2results about How to "Fix cold start" patented technology

This invention discloses a method and system for elastic scaling of serverless computing resources based on probability distribution, belonging to the field of serverless computing elastic scaling technology. This invention deploys multiple user service functions in a Kubernetes cluster. Users call these deployed functions through the corresponding APIs or HTTP requests provided by the cluster. The elastic scaler expands and shrinks function instances according to the volume of user requests to quickly respond to user requests. This invention calculates the number of preheated function instances by constructing a probability distribution and combines the dispersion of data to address the problem of sudden traffic surges in cloud environments for elastic scaling. This not only ensures timely responses to user requests but also reduces the computational cost and time overhead in calculating the number of preheated function instances while maintaining low latency. By predicting the probability distribution using a deep learning model, request response time can be significantly reduced, effectively mitigating the impact of cold start problems on serverless computing.

This invention discloses an image data annotation method based on artificial intelligence, relating to the fields of computer vision and machine learning. It includes the following steps: S1 Model initialization step; S2 Intelligent pre-annotation and selection step; S3 Human-machine collaborative correction step; S4 Model iterative update step; S5 Closed-loop feedback step. This invention significantly improves efficiency: intelligent pre-annotation avoids manual annotation from scratch, and utilizes an active learning strategy to maximize the value of human intervention, increasing overall annotation efficiency by more than 50%. Dynamic quality improvement: the closed-loop iteration mechanism allows the model to continuously learn from human feedback, and the pre-annotation quality continuously improves with each iteration, forming a self-reinforcing virtuous cycle.