The AI Economy in the 21st Century
31 August, 2021 by
The AI Economy in the 21st Century
Laps Solutions Limited

When we discuss with customers how to use artificial intelligence (AI) for their business, we will elaborate cases and examples to illustrate various application scenarios. Many customers would like to know the difference between the popularity of e-commerce and social media since 2000 and the trend of artificial intelligence.

E-commerce and social media technologies have enabled many large giants to provide platforms to expand their businesses on the Internet. I would say that this is the internet economy. For example,,,,, Netflix etc. are online marketplaces that facilitate commercial transactions between people and companies or between buyers and sellers. Digital payment service providers such as Paypal, Alipay, Apple Pay, and Google Pay capture most of the world's online payment transactions. These platform service providers are global and their scale is so large that they even have serious adverse effects on traditional participants in multiple industry sectors. When these giants grow up, their existence looks like a threat to companies of all sizes. Internet giants have undoubtedly been carrying out a "Winners Take All" business strategy for the past two decades, which is also one of the characteristics of the internet economy. Taking advantage of the "network effect" is the core foundation for the success of enterprises. At the same time, most of these giants also rely heavily on software technology.

What about the AI economy? We can take "smart cars" as an example. This is not just a matter of a family buying a car online. In the “smart car” industry, artificial intelligence technology is not only about software programming, but also hardware technology (such as robots, automated machine production, etc.), computing algorithms and data science. The use of data is critical to the success in the AI economy.

Traditional cars operate relying on power (energy) supply, car bodies (engines, wheels, safety measures, etc.) and human drivers. The car body is an integration of thousands of mechanical, electrical and electronic components. Power comes from gasoline or batteries. However, whether it works well depends on the person, i.e. the driver.

For "smart cars", it will be equipped with an electric engine, but with fewer mechanical and electrical components than traditional cars. In the long run, automakers may use similar hardware, and future "smart cars" hardware will be roughly the same (for example, car camera, GPS, LiDAR, ultrasonic, radar, electronic chip etc. Just like today, our personal computers or mobile phones share quite similar hardware specifications.)

In the world of artificial intelligence, the difference between "smart cars" and traditional cars is that "smart cars" can "intelligently" respond to their operating environment (and even exchange information with the environment). By using various types of car sensors to capture a large amount of environmental and operating data, and processing the captured data through appropriate machine learning algorithms, cars can safely drive themselves without human intervention (the ultimate goal is SAE L5 full driving automation).

Here, the ability to properly use data and machine learning algorithms play an important role in "good" driving. Artificial intelligence not only uses historical data for learning, but the real-time information captured from the driving environment will directly affect the performance of the car.

You may identify the difference between the AI economy and the Internet economy. In the artificial intelligence world, machine learning algorithms (like computer programs) can be shared and copied between different suppliers (in our case they are car manufacturers), but the data is unique, especially when it comes to real-time and local data in the working environment. The "Winners Take All" business strategy is no longer a guarantee of success. An EU car manufacturer can make the best local self-driving cars in Europe, but it may not work properly in China because the car manufacturer lacks quality data of the driving environment in China.

When two car manufacturers use roughly the same sets of car sensors to obtain data, how they use the data (operation and processing) will have a significant impact on product design and production.

(Another example is in the medical and health industries. For example, when an AI medical system trained and working in one country is transferred to another country, it may not work normally because the patient data (health record data) of these two countries are different.)

The production plant of a car manufacturer is another scenario where AI can be used. Thanks to the use of robots and automation, the productivity and product quality of a factory manufacturing will be greatly improved. Imagine what the business economy will look like when labor is no longer the bottleneck in the production process. How manufacturers make good use of the data captured by AI in the manufacturing process can enable factories to operate in different ways.

In the internet economy, e-commerce and social media technologies place great emphasis on sales and marketing. In the AI economy, AI technologies will have a significant impact on many business processes from the back-end to the front-end.

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