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.

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.

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 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.

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.

The image recognition function of artificial intelligence (AI) is becoming more and more powerful. Face recognition, license plate recognition, and object recognition are not uncommon. In the fields of smart manufacturing and warehousing logistics, more and more manufacturers are beginning to introduce AI technology into more special applications.

The rising trend of e-commerce and retail online shopping has directly led to the improvement of distribution performance. In addition to the continuous expansion of the operating territory of local distribution companies, offline retail and mass stores have begun to carry out a series of measures to shorten delivery time and improve service quality.

Refers to the use of imaging, medical image processing technology, and other possible physiological and biochemical means, combined with computer analysis and calculation, to assist radiologists in finding lesions and improve the accuracy of diagnosis.

Data science is a complex process of extracting, integrating, and analyzing data, combining knowledge from computer science, mathematics, statistics, and related fields to help companies understand their customers, understand industry competition, and make relative decision-making.

With the development of technology and the gradual shortage of working manpower, more and more AI intelligent robots have been developed and officially applied in the workplace. How should human beings think and respond to such a wave of technology? Will jobs really be completely replaced?

Tiny AI integrates low-power, small-volume NPU, and MCU adapts to various mainstream 3D sensors in the market. And supports three mainstream 3D sensing technologies such as structured light, ToF, and binocular stereo vision, to meet the needs of voice, image, and so on to identify needs.

Machine learning (ML) is a type of artificial intelligence (AI) that allows businesses to make sense of large amounts of data and learn something. Through mathematical optimization, it can help to interpret the correctness of data and improve the decision-making basis of machine learning.

What is Artificial Intelligence (AI)? At present, in which life scenarios has artificial intelligence been used? How will it change the future? Artificial intelligence is the power of the new era. In the future, there will be no modern industries that have nothing to do with artificial intelligence. Artificial intelligence (AI) has illuminated the prospects of a new generation of technology. Since then, people have quickly used huge amounts of data to analyze and carry out machine learning. solution, leading to the best decision. How does this technology work and drive the development of other new technologies? What are the development trends of artificial intelligence?

Wafer-level packaging (WLP) has gained traction over the past decade as the semiconductor industry continues to push for generations of higher-performance chips. Back-end packaging technologies are becoming increasingly important in meeting the demands of low-latency, high-bandwidth, and low-cost semiconductor devices.

The vision of the Internet of Things is to make everyone's life better, safer, and more convenient. To achieve this goal, we must first increase the speed of data processing, generate real-time intelligence, and allow IoT data to make informed decisions in seconds.

In an increasingly connected society, technology has brought about changes and reshaped business models. Through the epidemic, and looking forward to the future, emerging technologies can help companies break through business challenges and create a fairer and more resilient society. The following will summarize and explain the ten technology trends that will shape the industry in 2022.

IoT is the current mainstream trend in technology. In this way, we will discuss the industrial changes and market opportunities of the digital revolution, and will further analyze the technology and application fields of IoT.

The development of new technologies has brought the whole world into the era of the Internet of Things. This new era has more advancements in the area of intelligent design than the information age, and smart sensors have played an indispensable role in its development.

With the rapid development of emerging industries such as the Internet of Things and mobile Internet, smart sensors are becoming more popular. Smart sensors are composed of sensing elements and signal conditioning circuit controllers that have data acquisition, conversion, analysis, and even decision-making functions. Intelligence can improve the accuracy of the sensor, reduce power consumption and volume, and achieve easier networking, thereby expanding the application range of the sensor and making its development more rapid and effective.

The variety and volume of data that is being transmitted via the internet today, as well as the velocity at which it is being transmitted is constantly increasing. These data sets are so voluminous that traditional data processing software just can’t manage them, and so they have come to be called “Big Data”. The massive volume of data necessary to address new and more complex business operations has brought about new challenges to meeting the requirements of these new developments.