Best AI tools for< Design Cloud Systems >

Motiff is an AI-powered professional interface design tool that enables collaboration between human and AI to achieve 10x efficiency in UI design. It offers a comprehensive platform for designing, aligning, and building with a team, along with features like cloud collaboration, prototyping, and Dev Mode for developers. Motiff provides high-performance design tools at a cost-effective price, with a focus on smooth performance, speedy optimization, and robust stability. The application aims to push creativity to the max by starting intelligent practices and exploring the future of AI design systems.

NVIDIA is a world leader in artificial intelligence computing. The company's products and services are used by businesses and governments around the world to develop and deploy AI applications. NVIDIA's AI platform includes hardware, software, and tools that make it easy to build and train AI models. The company also offers a range of cloud-based AI services that make it easy to deploy and manage AI applications. NVIDIA's AI platform is used in a wide variety of industries, including healthcare, manufacturing, retail, and transportation. The company's AI technology is helping to improve the efficiency and accuracy of a wide range of tasks, from medical diagnosis to product design.

Microsoft is a leading technology company that develops, manufactures, licenses, supports, and sells computer software, consumer electronics, personal computers, and services. Its best-known software products are the Microsoft Windows operating system, the Microsoft Office suite, and the Internet Explorer and Edge web browsers. Its hardware products include the Xbox video game consoles and the Surface tablet computers. Microsoft is also a major provider of cloud computing services through its Azure platform.

Mobileye is a leading company specializing in driver assist and autonomous driving technologies. With a focus on developing innovative solutions for the automotive industry, Mobileye has revolutionized driver-assist technology by leveraging camera sensors to enhance safety and efficiency in vehicles. The company offers a range of solutions, from cloud-enhanced driver-assist systems to fully autonomous driving capabilities, all designed to provide a seamless and natural driving experience. By developing both hardware and software in-house, Mobileye ensures a safe-by-design approach that prioritizes scalability and efficiency, making their technology accessible to the mass market.

CloudLinks is an AI-powered platform that offers a range of services including mobile application development, web design, consultancy, cloud solutions, hosting, and maintenance. The platform focuses on customer-centric solutions tailored to individual business needs, providing seamless integration with existing systems and empowering businesses with e-commerce solutions and AI-driven innovation. CloudLinks prioritizes collaboration with clients, delivering reliable and innovative solutions that enhance efficiency and growth. With a wealth of experience and a commitment to customer success, CloudLinks aims to streamline operations, boost customer engagement, and increase revenue for businesses.

N-iX is a global provider of software development outsourcing services with delivery centers across Europe and over 2,200 expert software developers. We partner with technology businesses globally helping them to build successful engineering teams and create innovative software products. Our expertise includes cloud solutions, data analytics, machine learning & AI, embedded software and IoT, enterprise VR, and RPA and enterprise platforms.

AiHouse is an AI-powered integrated 3D design tool that provides an all-in-one solution for interior design and manufacturing. It offers a range of features including 2D/3D floor plan creation, room decoration, furniture customization, photo-realistic visualization, 3D walkthrough videos, product visualization, and end-to-end design-to-manufacture solutions. AiHouse is designed to streamline the design process, improve communication with clients, and increase efficiency for interior designers, furniture brands, and manufacturers.

UbiOps is an AI infrastructure platform that helps teams quickly run their AI & ML workloads as reliable and secure microservices. It offers powerful AI model serving and orchestration with unmatched simplicity, speed, and scale. UbiOps allows users to deploy models and functions in minutes, manage AI workloads from a single control plane, integrate easily with tools like PyTorch and TensorFlow, and ensure security and compliance by design. The platform supports hybrid and multi-cloud workload orchestration, rapid adaptive scaling, and modular applications with unique workflow management system.

Metail is an AI tool specializing in apparel AI solutions. The platform offers services such as EcoShot for creating on-model images from 3D designs, AI-generated models, and Machine-Learning Advanced Motion Analytics (MAMA) for factory efficiency. Metail also provides the Metail-Avatar-System (MAS) for accurate 3D body scans and SizeStream mobile apps for personalized experiences. The company focuses on leveraging AI technologies to enhance the capabilities of apparel companies and improve user experiences.

