update README for version 3

README.md

@@ -10,16 +10,16 @@ English | [简体中文](./README_cn.md) | [日本語](./README_ja.md)
 [![Documentation Status](https://img.shields.io/badge/中文文档-最新-brightgreen.svg)](https://paddlepaddle.org.cn/documentation/docs/zh/guides/index_cn.html)
 [![Release](https://img.shields.io/github/release/PaddlePaddle/Paddle.svg)](https://github.com/PaddlePaddle/Paddle/releases)
 [![License](https://img.shields.io/badge/license-Apache%202-blue.svg)](LICENSE)
-[![Twitter](https://img.shields.io/badge/Twitter-1ca0f1.svg?logo=twitter&logoColor=white)](https://twitter.com/PaddlePaddle)
+![X (formerly Twitter) URL](https://img.shields.io/twitter/url?url=https%3A%2F%2Fx.com%2FPaddlePaddle)
 
 Welcome to the PaddlePaddle GitHub.
 
 PaddlePaddle, as the first independent R&D deep learning platform in China, has been officially open-sourced to professional communities since 2016. It is an industrial platform with advanced technologies and rich features that cover core deep learning frameworks, basic model libraries, end-to-end development kits, tools & components as well as service platforms.
-PaddlePaddle is originated from industrial practices with dedication and commitments to industrialization. It has been widely adopted by a wide range of sectors including manufacturing, agriculture, enterprise service, and so on while serving more than 10.7 million developers, 235,000 companies and generating 860,000 models. With such advantages, PaddlePaddle has helped an increasing number of partners commercialize AI.
+PaddlePaddle originates from industrial practices with dedication and commitments to industrialization. It has been widely adopted by a wide range of sectors including manufacturing, agriculture, enterprise service, and so on while serving more than 18.08 million developers, 430,000 companies and generating 1,010,000 models. With such advantages, PaddlePaddle has helped an increasing number of partners commercialize AI.
 
 ## Installation
 
-### Latest PaddlePaddle Release: [3.0-rc](https://github.com/PaddlePaddle/Paddle/tree/release/3.0-rc)
+### Latest PaddlePaddle Release: [3.0](https://github.com/PaddlePaddle/Paddle/tree/release/3.0)
 
 Our vision is to enable deep learning for everyone via PaddlePaddle.
 Please refer to our [release announcement](https://github.com/PaddlePaddle/Paddle/releases) to track the latest features of PaddlePaddle.
@@ -35,68 +35,54 @@ pip install paddlepaddle-gpu
 
 For more information about installation, please view [Quick Install](https://www.paddlepaddle.org.cn/install/quick)
 
-Now our developers can acquire Tesla V100 online computing resources for free. If you create a program by AI Studio, you will obtain 8 hours to train models online per day. [Click here to start](https://aistudio.baidu.com/aistudio/index).
+## **PaddlePaddle New Generation Framework 3.0**
 
-## FOUR LEADING TECHNOLOGIES
+* **Unified Dynamic/Static Graphs and Automatic Parallelism**
 
-- **Agile Framework for Industrial Development of Deep Neural Networks**
+    By requiring only minimal tensor partitioning annotations based on a single-card configuration, PaddlePaddle automatically discovers the most efficient distributed parallel strategy. This significantly reduces the costs of industrial development and training, enabling developers to focus more intently on model and algorithm innovation.
 
-    The PaddlePaddle deep learning framework facilitates the development while lowering the technical burden, through leveraging a programmable scheme to architect the neural networks. It supports both declarative programming and imperative programming with both development flexibility and high runtime performance preserved.  The neural architectures could be automatically designed by algorithms with better performance than the ones designed by human experts.
+* **Integrated Training and Inference for Large Models**
 
-- **Support Ultra-Large-Scale Training of Deep Neural Networks**
+    The same framework supports both training and inference, achieving code reuse and seamless integration between these stages. This provides a unified development experience and maximum training efficiency for the entire large model workflow, offering the industry a superior development experience.
 
-    PaddlePaddle has made breakthroughs in ultra-large-scale deep neural networks training. It launched the world's first large-scale open-source training platform that supports the training of deep networks with 100 billion features and trillions of parameters using data sources distributed over hundreds of nodes. PaddlePaddle overcomes the online deep learning challenges for ultra-large-scale deep learning models, and further achieved real-time model updating with more than 1 trillion parameters.
-     [Click here to learn more](https://github.com/PaddlePaddle/Fleet)
+* **High-Order Differentiation for Scientific Computing**
 
-- **High-Performance Inference Engines for Comprehensive Deployment Environments**
+    Provides capabilities such as high-order automatic differentiation, complex number operations, Fourier transforms, compilation optimization, and distributed training support. It facilitates scientific exploration in fields including mathematics, mechanics, materials science, meteorology, and biology, substantially improving the speed of solving differential equations.
 
