AI has become the hot spot of the moment, the future development of AI will focus more on the scale production capacity
Throughout the evolution of AI, we find that the current technology companies have started to shift towards AI. As Google CEO Sundar Pichai proposed a shift in strategy, Google shifted from Moblie First to AI first and started investing more in machine learning.
Over the past 15 years, we have leveraged the convenience of Mobile to make commercialization cost effective and efficient. In the next 15 years, the technology revolution driven by technology companies will focus more on the use of technology in the direction of AI, which will lead to further upgrades in business models. In the financial sector, the biggest challenge encountered with AI-centric technology change is how to land AI into business processes.
When we serve our bank clients, we cut through at the system level. By looking at how to implement machine learning at the system level, we found that systems built with machine learning as a core technology are very similar to the role of Android in the Mobile industry. And so we have found our niche, which is to build the Android of AI.
Over a decade ago, in Mobile, it took a big company to implement very simple application systems such as Tetris. This is because different phones have different operating systems and require the development of different apps. In the following years, the emergence of Android has solved this problem very well. The Mobile industry generally adopts Android as the smart phone operating system, and the development of mobile phone APP is no longer the patent of big companies, and the team of fresh graduates can also develop their own APP based on Android.
In the AI space, we find the same process to be true. At the very beginning of the interface with the client, the entire process from data entry, data cleaning, to building the model took several months.
We believe that the use of a process-oriented approach will reduce the time spent on building processes and thus increase productivity. With increased productivity, we can then find more production capacity at scale to solve more problems. An overall virtuous circle. Based on this logic, we have done practice in several joint-stock banks and the results are remarkable.
Thus, AI is not an elite technology in the ivory tower anymore. AI can be a practical help in business processes, expressing some complex phenomena that were previously difficult to describe in a quantitative way. For example, the decision engine, which has received more attention in the industry, is a process-driven automated system that abstracts clear rules and processes from complex financial operations.
And today we are faced with a data-driven automated system, how to re-express complex business, transform traditional processes and improve productivity with scaled AI applications to save time. This is the future trend of AI development and the current business logic of SkyCloud.
Empowering enterprise customers with AI PaaSification and reducing reliance on data scientists
By doing AI empowerment for our clients, we've found more than just helping them save time, we've helped them uncover more scenarios. These scenarios are not defined by us, but rather, after the client is empowered, their own team is able to apply them to create and improve the business processes corresponding to each scenario, such as lending and approval process improvements. After the constant generation of large amounts of data through empowering customers, followed by customer business processes, standardized data, which is extremely important for machine learning, started to emerge. How to use such data to enable rapid model building for customers places demands on the online modeling capabilities of the system platform, and these demands are beginning to be focused on the business side.
We have positioned ourselves in the role of empowerment. We want to empower our customers by taking the work of data scientists and business elites in the industry and making it possible with machine learning technology. This process of implementation can be well described as "demystifying", that is, removing the mystery from the industry and replacing expensive business elites like data scientists with platforms. The West is known as the democratization of AI.
A platform that can replace data scientists is the distributed data science platform launched by SkyCloud: MaximAI