HUAWEI Cloud Pangu is an AI tool designed for accelerating drug discovery by optimizing drug molecules. It offers features such as Molecule Search, Molecule Optimizer, and Pocket Molecule Design. Users can submit molecules for optimization and view historical optimization results. The tool is based on the MindSpore framework and has been visited over 300,000 times since August 23, 2021.

XKool Technology is an AI cloud platform offering comprehensive solutions for the building industry. It provides digital and intelligent empowerment for design, construction, and management processes. The platform integrates AI technology to enhance building industrial upgrades and offers AI-assisted content creation, model marketplace, AI toolbox, and various design and management solutions.

Flush AI is an AI-powered art studio that allows users to create stunning digital art with just a few clicks. With its intuitive interface and powerful tools, Flush AI makes it easy for anyone to create beautiful and unique artwork, even if they have no prior experience with art or design. Flush AI is perfect for creating social media graphics, website banners, marketing materials, and more.

Études is a pioneering firm that seamlessly merges creativity and functionality to redefine architectural excellence. They offer a comprehensive suite of professional services catering to a diverse clientele, including renovation, restoration, consulting, project management, and architectural solutions. The Études Architect App allows collaboration among architects to showcase projects and explore the world of architecture. The Études Newsletter provides thought-provoking articles, case studies, and design insights. Testimonials highlight the time-saving and insightful benefits of using Études.

The AI Anime Generator is an online tool that allows users to generate anime characters or scenes by entering a description in a text box. Users can create unique anime images by providing specific details and clicking the 'Generate' button. The tool utilizes artificial intelligence to produce the desired image based on the input. It offers a user-friendly interface and is free to use for creating custom anime content.

ThinkDiffusion is a cloud-based AI application that offers a stable diffusion workspace for creating AI art. It provides fully-managed open-source cloud workspace with dedicated machine instances loaded with cutting-edge apps. Users can freely add extensions, upload models, and run multiple machines simultaneously. The platform offers different UI options catering to various user needs, from beginners to advanced model creators. ThinkDiffusion empowers users to create photorealistic art, animations, and videos with unmatched control and flexibility. It also hosts a learning center, community forums, and tutorials to support users in exploring the full potential of AI art creation.

RunDiffusion is a cloud-based platform that provides access to a suite of open-source AI tools, including Automatic1111, Fooocus, ComfyUI, and more. These tools enable users to generate images, videos, and other creative content using artificial intelligence. RunDiffusion offers a variety of features, including a user-friendly interface, a wide range of models to choose from, and the ability to collaborate with other users. The platform is suitable for both hobbyists and professionals, and it can be used for a variety of tasks, such as creating marketing materials, generating product ideas, and developing new artistic concepts.

Corel Vector is a web-based vector graphics application designed for hobbyists and aspiring professionals. It offers a user-friendly interface, intuitive tools, and unlimited cloud storage, making it accessible and convenient for users to create and store their designs. With its powerful vector editing capabilities, support for various file formats, and compatibility with touch devices, Corel Vector empowers users to design on any device, anytime, anywhere.

jsonAI is an AI tool that allows users to easily transform data into structured JSON format. Users can define their schema, add custom prompts, and receive AI-structured JSON responses. The tool enables users to create complex schemas with nested objects, control the response JSON on the fly, and test their JSON data in real-time. jsonAI offers a free trial plan, seamless integration with existing apps, and ensures data security by not storing user data on their servers.

Spline is a 3D design tool that allows users to create, edit, and collaborate on 3D designs in real-time. It is a web-based application that is accessible from any device with an internet connection. Spline is designed to be easy to use, even for beginners, and it offers a wide range of features that make it suitable for a variety of projects, from simple 3D models to complex animations and interactive experiences.

AIPage.dev is an AI-powered landing page generator that simplifies web development by utilizing cutting-edge AI technology. It allows users to create stunning landing pages with just a single prompt, eliminating the need for hours of coding and designing. The platform offers features like AI-driven design, intuitive editing interface, seamless cloud deployment, rapid development, effortless blog post creation, unlimited hosting for blog posts, lead collection, and seamless integration with leading providers. AIPage.dev aims to transform ideas into reality and empower users to showcase their projects and products effectively.

awesome-AIOps is a curated list of academic researches and industrial materials related to Artificial Intelligence for IT Operations (AIOps). It includes resources such as competitions, white papers, blogs, tutorials, benchmarks, tools, companies, academic materials, talks, workshops, papers, and courses covering various aspects of AIOps like anomaly detection, root cause analysis, incident management, microservices, dependency tracing, and more.

