GrowthEase is sharing its latest achievements in AI-powered technology with the world for the first time

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The last decade has witnessed a revolutionary breakthrough in the new generation of AI algorithms represented by neural networks and deep learning in computer vision and natural language and speech. Emerging technologies such as mobile internet and multimedia are widely used in various companies and industries. As a result, audio and video communication has become common in everyday work and life. Video-on-demand and live streaming are growing in popularity around the world. Almost all companies are equipped with chatbots. The innovation of the digital industry has opened up new growth opportunities for companies.

However, new opportunities come with new challenges. New application scenarios place new demands on multimedia communication, digital marketing and cyber security. The integration of AI technology plays an important role in overcoming such challenges. In this context, GrowthEase intends to provide modern companies with an effective reference for conducting business innovation and digital transformation in the age of AI by deeply interpreting its AI solutions and presenting how the company uses AI technology in industrial practice to create a achieve continuous iteration of content risk control, audio and video, and natural language dialogue technologies.

This white paper identifies three major challenges facing businesses in the new era. First, we are witnessing an explosion of online content. A content monitoring system with fast recognition capability and low resource consumption is required. Second, as real-time audio and video applications become more demanding, technology providers must ensure stable performance of real-time audio and video communication technology in a noisy environment while keeping costs low. Third, AI customer services are enjoying rapid development. Vendors need to make better use of natural language conversations to meet customer needs, realize fast cold start, and improve performance to reduce costs.

In response to the above challenges, GrowthEase’s R&D team has developed a set of all-round AI solutions by exploring full-stack AI technologies of its GuardEase, CommsEase and BizEase divisions, while simultaneously R&D resources channeled into three main areas: content risk control, real-time and interactive multimedia, and AI customer service.

Chapter I and Chapter II of the white paper describe current opportunities and technological challenges in the market. GrowthEase provides an in-depth interpretation of its AI R&D team’s solutions and an in-depth analysis of GrowthEase’s practical application of AI technologies to content risk control, audio & video, and natural language dialogue. GuardEase has developed a new digital content risk control system characterized by rapid identification, low resource consumption, agile response and scenario generalization. CommsEase applied AI technology to audio and video technologies to optimize its algorithms and on-device applications. BizEase has innovated its natural language dialog technology based on the new generation AI algorithm and has developed effective solutions for users’ needs, featuring fast cold start, low cost and high availability. The three GrowthEase companies each provide a comprehensive analysis of their practices in the new era in Chapter II.

Chapter III focuses on the five aspects of the AI ​​system – data, model, solution, algorithm and delivery. Based on the architecture adopted by GrowthEase’s AI team, this chapter summarizes the innovative methodology of the current AI system as shown in the figure below.

Chapter IV examines customer stories from GuardEase, CommsEase, and BizEase, and explores how companies can achieve business innovation and breakthroughs by deploying efficient and professional AI solutions. Chapters V and VI discuss the trend of AI technology from the perspective of trusted AI and data-centric AI, and summarize the insights from academia and industry on multimodality, unsupervised and ultra-large AI systems, and engineering automation.

To obtain the white paper, please visit:

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