AI & Technology

Copyright: SoraEase , please indicate the source when forwarding. This article from the https://github.com/SoraEase/sora-prompt open source project,SoraEase wants to provide automated, easy, and quick to use tools and guidelines for SORa-related developers. Sora Prompt Collection, a repository dedicated to inspiring AI-driven video creation with Sora. Structured Prompt | Sora Collection of prompt words, a repository designed to inspire AI-driven video creation using Sora. Sora | Sora is an AI model that can create realistic and imaginative scenes from OpenAI’s text instructions. OpenAI is teaching AI to understand and simulate the physical world in motion, with the goal of training models to help people solve problems that require real-world interaction. ...

Sora! ! ! Recently, there has been a craze about Sora on the Internet. As the latest technology launched by OpenAI, Sora gives the magic of text-generated videos, and the results it demonstrates are impressive. At present, the appeal of short videos has far exceeded traditional novels and graphic comics. Therefore, the advent of Sora may trigger a revolution in the field of video production. The charm of Sora is that it can generate up to 60 seconds of video content based on text descriptions, which includes detailed scene settings, lifelike character expressions, and smooth camera transitions. ...

After researching a large amount of information, we summarized the methods of memorizing words and learning spoken English. A problem student in the eyes of teachers since childhood, and a stupid child in the eyes of parents. For a class teacher whose eyes are full of excellent students, there is no room for an undistinguished student like me in his eyes. I have been on the road to understanding and redeeming myself, constantly exploring why others memorize words so quickly, why all online learning methods fail for me, and why everyone thinks it is my problem… ...

These go: instructions in the Go source code && go automation tools Developers have a strong tendency to automate repetitive tasks, and this also applies to writing code. Boilerplate code may include operations such as setting up a basic file structure, initializing variables, defining functions, or importing libraries or modules. In some cases, packages provide boilerplate code as a starting point for developers to build from, typically generated after the code behavior has been configured. Although boilerplate code may be necessary and valuable to application functionality, it can also be wasteful and redundant. For this reason, there are many tools that minimize boilerplate code. go generate is a command line tool for the Go programming language that allows automatic code generation. You can use go generate to generate easily modifiable code specific to your project, making the tool powerful at reducing boilerplate. go generate This command is usually used to automatically generate code before compilation. It can be used to create repetitive or patterned code, thereby saving time and reducing errors. Think about it, in what situations would this be particularly useful? 🤔 ...

OpenIM cross-platform source code type checking tool start question In the automation path of OpenIM, it involves more and more comprehensive automated design and testing. In the process, I encountered a problem, so I completed a full set of experience from go language type detection to integrated local and CI. The problem is this issue: https://github.com/openimsdk/open-im-server/issues/1807 Our Go code encountered an integer overflow issue when running on a 32-bit system (linux/386). This problem occurs because the int type in Go has different sizes depending on the architecture: on 32-bit systems it is equivalent to int32, and on 64-bit systems it is equivalent to int64. ...

Vector database learning I learned rust today and found that rust is a very suitable language for writing databases. I found a treasure project tikv. Its github project address is https://github.com/tikv/tikv . It is a very active project, but today I The topic is vector database in the field of AI. Without further ado, let’s get started right away. prerequisites 0.1 Introduction to basic knowledge: Understand the basic definition of vector database and its difference from traditional database. 0.2 Data Structure Basics: Learn vectors and other basic data structures, and how to represent and manipulate these structures in databases. 0.3 Introduction to Linear Algebra: Introduction to vector operations, including vector addition, subtraction and dot multiplication. 0.4 Similarity measures: Learn how to calculate similarity between vectors, such as cosine similarity. 0.5 Basics of Database Index: Introduces the basic concepts of database index, especially its application in vector databases. 0.6 Preliminary Search Algorithms: Learn basic search algorithms and understand how to perform effective searches in large data sets. 0.7 Application case studies: Study the application of vector databases in different fields (such as recommendation systems, image recognition). ...

The success of an open-source project largely depends on its quality management and collaborative processes. In the OpenIM open-source community, the standardization of project management and testing processes is crucial to ensure the quality and stability of the codebase. This document provides a brief overview of our testing strategy, branch management, quality control policies, and how they are applied to the main branch, PR testing branches, and stable release branches to meet the needs of developers, testers, and community managers. Additionally, we will introduce the standards, testing schemes, and project management strategies of the OpenIM open-source community, aiming to provide clear guidance to ensure project stability and sustainability. ...

Large language model sharing meeting on January 6, 2024 Limitations of the model: Deep learning Pre-trained model Large language model The emergent power of large language models: 💡 Relevant research on emergence phenomena has been done for a long time in the discipline of complex systems. So, what is “emergent phenomenon”? When a complex system is composed of many tiny individuals, these tiny individuals come together and interact with each other. When the number is large enough, they exhibit special phenomena that cannot be explained by the microscopic individuals at the macro level. This can be called an "emergent phenomenon." Link: ...

Today we will take a look at the theory and practice of kubernetes and gitops Command introduction First, let’s take a look at the subnaming supported by kubectl for our convenience: kubectl apply - applies the definition of one or more resources. Typically used to deploy applications or update resources. kubectl get - displays information about one or more resources. This is a common command to view the status of resources in a Kubernetes cluster. kubectl describe - Displays details of one or more resources, such as events, status, and configuration. kubectl delete - Delete resources in the Kubernetes cluster. kubectl exec - Execute commands in containers in the cluster. kubectl logs - Print container logs. kubectl create - Create one or more resources from a file or standard input. kubectl edit - Edit resources in the cluster. This will open an editor to modify the resource’s configuration. kubectl port-forward - Forward local ports to Pods in the cluster. kubectl run - Run a specified image in the cluster. kubectl scale - Adjust the number of replicas of resources (such as Deployment, ReplicaSet). kubectl rollout - Manage the deployment of resources, such as viewing status, pausing, resuming or rolling back updates. **In addition to the above commands, kubectl in Kubernetes also supports annotations: ** ...

OpenIM offers various flexible deployment options to suit different environments and requirements. Here is a simplified and optimized description of these deployment options: Source Code Deployment: Regular Source Code Deployment: Deployment using the nohup method. This is a basic deployment method suitable for development and testing environments. For details, refer to the Regular Source Code Deployment Guide . Production-Level Deployment: Deployment using the system method, more suitable for production environments. This method provides higher stability and reliability. For details, refer to the Production-Level Deployment Guide . Cluster Deployment: Kubernetes Deployment: Provides two deployment methods, including deployment through Helm and sealos. This is suitable for environments that require high availability and scalability. Specific methods can be found in the Kubernetes Deployment Guide . Docker Deployment: Regular Docker Deployment: Suitable for quick deployments and small projects. For detailed information, refer to the Docker Deployment Guide . Docker Compose Deployment: Provides more convenient service management and configuration, suitable for complex multi-container applications. Next, we will introduce the specific steps, monitoring, and management backend configuration for each of these deployment methods, as well as usage tips to help you choose the most suitable deployment option according to your needs. ...