AI System School is a curated list of research in machine learning systems, focusing on ML/DL infra, LLM infra, domain-specific infra, ML/LLM conferences, and general resources. It provides resources such as data processing, training systems, video systems, autoML systems, and more. The repository aims to help users navigate the landscape of AI systems and machine learning infrastructure, offering insights into conferences, surveys, books, videos, courses, and blogs related to the field.

Yudao-cloud is an open-source project designed to provide a fast development platform for developers in China. It includes various system functions, infrastructure, member center, data reports, workflow, mall system, WeChat public account, CRM, ERP, etc. The project is based on Java backend with Spring Boot and Spring Cloud Alibaba microservices architecture. It supports multiple databases, message queues, authentication systems, dynamic menu loading, SaaS multi-tenant system, code generator, real-time communication, integration with third-party services like WeChat, Alipay, and more. The project is well-documented and follows the Alibaba Java development guidelines, ensuring clean code and architecture.

Züs is a high-performance cloud on a fast blockchain offering privacy and configurable uptime. It uses erasure code to distribute data between data and parity servers, allowing flexibility for IT managers to design for security and uptime. Users can easily share encrypted data with business partners through a proxy key sharing protocol. The ecosystem includes apps like Blimp for cloud migration, Vult for personal cloud storage, and Chalk for NFT artists. Other apps include Bolt for secure wallet and staking, Atlus for blockchain explorer, and Chimney for network participation. The QoS protocol challenges providers based on response time, while the privacy protocol enables secure data sharing. Züs supports hybrid and multi-cloud architectures, allowing users to improve regulatory compliance and security requirements.

Vearch is a cloud-native distributed vector database designed for efficient similarity search of embedding vectors in AI applications. It supports hybrid search with vector search and scalar filtering, offers fast vector retrieval from millions of objects in milliseconds, and ensures scalability and reliability through replication and elastic scaling out. Users can deploy Vearch cluster on Kubernetes, add charts from the repository or locally, start with Docker-compose, or compile from source code. The tool includes components like Master for schema management, Router for RESTful API, and PartitionServer for hosting document partitions with raft-based replication. Vearch can be used for building visual search systems for indexing images and offers a Python SDK for easy installation and usage. The tool is suitable for AI developers and researchers looking for efficient vector search capabilities in their applications.

This repository serves as a personal knowledge base for the owner's reference and use. It covers a wide range of topics including cloud-native operations, Kubernetes ecosystem, networking, cloud services, telemetry, CI/CD, electronic engineering, hardware projects, operating systems, homelab setups, high-performance computing applications, openwrt router usage, programming languages, music theory, blockchain, distributed systems principles, and various other knowledge domains. The content is periodically refined and published on the owner's blog for maintenance purposes.

Jina is a tool that allows users to build multimodal AI services and pipelines using cloud-native technologies. It provides a Pythonic experience for serving ML models and transitioning from local deployment to advanced orchestration frameworks like Docker-Compose, Kubernetes, or Jina AI Cloud. Users can build and serve models for any data type and deep learning framework, design high-performance services with easy scaling, serve LLM models while streaming their output, integrate with Docker containers via Executor Hub, and host on CPU/GPU using Jina AI Cloud. Jina also offers advanced orchestration and scaling capabilities, a smooth transition to the cloud, and easy scalability and concurrency features for applications. Users can deploy to their own cloud or system with Kubernetes and Docker Compose integration, and even deploy to JCloud for autoscaling and monitoring.

Milvus is an open-source vector database built to power embedding similarity search and AI applications. Milvus makes unstructured data search more accessible, and provides a consistent user experience regardless of the deployment environment. Milvus 2.0 is a cloud-native vector database with storage and computation separated by design. All components in this refactored version of Milvus are stateless to enhance elasticity and flexibility. For more architecture details, see Milvus Architecture Overview. Milvus was released under the open-source Apache License 2.0 in October 2019. It is currently a graduate project under LF AI & Data Foundation.