-   PaddlePaddle is not only compatible with models trained in 3rd party open-source frameworks , but also offers complete inference products for various production scenarios. Our inference product line includes [Paddle Inference](https://www.paddlepaddle.org.cn/inference/master/guides/introduction/index_intro.html): Native inference library for high-performance server and cloud inference; [FastDeploy](https://github.com/PaddlePaddle/FastDeploy): Easy-to-use and High Performance AI model deployment toolkit for Cloud, Mobile and Edge without-of-the-box and unified experience; [Paddle Lite](https://github.com/PaddlePaddle/Paddle-Lite): Ultra-Lightweight inference engine for mobile and IoT environments; [Paddle.js](https://www.paddlepaddle.org.cn/paddle/paddlejs): A frontend inference engine for browser and mini-apps. Furthermore, by great amounts of optimization with leading hardware in each scenario, Paddle inference engines outperform most of the other mainstream frameworks.
+* **Neural Network Compiler**
 
-- **Industry-Oriented Models and Libraries with Open Source Repositories**
+    Adopting an integrated framework design, it supports efficient training and flexible inference for diverse models, including generative and scientific computing models. It achieves an effective balance between computational flexibility and high performance, significantly lowering performance optimization costs.
 
-     PaddlePaddle includes and maintains more than 100 mainstream models that have been practiced and polished for a long time in the industry. Some of these models have won major prizes from key international competitions. In the meanwhile, PaddlePaddle has further more than 200 pre-training models (some of them with source codes) to facilitate the rapid development of industrial applications.
-     [Click here to learn more](https://github.com/PaddlePaddle/models)
+* **Heterogeneous Multi-Chip Adaptation**
+    Features a mature and complete unified adaptation solution for multiple hardware types. Through standardized interfaces, it abstracts the variations in development interfaces across different chip software stacks, realizing a pluggable architecture.
 
 ## Documentation
 
 We provide [English](https://www.paddlepaddle.org.cn/documentation/docs/en/guides/index_en.html) and
 [Chinese](https://www.paddlepaddle.org.cn/documentation/docs/zh/guide/index_cn.html) documentation.
 
-- [Guides](https://www.paddlepaddle.org.cn/documentation/docs/en/guides/index_en.html)
+* [Guides](https://www.paddlepaddle.org.cn/documentation/docs/en/guides/index_en.html)
 
   You might want to start from how to implement deep learning basics with PaddlePaddle.
 
-- [Practice](https://www.paddlepaddle.org.cn/documentation/docs/zh/tutorial/index_cn.html)
+* [Practice](https://www.paddlepaddle.org.cn/documentation/docs/zh/tutorial/index_cn.html)
 
   So far you have already been familiar with Fluid. And the next step should be building a more efficient model or inventing your original Operator.
 
-- [API Reference](https://www.paddlepaddle.org.cn/documentation/docs/en/api/index_en.html)
+* [API Reference](https://www.paddlepaddle.org.cn/documentation/docs/en/api/index_en.html)
 
    Our new API enables much shorter programs.
 
-- [How to Contribute](https://www.paddlepaddle.org.cn/documentation/docs/en/guides/08_contribution/index_en.html)
+* [How to Contribute](https://www.paddlepaddle.org.cn/documentation/docs/en/guides/08_contribution/index_en.html)
 
    We appreciate your contributions!
 
