AI terminal era refers to the development stage when AI technology is popularized and applied to terminal devices, covering all kinds of terminal devices from smart phones, smart wearable devices to smart homes, smart cars and so on. In this era, CY7C263-25WC AI technology is no longer limited to large servers and cloud computing, but goes deep into all aspects of user life, bringing great changes to people's daily life, work and entertainment.
In the era of AI terminal, the rapid improvement of end-to-end computing power has become an important trend. With the improvement of terminal equipment performance and the expansion of demand for use, higher requirements are put forward for the computing power and algorithm reasoning ability of terminal equipment. In order to achieve more intelligent and efficient applications, terminal devices need to have strong computing power and efficient algorithm running ability, so as to achieve more complex AI scenarios, such as voice recognition, image recognition, intelligent recommendation, etc.
At the same time, the competition of AI chips in the AI terminal era has entered a new stage. In order to meet the dual needs of terminal devices for computing efficiency and energy consumption, major manufacturers have launched chip products specifically for AI applications, such as NPU (neural network processing unit), TPU (tensor processing unit), etc. These AI chips not only make breakthroughs in performance, but also optimize energy efficiency ratio, hardware design and other aspects to better support the operation of various AI applications on terminal devices.
In general, the arrival of AI terminal era means that AI technology will be closer to people's life and work, and terminal devices will become more intelligent and convenient, providing users with more comprehensive and personalized services and experiences. The rapid improvement of end side computing power and the fierce competition of AI chips have entered a new stage, which has injected more power and possibility into the development of AI terminal era.
It is shown in the following five trends:
1. Rapid improvement of end side computing power: With the popularization and function enhancement of smart phones, smart speakers, smart cameras and other terminal devices, the demand for end side computing power continues to increase. In order to achieve more complex and efficient AI applications, terminal devices need to have more powerful computing power and more efficient algorithm reasoning ability. Therefore, the rapid increase of end to side calculation force has become an obvious trend.
2. A new stage of AI chip competition: In the AI terminal era, the development and competition of AI chips are becoming increasingly fierce. The traditional CPU and GPU can no longer meet the dual needs of terminal devices for computing efficiency and energy consumption, and various special AI accelerator chips have emerged as the times require. Some companies have built high-performance NPU (neural network processing unit), TPU (tensor processing unit) and other chips, while others have introduced low-power and high-efficiency edge computing chips. Therefore, the design and competition of AI chips have entered a new stage.
3. Algorithm optimization and model compression: In order to adapt to the limitations of end to end computing force, researchers continue to explore methods for algorithm optimization and model compression. Through pruning, quantification, distillation and other technical means, the large-scale deep learning model is compressed to achieve more efficient reasoning on the terminal device. In addition, developing lightweight models for different application scenarios has also become an important research direction.
4. Heterogeneous fusion technology is widely used: End devices usually have limited hardware resources. To make full use of these resources to complete complex AI tasks, it is necessary to apply heterogeneous fusion technology. That is, CPU, GPU, DSP, NPU and other different types of processors are effectively integrated to achieve collaborative work. This technology can flexibly allocate computing resources according to task requirements, and improve the performance and efficiency of terminal devices.
5. Security and privacy issues attract attention: the popularity of AI terminal devices also brings risks and challenges in security and privacy. The problems of personal privacy data being leaked and models being maliciously attacked are increasingly prominent. In order to ensure the security and privacy of user data, developers need to fully consider security when designing terminal equipment, take corresponding data encryption, isolation and secure transmission measures, and establish a secure AI algorithm and model update mechanism.
