Best AI tools for< Receive Design Critiques >

Mock-My-Mockup is an AI-powered product design tool created by Fairpixels. It allows users to upload a screenshot of a page they are working on and receive brutally honest feedback. The tool offers a user-friendly interface where users can easily drag and drop their product screenshots for analysis.

Designera is an AI-powered design tool that allows users to create design ideas specialized to their interior spaces in seconds. Users can upload images of their rooms, select room types and themes, and receive design suggestions tailored to their preferences. The tool provides a platform for users to explore creative design concepts and get inspired by a community of designers. Designera aims to simplify the design process and empower users to visualize and transform their living spaces with ease.

InkGen is an AI Tattoo Generator that allows users to create the perfect tattoo design with the help of a personal tattoo artist AI. Users can input their tattoo ideas, select styles and colors, and receive unique design concepts within seconds. The platform has generated over 423,490 tattoos for satisfied customers, offering a wide range of design options. Users can interact with the AI to bring their tattoo dreams to life, ensuring each design is unique and tailored to their preferences.

DecorAI.xyz is an AI-driven interior design tool that allows users to generate dream rooms using artificial intelligence. By simply taking a picture of a room, users can see how it looks in different themes and receive personalized design suggestions. With exceptional training on a massive dataset of 160 million design samples, DecorAI optimizes spatial layouts, provides cost-effective design solutions, and saves time compared to traditional interior design methods. The tool caters to homeowners, renters, and small businesses looking to redesign their spaces without the need for an expensive interior designer.

Paintit.ai is an AI-driven interior design service that revolutionizes space design by leveraging the latest in AI technology. It offers personalized and innovative design solutions for residential and commercial spaces, capturing unique visions and style preferences. Users can upload photos of their space, select design preferences, and receive AI-generated design concepts that can be refined to align with individual tastes and visions.

Tattoo Design Pro is an AI-powered application that allows users to transform their imagination into stunning tattoo designs in various styles. Whether starting with a simple prompt or uploading an existing sketch, the app uses AI magic to create unique and detailed designs. Customers can experiment with different designs, receive AI-generated suggestions, and easily choose the perfect tattoo design. The app provides a user-friendly interface and a wide range of features to help tattoo enthusiasts and artists in the design process.

Brandity.ai is an AI-powered brand identity tool that helps users generate complete visual identities quickly and efficiently. The tool utilizes advanced algorithms to adapt to users' brand needs and preferences, maintaining a consistent style across all brand assets. Brandity's AI-driven identity generation ensures coherence and uniqueness in brand identities, from color schemes to art styles, tailored to fit each brand's unique requirements. The tool offers a range of pricing plans suitable for individuals, SMEs, agencies, and high-conversion entities, providing flexibility and scalability in generating logo, scenes, props, and patterns. With Brandity, users can kickstart their brand identity in less than 5 minutes, saving time and ensuring a compelling brand image across various applications.

beb.ai is a web-based application that uses artificial intelligence to generate creative content for brands. It allows users to upload 20-30 photos of their product from different locations and angles, with different facial expressions and emotions. The AI generator will then learn the unique features of the product and generate 72 new photos in 9 different themes, on different backgrounds every week. This content can be used for social media posts, ads, marketing campaigns, dynamic marketing materials, holiday cards, or just for fun.

Prototide is an AI tool designed to streamline design iterations by providing real-time AI insights. It helps elevate design quality and decision-making speed by offering targeted, actionable insights directly in the browser. Users can receive clear feedback, make informed decisions, and enhance their designs with precision. Prototide values user privacy and collects minimal personal information for login and communication purposes. The tool offers a demo with 3 free runs to showcase its workflow enhancement capabilities.

ReRoom AI is an AI-powered interior design tool that allows users to upload a picture of their project and discover 20+ unique design styles. Users can then enjoy photorealistic renders of their project in just seconds. ReRoom AI is perfect for anyone who wants to quickly and easily create beautiful and realistic interior designs.

Sourceful Spring is an AI packaging design generator that helps users create unique packaging designs quickly and for free. The platform allows users to describe their product, select colors and styles, and receive AI-generated packaging designs within minutes. Sourceful Spring aims to help businesses go to market faster, visualize packaging ideas instantly, and accelerate collaboration within teams. The tool also emphasizes sustainability by offering high-quality, sustainable packaging options. Users can explore endless packaging possibilities without any cost, making it a valuable resource for brands looking to stand out.