The LLM Twin Course is a free, end-to-end framework for building production-ready LLM systems. It teaches you how to design, train, and deploy a production-ready LLM twin of yourself powered by LLMs, vector DBs, and LLMOps good practices. The course is split into 11 hands-on written lessons and the open-source code you can access on GitHub. You can read everything and try out the code at your own pace.

High Performance LLMs 2024 is a comprehensive course focused on building a high-performance Large Language Model (LLM) from scratch using Jax. The course covers various aspects such as training, inference, roofline analysis, compilation, sharding, profiling, and optimization techniques. Participants will gain a deep understanding of Jax and learn how to design high-performance computing systems that operate close to their physical limits.

Chat Nio is a next-generation AIGC one-stop business solution that combines the advantages of frontend-oriented lightweight deployment projects with powerful API distribution systems. It offers rich model support, beautiful UI design, complete Markdown support, multi-theme support, internationalization support, text-to-image support, powerful conversation sync, model market & preset system, rich file parsing, full model internet search, Progressive Web App (PWA) support, comprehensive backend management, multiple billing methods, innovative model caching, and additional features. The project aims to address limitations in conversation synchronization, billing, file parsing, conversation URL sharing, channel management, and API call support found in existing AIGC commercial sites, while also providing a user-friendly interface design and C-end features.

Collective Mind (CM) is a collection of portable, extensible, technology-agnostic and ready-to-use automation recipes with a human-friendly interface (aka CM scripts) to unify and automate all the manual steps required to compose, run, benchmark and optimize complex ML/AI applications on any platform with any software and hardware: see online catalog and source code. CM scripts require Python 3.7+ with minimal dependencies and are continuously extended by the community and MLCommons members to run natively on Ubuntu, MacOS, Windows, RHEL, Debian, Amazon Linux and any other operating system, in a cloud or inside automatically generated containers while keeping backward compatibility - please don't hesitate to report encountered issues here and contact us via public Discord Server to help this collaborative engineering effort! CM scripts were originally developed based on the following requirements from the MLCommons members to help them automatically compose and optimize complex MLPerf benchmarks, applications and systems across diverse and continuously changing models, data sets, software and hardware from Nvidia, Intel, AMD, Google, Qualcomm, Amazon and other vendors: * must work out of the box with the default options and without the need to edit some paths, environment variables and configuration files; * must be non-intrusive, easy to debug and must reuse existing user scripts and automation tools (such as cmake, make, ML workflows, python poetry and containers) rather than substituting them; * must have a very simple and human-friendly command line with a Python API and minimal dependencies; * must require minimal or zero learning curve by using plain Python, native scripts, environment variables and simple JSON/YAML descriptions instead of inventing new workflow languages; * must have the same interface to run all automations natively, in a cloud or inside containers. CM scripts were successfully validated by MLCommons to modularize MLPerf inference benchmarks and help the community automate more than 95% of all performance and power submissions in the v3.1 round across more than 120 system configurations (models, frameworks, hardware) while reducing development and maintenance costs.

Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. * **Highly performant** : web layer and task coordination built with Rust 🦀, which offers blazing speed in addition to efficient CPU utilization powered by async I/O * **Ease of use** : user interface purely in Python 🐍, by which users can serve their models in an ML framework-agnostic manner using the same code as they do for offline testing * **Dynamic batching** : aggregate requests from different users for batched inference and distribute results back * **Pipelined stages** : spawn multiple processes for pipelined stages to handle CPU/GPU/IO mixed workloads * **Cloud friendly** : designed to run in the cloud, with the model warmup, graceful shutdown, and Prometheus monitoring metrics, easily managed by Kubernetes or any container orchestration systems * **Do one thing well** : focus on the online serving part, users can pay attention to the model optimization and business logic

Kaapana is an open-source toolkit for state-of-the-art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. Obtaining large amounts of medical data necessary for developing and training modern machine learning methods is an extremely challenging effort that often fails in a multi-center setting, e.g. due to technical, organizational and legal hurdles. A federated approach where the data remains under the authority of the individual institutions and is only processed on-site is, in contrast, a promising approach ideally suited to overcome these difficulties. Following this federated concept, the goal of Kaapana is to provide a framework and a set of tools for sharing data processing algorithms, for standardized workflow design and execution as well as for performing distributed method development. This will facilitate data analysis in a compliant way enabling researchers and clinicians to perform large-scale multi-center studies. By adhering to established standards and by adopting widely used open technologies for private cloud development and containerized data processing, Kaapana integrates seamlessly with the existing clinical IT infrastructure, such as the Picture Archiving and Communication System (PACS), and ensures modularity and easy extensibility.