 ## Open Source Community
 
-- [Github Issues](https://github.com/PaddlePaddle/Paddle/issues): bug reports, feature requests, install issues, usage issues, etc.
-
-- Open Source Contribution Activities:
-
-  - Beginner: Happy Open Source Activity（[Regular Season](https://github.com/PaddlePaddle/Paddle/issues/56689)、[Pre-Hackathon Camp](https://github.com/PaddlePaddle/Paddle/issues/58497)）
-  - Advanced: PaddlePaddle Hackathon（[Personal Challenge Competition](https://github.com/PaddlePaddle/Paddle/issues/57262)、[LLM Application Competition](https://github.com/PaddlePaddle/Paddle/issues/57585)、[Hackathon Code Camp](https://github.com/PaddlePaddle/Paddle/issues/57264)）
-
-- Community Organizations:
-  - Technical Organization: [Paddle Framework Contributor Club, PFCC](https://github.com/PaddlePaddle/community/tree/master/pfcc)
-  - Community Governance Organization: [PaddlePaddle OpenSource Development Working Group, PPOSDWG](https://github.com/PaddlePaddle/community/tree/master/pposdwg)
-
-- Community Blog: <https://pfcc.blog/>
-
-## Courses
-
-- [Server Deployments](https://aistudio.baidu.com/aistudio/course/introduce/19084): Courses introducing high performance server deployments via local and remote services.
-- [Edge Deployments](https://aistudio.baidu.com/aistudio/course/introduce/22690): Courses introducing edge deployments from mobile, IoT to web and applets.
+* [Github Issues](https://github.com/PaddlePaddle/Paddle/issues): bug reports, feature requests, install issues, usage issues, etc.
+* Many of our contribution events offer varying levels of mentorship from experienced community members, please check the events in the pinned issues, and consider attending.
+* Community Blog: <https://pfcc.blog/>
+* See more details about PaddlePaddle community at [community](https://github.com/PaddlePaddle/community).
 
 ## Copyright and License
 

README_cn.md

@@ -14,11 +14,11 @@
 
 欢迎来到 PaddlePaddle GitHub
 
-飞桨(PaddlePaddle)以百度多年的深度学习技术研究和业务应用为基础，是中国首个自主研发、功能完备、 开源开放的产业级深度学习平台，集深度学习核心训练和推理框架、基础模型库、端到端开发套件和丰富的工具组件于一体。目前，飞桨累计开发者1070万，服务企业23.5万家，基于飞桨开源深度学习平台产生了86万个模型。飞桨助力开发者快速实现AI想法，快速上线AI业务。帮助越来越多的行业完成AI赋能，实现产业智能化升级。
+飞桨(PaddlePaddle)以百度多年的深度学习技术研究和业务应用为基础，是中国首个自主研发、功能完备、 开源开放的产业级深度学习平台，集深度学习核心训练和推理框架、基础模型库、端到端开发套件和丰富的工具组件于一体。目前，飞桨累计开发者 1808 万，服务企业 43 万家，基于飞桨开源深度学习平台产生了 101 万个模型。飞桨助力开发者快速实现 AI 想法，快速上线 AI 业务。帮助越来越多的行业完成 AI 赋能，实现产业智能化升级。
 
 ## 安装
 
-### PaddlePaddle 最新版本: [3.0-rc](https://github.com/PaddlePaddle/Paddle/tree/release/3.0-rc)
+### PaddlePaddle 最新版本: [3.0](https://github.com/PaddlePaddle/Paddle/tree/release/3.0)
 
 跟进 PaddlePaddle 最新特性请参考我们的[版本说明](https://github.com/PaddlePaddle/Paddle/releases)
 