VisualHUB is an AI-powered design analysis tool that provides instant insights on UI, UX, readability, and more. It offers features like A/B Testing, UI Analysis, UX Analysis, Readability Analysis, Margin and Hierarchy Analysis, and Competition Analysis. Users can upload product images to receive detailed reports with actionable insights and scores. Trusted by founders and designers, VisualHUB helps optimize design variations and identify areas for improvement in products.

Collov AI is a revolutionary interior design platform powered by artificial intelligence. It empowers users to create stunning and personalized designs for their homes, offices, and other spaces. With Collov AI, you can explore a vast library of furniture, décor, and color schemes, and receive real-time feedback from an AI-powered design assistant. Whether you're a professional designer or a homeowner looking to refresh your space, Collov AI makes interior design accessible, affordable, and fun.

Package is a generative AI rendering tool that helps homeowners envision different renovation styles, receive recommended material packages, and streamline procurement with just one click. It offers a wide range of design packages curated by experts, allowing users to customize items to fit their specific style. Package also provides 3D renderings, material management, and personalized choices, making it easy for homeowners to bring their design ideas to life.

Qtandard is an AI website generator that allows users to easily create stunning websites with AI-generated text and images. Users can describe the website they envision, and Qtandard will generate a website ready for customization. With AI assistance, users can craft their website in just one minute, with auto-generated content that can be reviewed and tweaked as needed. Qtandard offers awesome design capabilities, continuous monitoring and care services, and supports over 30 languages. The platform aims to simplify website creation and make the web better.

Let Me Know When is an AI-powered website monitoring tool that offers automated monitoring and competitor analysis. It allows users to track changes on any website, receive price change alerts, monitor competitor websites, detect design changes, and stay updated with content changes. The platform provides insights on SEO performance, product launches, job postings, event tickets, cryptocurrency and stock prices, Google search trends, news updates, customer reviews, and software version tracking. Let Me Know When offers flexible pricing plans and an AI assistant for intelligent insights.

NonprofitAMA is an AI chatbot designed to provide information and resources related to nonprofits. It covers a wide range of topics such as leadership, management, governance, fundraising, marketing, incorporation, fiscal sponsorship, organizational design, strategy, advocacy, and DEI. Users can ask questions and receive responses based on curated, high-quality resources. The chatbot also offers links to additional sources for further exploration. For personalized advice or consultation, users can reach out for more custom assistance.

OpenArt is an AI-powered art platform that offers a free AI image generator and editor. It allows users to create images using pre-built models or by training their own models. The platform provides an intuitive AI drawing tool and editing suite to transform artistic concepts into reality. OpenArt stands out for its boundary-free AI drawing, advanced AI art tools, diverse artistic styles, and the ability to train custom AI models. It caters to both amateur and professional artists, offering high-quality art creation and comprehensive support. Users can experiment with various styles, receive detailed feedback, and collaborate on artistic projects through the platform.

Namecheap is a domain registrar and web hosting company. It offers a wide range of services, including domain registration, web hosting, email hosting, and security services. Namecheap is known for its low prices and its commitment to customer service. The company has been in business since 2000 and has over 10 million customers worldwide.

Moxie is an AI-powered academic research writing companion that assists users in refining arguments, guiding research, and enhancing academic voice. It offers personalized feedback, AI-powered writing assistance, and tools for research design. Unlike AI content generators, Moxie empowers scholars to tackle complex tasks while preserving their critical thinking. The platform provides premium AI models, interactive learning sessions, and a personalized approach to academic writing. Users can streamline research processes, refine arguments, and receive actionable feedback to enhance their academic work.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

A curated list of Generative AI projects, tools, artworks, and models

NeMo Guardrails is an open-source toolkit for easily adding _programmable guardrails_ to LLM-based conversational applications. Guardrails (or "rails" for short) are specific ways of controlling the output of a large language model, such as not talking about politics, responding in a particular way to specific user requests, following a predefined dialog path, using a particular language style, extracting structured data, and more.

Open Data QnA is a Python library that allows users to interact with their PostgreSQL or BigQuery databases in a conversational manner, without needing to write SQL queries. The library leverages Large Language Models (LLMs) to bridge the gap between human language and database queries, enabling users to ask questions in natural language and receive informative responses. It offers features such as conversational querying with multiturn support, table grouping, multi schema/dataset support, SQL generation, query refinement, natural language responses, visualizations, and extensibility. The library is built on a modular design and supports various components like Database Connectors, Vector Stores, and Agents for SQL generation, validation, debugging, descriptions, embeddings, responses, and visualizations.

