With the advancement of technology, new-generation technologies such as big models, edge computing, artificial intelligence and big data are emerging. In such a rapid technological development environment, multi-technology integration and innovation has become a trend. For example, the combination of edge computing and big models will surely bring new opportunities for the industry.
What are Big Models?
With the rise of big models such as ChatGPT, the field of artificial intelligence has set off a change that may revolutionize the way people work and live. Big models are machine learning models with massive parameters and complex structures. It is able to handle a variety of massive data and tasks with stronger learning and generalization capabilities. It includes natural language processing, image recognition, speech recognition and so on. Big models have achieved great results in many fields, but their requirements in terms of deployment and computational resources are extremely high, which makes the application of big models in edge scenarios limited.
What is edge computing?
Edge computing is an emerging approach to computing. It pushes data processing closer to the edge of the data source instead of concentrating on remote data centers or cloud servers. This type of computing can effectively reduce the pressure on the central server and reduce the latency of data. This is very beneficial for realizing real-time response and intelligent control of end devices.
What will the combination of the two technologies bring?
With the upgrading of intelligent devices and terminals, the combination of big models and edge computing becomes possible. Their combination will change the way data is processed and interacted with, and enhance the user experience. In scenarios such as smart factories, smart driving, and smart healthcare, edge-based big language models have many roles. It can not only help devices understand natural language and quickly recognize verbal commands, but also perform real-time, efficient, and safe intelligent control. In addition, the big model at the edge can also analyze and predict sensor data in real time and generate a professional and reliable expert think tank. It solves all kinds of problems encountered in the production process and realizes faster and more accurate decision-making. Since the data is not transmitted to the central server during processing, data privacy is guaranteed. This is very important for the construction of private big models.
Difficulties and Challenges
The benefits that can be brought by combining edge computing with big models can be countless, but the challenges are also huge. Among them, how to successfully deploy and run huge and complex big models on edge devices, solve the problem of data silos between different edge computing nodes, and promote the standardization of models and edge computing are all urgent issues.
Nonetheless, the combination of edge computing and big models is still bringing a new light to the IoT industry. Hopefully, the problems will all be solved over time. IoT can be fully utilized to its fullest potential with emerging technologies.