With the rapid development of the automotive industry in smart driving, safety assistance, automotive electronics, and human-machine interface-related technologies, the integration of virtual and real superimposed displays, driver monitoring systems (DMS), interactive functions, Internet of Things (IoT) of the smart cockpit system have become the current trend.

To realize the smart city of the future, it is indispensable to build a safer and more efficient traffic environment, and smart vehicles with networking and various advanced functions are the key.

With the global economic development, the demand of the consumer market has driven the vigorous growth of the textile industry. However, under the business model of production-based sales, excessive production has not only caused environmental pollution but has also caused unnecessary waste of resources. Over the past few years, this has led the United Nations and the European Union, to begin to advocate "sustainability" and "environmental protection" as the focus of global development for the next 10 years.

Artificial intelligence has brought in a new generation of robotics technology: Robotics 2.0. The principal challenge is the transformation from original manual programming methods to true autonomous learning. Faced with this challenge for innovation in AI robotics, how can Taiwan's manufacturing industry best seize the opportunity?

Improving production efficiency is the foundation for the manufacturing industry to gain a firm foothold. The manufacturing industry achieves smart operations by introducing AI applications, automatically identifying abnormalities, or making adjustment suggestions, and assisting companies in achieving more accurate adjustments to machines and upgrading equipment. During the process, the traditional manufacturers are transformed into the smart manufacturers.

With the rise of global environmental protection awareness, the improvement of process efficiency and pollution reduction of plastic products have become important issues for the rubber and plastic industry. In response to the shortage of workers and the reduction of personnel contact, mechanical automation and cloud services have become the new normal in the industry.

Recently, there has been widespread discussion about Artificial Intelligence, Machine Learning, Deep Learning, and Big Data. These technologies find application in various domains such as the financial industry, logistics, business analysis, unmanned vehicles, computer vision, natural language processing, and more, permeating every facet of daily life.

Utilizing machine learning and neural networks, artificial intelligence (AI) plays a crucial role in enabling the autonomous operation of self-driving cars. These vehicles leverage a combination of sensors, cameras, radar, and AI to navigate between destinations without the need for human intervention. For a car to be considered fully autonomous, it should demonstrate the capability to independently navigate predetermined routes without human input, even on roads that have not been specifically modified for autonomous vehicle use.