Best AI tools for< Concept Cyberpunk Worlds >

AI Art Generator is a website that allows users to create AI-generated art. Users can choose from a variety of styles, including fantasy, anime, and cyberpunk. The website also offers a variety of tools to help users create their own unique artwork. AI Art Generator is a great way to explore your creativity and create beautiful, unique artwork.

Neural Concept is an end-to-end platform for high-performance engineering teams, powered by a leading proprietary 3D AI core. It accelerates product development and innovation with industry-leading 3D deep-learning and simulation capabilities. The platform works with various CAE and CAD softwares, offering 3D visual feedback, collaborative environment, and LLM guidance to boost engineers' impact. Neural Concept is used by engineering companies to design and deliver better products faster, bringing AI-designed products to market up to 75% faster.

Prelaunch.com is a product validation platform that helps creators test market demand before launching a product. It provides tools for concept validation, price validation, positioning testing, and idea validation. Users can gather early customer feedback, define pricing, identify target audiences, and make data-driven decisions to either launch confidently or pivot their product idea. The platform offers AI market research assistance, co-creation opportunities, and analytics to optimize product launches.

Creators is a website that offers a service to create pitch decks for startups and growing businesses. They specialize in creating visually stunning and impactful pitch decks that tell the story of the business and capture the attention of investors. They use a data-driven approach to storytelling, incorporating relevant data and analytics to back up the idea and prove its potential to investors. They also use artificial intelligence to identify the most compelling way to present the information, ensuring that the pitch deck is not just informative, but also engaging. Creators has a team of expert designers who excel at transforming complex ideas into clear, understandable visuals that are both stunning and highly effective in communicating the message to potential investors.

Heuristica is an AI-powered concept mapping tool that uses a mind map-like UI to dive deep into a subject by simply pressing buttons. Concept maps are a visual learning tool that makes acquiring, visualizing, and organizing knowledge easy. Heuristica is used by thousands of industry professionals, business executives, researchers, and students.

Draw3D is an online tool that allows users to transform their sketches into photorealistic images. It is a powerful tool that can be used to create realistic images of anything from landscapes to portraits. Draw3D is easy to use and can be used by anyone, regardless of their artistic ability. Simply upload a sketch and Draw3D will automatically convert it into a photorealistic image.

Storyboarder.ai is a powerful AI-powered tool designed to streamline the storyboarding process for filmmakers. It offers advanced features such as AI-powered animatic and video creation, screenplay writing with AI, image-to-image upload, and more. The platform aims to enhance communication of artistic visions with crew members and clients by automating the generation of storyboards, shot lists, and screenplays, ultimately saving valuable time and ensuring effective collaboration throughout the project.

Censored AI is an AI-powered application that allows users to bring their dream artwork to life with a state-of-the-art generator. It offers a range of styles including anime, comics, realistic designs, and 3D creations. Users can create stunning pieces tailored to their vision for just $2 a month. The application leverages a powerful AI engine to amplify creativity and unlock limitless possibilities. With features like Anime & Comic Styles, Realistic Generations, Toon & T-Shirt Designs, and more, Censored AI provides a platform for users to unleash their imagination and create epic artwork.

Story-boards.ai is an AI-driven platform that revolutionizes storyboarding for visual storytellers, including filmmakers, ad creators, and graphic novelists. It empowers users to transform written scripts into dynamic visual storyboards, maintain character consistency, and speed up the pre-production process with AI-enhanced storyboarding. The platform offers tailored storyboards, custom camera angles, character consistency, and a streamlined workflow to elevate narratives and unlock new realms of possibility in visual storytelling.

Bibit AI is a real estate marketing AI designed to enhance the efficiency and effectiveness of real estate marketing and sales. It can help create listings, descriptions, and property content, and offers a host of other features. Bibit AI is the world's first AI for Real Estate. We are transforming the real estate industry by boosting efficiency and simplifying tasks like listing creation and content generation.

DecodeAI is an experimental concept for an automatic blog about AI, generated by AI and curated by human. The blog mainly focuses on AI-related GitHub open-source repositories but is not limited to that. It features tools like Cody, an AI coding assistant, Jan, an open-source offline AI desktop tool, and Open Interpreter, which allows language models to execute code locally. DecodeAI aims to provide valuable insights and resources for developers interested in AI technologies.

FutureGPT is an AI tool that leverages the power of GPT-4 to provide advanced predictive capabilities. Users can enhance their outcomes by utilizing paid predictions through this application. By enabling JavaScript, users can access the predictive features and settings to improve their decision-making processes.

Artifactory is an AI-powered game asset generation tool that helps you create concepts for characters, icons, and backgrounds in seconds. With Artifactory, you can describe your task in text and generate images instantly. You can also use other images as references and train the model according to your style. Artifactory is easy to use and affordable, making it a great option for game developers of all levels.

Epipheo AI is a powerful Gen AI tool that effortlessly generates professional explainer videos. With its intuitive interface and advanced algorithms, users can create engaging videos in minutes. The tool streamlines the video creation process by automating script generation, storyboard creation, and animation. Users have full control over customization options, including visual styles, branding, voiceovers, and music. Epipheo AI accelerates concept development, enhances video quality, and enables rapid iteration for efficient video production.