The Cheat-Sheet Collection for DevOps, Engineers, IT professionals, and more is a curated list of cheat sheets for various tools and technologies commonly used in the software development and IT industry. It includes cheat sheets for Nginx, Docker, Ansible, Python, Go (Golang), Git, Regular Expressions (Regex), PowerShell, VIM, Jenkins, CI/CD, Kubernetes, Linux, Redis, Slack, Puppet, Google Cloud Developer, AI, Neural Networks, Machine Learning, Deep Learning & Data Science, PostgreSQL, Ajax, AWS, Infrastructure as Code (IaC), System Design, and Cyber Security.

This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (🌟) this repo to find it easier later. ## 🧠 Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## 🗣️ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## 🚀 Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## 🙏 Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## 📂 Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## 🗃️ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |

The IBM Power Systems AIX Collection provides modules to manage configurations and deployments of Power AIX systems, enabling workloads on Power platforms as part of an enterprise automation strategy through the Ansible ecosystem. It includes example best practices, requirements for AIX versions, Ansible, and Python, along with resources for documentation and contribution.

Cool-GenAI-Fashion-Papers is a curated list of resources related to GenAI-Fashion, including papers, workshops, companies, and products. It covers a wide range of topics such as fashion design synthesis, outfit recommendation, fashion knowledge extraction, trend analysis, and more. The repository provides valuable insights and resources for researchers, industry professionals, and enthusiasts interested in the intersection of AI and fashion.

The yudao-ui-admin-vue3 repository is an open-source project focused on building a fast development platform for developers in China. It utilizes Vue3 and Element Plus to provide features such as configurable themes, internationalization, dynamic route permission generation, common component encapsulation, and rich examples. The project supports the latest front-end technologies like Vue3 and Vite4, and also includes tools like TypeScript, pinia, vueuse, vue-i18n, vue-router, unocss, iconify, and wangeditor. It offers a range of development tools and features for system functions, infrastructure, workflow management, payment systems, member centers, data reporting, e-commerce systems, WeChat public accounts, ERP systems, and CRM systems.

Expert in system design best practices for cloud solutions

Create UML for flowcharts, Class, Sequence, Use Case, and Activity diagrams using PlantUML. System design and cloud infrastructure diagrams for AWS, Azue and GCP. No login required.

A System Architect Coach guiding you through system design principles and best practices. Explains CAP theorem like no one else

Specializes in PlantUML diagrams with structured API and microservice groups

Helping software engineers to architect domain-driven serverless systems on AWS

Expert advice on Azure, clear and concise.

Drives efficient back-end processes through innovative coding and software solutions.

Expert in backend/system design for scalable and secure web applications.

Guides cloud strategy and architecture to optimize business operations.

Architecte cloud chez KingLand et passionné de nature. Conception d'architectures cloud, expertise en solutions cloud, capacité d'innovation technologique, compétences en gestion de projet, collaboration interdépartementale.

Expert in cloud computing, offering insights on services, security, and infrastructure.

Expert in all aspects of Google Cloud Platform.

Cloud Engineer Expert, guiding in cloud tech, projects, career, and industry trends.

Expert in cloud-native solutions, provides tailored tech advice and cost estimates.

Cloud Mentor in AWS, Azure & Google Cloud for all your cloud related problems.

Create Goa services in seconds

Cybernetic humanoid expert in extraterrestrial tech, driven to merge past and future.

Architext is a sophisticated chatbot designed to guide users through the complexities of AWS architecture, leveraging the AWS Well-Architected Framework. It offers real-time, tailored advice, interactive learning, and up-to-date resources for both novices and experts in AWS cloud infrastructure.

I can convert your favorite quotes into a word cloud with a specified shape.

Senior Java software engineer and cloud expert