maintaining the operation of enterprises and institutions, and helps enterprises and institutions innovate and transform.