Author: Zen and the Art of Computer Programming
1 Introduction
In March, with the development of new technologies such as mobile Internet, big data, Internet of Things, and cloud computing, and the continuous innovation of corresponding application scenarios, new concepts such as "artificial intelligence +", "data-driven development", and "DevOps" emerged in many corporate horizons. Based on these concepts, I will combine my personal experience to explain how to use these new technologies, methods and tools to promote the improvement of corporate R&D efficiency from multiple dimensions and bring a better user experience. At the same time, this article will also share some best practices to help everyone grasp the trends during this period.
2020 has just ended, and "Black Friday" is coming soon. As one of the industry leaders, Tencent CEO Wang Jian said: "The epidemic is making everyone smarter, richer, and more open, and we are just following this trend." The epidemic has a profound impact on society, economy, and society. The impact of the international situation will never stop. Only those who truly know how to use scientific and technological means to solve problems, turn danger into safety, and create value can survive. In order to win in this difficult era, companies must establish the correct business direction, improve data management, optimize production processes, ensure product quality, and fully implement lean systems to ensure the company's long-term profit growth.
At the beginning of 2020, with the popularity of new technologies such as artificial intelligence, machine learning, and deep learning, as well as the emergence of related cloud services, platform services and other products, companies are rapidly transforming into data-driven development models. According to incomplete statistics, in the first three quarters of 2020, global enterprises invested more than 5 trillion yuan in R&D expenses, of which more than 90% was used in the research and development of human resources systems, business intelligence systems, industrial Internet, smart cities, medical health and other industries. Technologies such as artificial intelligence, machine learning, deep learning, computer vision, and natural language processing realize complex computer models and continue to develop rapidly, driving the development of the industry. In addition, the company's internal data and data quality continue to improve, providing companies with reliable basic information. Therefore, whether it is adjusting business forms, business models, and operating strategies, or optimizing R&D processes, product quality, and working methods, companies must pay close attention to R&D efficiency, data science, artificial intelligence,