MSCCL++ is a GPU-driven communication stack for scalable AI applications. It provides a highly efficient and customizable communication stack for distributed GPU applications. MSCCL++ redefines inter-GPU communication interfaces, delivering a highly efficient and customizable communication stack for distributed GPU applications. Its design is specifically tailored to accommodate diverse performance optimization scenarios often encountered in state-of-the-art AI applications. MSCCL++ provides communication abstractions at the lowest level close to hardware and at the highest level close to application API. The lowest level of abstraction is ultra light weight which enables a user to implement logics of data movement for a collective operation such as AllReduce inside a GPU kernel extremely efficiently without worrying about memory ordering of different ops. The modularity of MSCCL++ enables a user to construct the building blocks of MSCCL++ in a high level abstraction in Python and feed them to a CUDA kernel in order to facilitate the user's productivity. MSCCL++ provides fine-grained synchronous and asynchronous 0-copy 1-sided abstracts for communication primitives such as `put()`, `get()`, `signal()`, `flush()`, and `wait()`. The 1-sided abstractions allows a user to asynchronously `put()` their data on the remote GPU as soon as it is ready without requiring the remote side to issue any receive instruction. This enables users to easily implement flexible communication logics, such as overlapping communication with computation, or implementing customized collective communication algorithms without worrying about potential deadlocks. Additionally, the 0-copy capability enables MSCCL++ to directly transfer data between user's buffers without using intermediate internal buffers which saves GPU bandwidth and memory capacity. MSCCL++ provides consistent abstractions regardless of the location of the remote GPU (either on the local node or on a remote node) or the underlying link (either NVLink/xGMI or InfiniBand). This simplifies the code for inter-GPU communication, which is often complex due to memory ordering of GPU/CPU read/writes and therefore, is error-prone.

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 |

MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.

Venom is a high-performance system developed with JavaScript to create a bot for WhatsApp, support for creating any interaction, such as customer service, media sending, sentence recognition based on artificial intelligence and all types of design architecture for WhatsApp.

Lobe Chat is an open-source, modern-design ChatGPT/LLMs UI/Framework. Supports speech-synthesis, multi-modal, and extensible ([function call][docs-functionc-call]) plugin system. One-click **FREE** deployment of your private OpenAI ChatGPT/Claude/Gemini/Groq/Ollama chat application.

Alan AI is a comprehensive AI solution that acts as a 'unified brain' for enterprises, interconnecting applications, APIs, and data sources to streamline workflows. It offers tools like Alan AI Studio for designing dialog scenarios, lightweight SDKs for embedding AI Agents, and a backend powered by advanced AI technologies. With Alan AI, users can create conversational experiences with minimal UI changes, benefit from a serverless environment, receive on-the-fly updates, and access dialog testing and analytics tools. The platform supports various frameworks like JavaScript, React, Angular, Vue, Ember, and Electron, and provides example web apps for different platforms. Users can also explore Alan AI SDKs for iOS, Android, Flutter, Ionic, Apache Cordova, and React Native.

OpenCompass is a one-stop platform for large model evaluation, aiming to provide a fair, open, and reproducible benchmark for large model evaluation. Its main features include: * Comprehensive support for models and datasets: Pre-support for 20+ HuggingFace and API models, a model evaluation scheme of 70+ datasets with about 400,000 questions, comprehensively evaluating the capabilities of the models in five dimensions. * Efficient distributed evaluation: One line command to implement task division and distributed evaluation, completing the full evaluation of billion-scale models in just a few hours. * Diversified evaluation paradigms: Support for zero-shot, few-shot, and chain-of-thought evaluations, combined with standard or dialogue-type prompt templates, to easily stimulate the maximum performance of various models. * Modular design with high extensibility: Want to add new models or datasets, customize an advanced task division strategy, or even support a new cluster management system? Everything about OpenCompass can be easily expanded! * Experiment management and reporting mechanism: Use config files to fully record each experiment, and support real-time reporting of results.

Your design feedback partner offers you constructive feedback from multiple perspectives on your work. Simply upload your screens to receive valuable feedback.

나에게 맞는 직업과 진로 추천받기. 적성에 맞는 진로 상담, 직업추천, 휴먼디자인, Based on Human Design System

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This GPT follows 10 questions from Y Combinator for co-founders to discuss before deciding to work together. Co-founders answer the questions separately and receive unique IDs. To check compatibility, provide two IDs. Co-founder GPT has a long-term memory, so write down your ID for future checks.

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