@@ -31,29 +31,29 @@ pip install paddlepaddle
 pip install paddlepaddle-gpu
 ```
 
-更多安装信息详见官网 [安装说明](https://www.paddlepaddle.org.cn/install/quick)
+更多安装信息详见官网 [安装说明](https://www.paddlepaddle.org.cn/install/quick)。
 
-PaddlePaddle用户可领取**免费Tesla V100在线算力资源**，训练模型更高效。**每日登陆即送8小时**，[前往使用免费算力](https://aistudio.baidu.com/aistudio/index)。
+## 飞桨新一代框架 3.0
 
-## 四大领先技术
+- **动静统一自动并行**
 
-- **开发便捷的产业级深度学习框架**
+  只需在单卡基础上进行少量的张量切分标记，飞桨能自动寻找最⾼效的分布式并行策略，大幅度降低了产业开发和训练的成本，使开发者能够更专注于模型和算法的创新。
 
-    飞桨深度学习框架采用基于编程逻辑的组网范式，对于普通开发者而言更容易上手，符合他们的开发习惯。同时支持声明式和命令式编程，兼具开发的灵活性和高性能。网络结构自动设计，模型效果超越人类专家。
+- **大模型训练推一体**
 
-- **支持超大规模深度学习模型的训练**
+  同一套框架支持训练和推理，实现训练、推理代码复用和无缝衔接，为大模型的全流程提供了统一的开发体验和极致的训练效率，为产业提供了极致的开发体验。
 
-    飞桨突破了超大规模深度学习模型训练技术，实现了支持千亿特征、万亿参数、数百节点的开源大规模训练平台，攻克了超大规模深度学习模型的在线学习难题，实现了万亿规模参数模型的实时更新。
-    [查看详情](https://github.com/PaddlePaddle/Fleet)
+- **科学计算高阶微分**
 
-- **支持多端多平台的高性能推理部署工具**
+  提供高阶自动微分、复数运算、傅里叶变换、编译优化、分布式训练等能力支持，支持数学、力学、材料、气象、生物等领域科学探索，微分方程求解速度大幅提升。
 
-    飞桨不仅广泛兼容第三方开源框架训练的模型部署，并且为不同的场景的生产环境提供了完备的推理引擎，包括适用于高性能服务器及云端推理的原生推理库 [Paddle Inference](https://www.paddlepaddle.org.cn/inference/master/guides/introduction/index_intro.html)，全场景、易用灵活、极致高效的AI推理部署工具，支持云边端部署工具 [FastDeploy](https://github.com/PaddlePaddle/FastDeploy)，针对于移动端、物联网场景的轻量化推理引擎 [Paddle Lite](https://github.com/PaddlePaddle/Paddle-Lite)，以及在浏览器、小程序等环境下使用的前端推理引擎 [Paddle.js](https://www.paddlepaddle.org.cn/paddle/paddlejs)。同时，透过与不同场景下的主流硬件高度适配优化及异构计算的支持, 飞桨的推理性能也领先绝大部分的主流实现。
+- **神经网络编译器**
 
-- **面向产业应用，开源开放覆盖多领域的工业级模型库。**
+  采用框架一体化设计，支持⽣成式模型、科学计算模型等多种模型的高效训练与可变形推理，在计算灵活性与高性能之间提供了良好的平衡点，显著降低性能优化成本。
 
-    飞桨官方支持100多个经过产业实践长期打磨的主流模型，其中包括在国际竞赛中夺得冠军的模型；同时开源开放200多个预训练模型，助力快速的产业应用。
-    [查看详情](https://github.com/PaddlePaddle/models)
+- **异构多芯适配**
+
+  成熟且完整的多硬件统一适配方案，通过标准化接口屏蔽了不同芯片软件栈开发接口差异，实现可插拔架构。
 
 ## 文档
 
@@ -69,23 +69,11 @@ PaddlePaddle用户可领取**免费Tesla V100在线算力资源**，训练模型
 
 ## 开源社区
 
-- [Github Issues](https://github.com/PaddlePaddle/Paddle/issues)：提交安装/使用问题、报告bug、建议新特性、沟通开发计划等
-- 社区活动：
-
-  - 入门：快乐开源活动（[热身打卡 + 常规赛](https://github.com/PaddlePaddle/Paddle/issues/56689)、[启航计划](https://github.com/PaddlePaddle/Paddle/issues/58497)）
-  - 进阶：飞桨黑客马拉松（[开源贡献个人挑战赛](https://github.com/PaddlePaddle/Paddle/issues/57262)、[大模型应用与创意赛](https://github.com/PaddlePaddle/Paddle/issues/57585)、[飞桨护航计划集训营](https://github.com/PaddlePaddle/Paddle/issues/57264)）
-
-- 社区组织：
-  - 技术交流组织：[飞桨核心框架贡献者俱乐部 PFCC](https://github.com/PaddlePaddle/community/tree/master/pfcc)
-  - 社区治理组织：[飞桨社区开源发展工作组 PPOSDWG](https://github.com/PaddlePaddle/community/tree/master/pposdwg)
-
-- 社区博客：<https://pfcc.blog/>
-
-## 课程
-
-- [服务器部署](https://aistudio.baidu.com/aistudio/course/introduce/19084)：详细介绍高性能服务器端部署实操，包含本地端及服务化Serving部署等
-- [端侧部署](https://aistudio.baidu.com/aistudio/course/introduce/22690)：详细介绍端侧多场景部署实操，从移动端设备、IoT、网页到小程序部署
+- [Github Issues](https://github.com/PaddlePaddle/Paddle/issues)：错误报告、功能请求、安装问题、使用问题等。
+- 我们的许多贡献活动都提供来自经验丰富的社区成员的不同程度的指导，请查看置顶的 issues 中的活动，并考虑参加。
+- 社区博客：[https://pfcc.blog/](https://pfcc.blog/)。
+- 了解更多详情：[Community](https://github.com/PaddlePaddle/community)。
 
 ## 版权和许可证
 
-PaddlePaddle由[Apache-2.0 license](LICENSE)提供
+PaddlePaddle 由[Apache-2.0 license](LICENSE)提供