Koolio.ai is an AI-powered storytelling platform that helps you create engaging and personalized stories. With Koolio.ai, you can easily generate story ideas, develop characters, and write compelling narratives. Whether you're a professional writer, a student, or just someone who loves to tell stories, Koolio.ai can help you take your storytelling to the next level.

ImagePrompt.org is an AI-driven platform that empowers users to create unique and personalized images through the use of image prompts. By providing tools and guidance for crafting descriptive prompts, ImagePrompt.org enables users to unleash their creativity and bring their ideas to life through AI-generated artwork. The platform offers a seamless experience for generating stunning visuals and extracting precise image prompts, fueling the creative process and optimizing design efficiency with AI-powered precision.

MagicBrief is an AI-powered marketing tool that empowers your marketing team with superhuman capabilities. It offers features such as ad inspiration, creative analytics, ad search engine, brand tracking, creative reporting automation, and AI-powered creative sorting. With MagicBrief, you can browse and save top-performing ads, track competitor activity, automate reporting, and make faster creative decisions based on data-driven insights.

AI Art Generator is an online platform that leverages state-of-the-art Stable Diffusion technology to quickly turn users' imaginations into amazing artistic creations with just simple text prompts. Users can create unique images by providing text descriptions, and the AI model generates original artworks in seconds. The platform allows anyone to easily create stunning AI-generated artworks without needing artistic skills or training. AI Art Generator aims to provide a seamless and creative experience for users to explore the future of art through advanced technology.

Vizcom is an AI tool that allows users to transform sketches into renders and 3D models in seconds. It offers features such as sketching, rendering, 3D modeling, custom palettes creation, visual communication, and design iteration. Vizcom provides a seamless design process, from sketch to render to 3D printing, with a focus on security and data protection.

Off/Script is a community-led product creation platform that empowers users to bring their product ideas to life without spending any money. The platform provides users with access to an AI-powered product creation studio, a community of design experts, and a marketplace to sell their products. Off/Script handles all product creation and logistics requirements, so users can focus on what they do best: designing and creating innovative products.

Stable Diffusion is a text-to-image AI model that can generate realistic images from a given text prompt. It is a powerful tool that can be used for a variety of creative and practical applications, such as generating concept art, creating illustrations, and designing products. Stable Diffusion is also a great tool for learning about AI and machine learning. This repository contains a collection of tutorials and resources on how to use Stable Diffusion.

AlwaysReddy is a simple LLM assistant with no UI that you interact with entirely using hotkeys. It can easily read from or write to your clipboard, and voice chat with you via TTS and STT. Here are some of the things you can use AlwaysReddy for: - Explain a new concept to AlwaysReddy and have it save the concept (in roughly your words) into a note. - Ask AlwaysReddy "What is X called?" when you know how to roughly describe something but can't remember what it is called. - Have AlwaysReddy proofread the text in your clipboard before you send it. - Ask AlwaysReddy "From the comments in my clipboard, what do the r/LocalLLaMA users think of X?" - Quickly list what you have done today and get AlwaysReddy to write a journal entry to your clipboard before you shutdown the computer for the day.

This project provides a proof of concept for deploying a scalable, serverless LLM Generative AI inference engine on AWS Lambda. It leverages the llama.cpp project to enable the usage of more accessible CPU and RAM configurations instead of limited and expensive GPU capabilities. By deploying a container with the llama.cpp converted models onto AWS Lambda, this project offers the advantages of scale, minimizing cost, and maximizing compute availability. The project includes AWS CDK code to create and deploy a Lambda function leveraging your model of choice, with a FastAPI frontend accessible from a Lambda URL. It is important to note that you will need ggml quantized versions of your model and model sizes under 6GB, as your inference RAM requirements cannot exceed 9GB or your Lambda function will fail.

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.

Dream Textures is a tool integrated into Blender that allows users to create textures, concept art, background assets, and more using simple text prompts. It offers features like seamless texture creation, texture projection for entire scenes, restyling animations, and running models on the user's machine for faster iteration. The tool supports CUDA and Apple Silicon GPUs, with over 4GB of VRAM recommended. Users can troubleshoot issues by checking Blender's system console or seeking help from the community on Discord.

FluidDB is a research repository focusing on the concept of a fluid database that dynamically updates its schema based on ingested data. It enables the creation of personalized AI agents with features like adaptive schema, flexible querying, and versatile data input. The tool allows for storing unstructured data in a structured form and supports natural language queries. It aims to revolutionize database management by providing a dynamic and intuitive approach to data storage and retrieval.

Praison AI is a low-code, centralised framework that simplifies the creation and orchestration of multi-agent systems for various LLM applications. It emphasizes ease of use, customization, and human-agent interaction. The tool leverages AutoGen and CrewAI frameworks to facilitate the development of AI-generated scripts and movie concepts. Users can easily create, run, test, and deploy agents for scriptwriting and movie concept development. Praison AI also provides options for full automatic mode and integration with OpenAI models for enhanced AI capabilities.

This repository contains sample code demonstrating various use cases leveraging Amazon Bedrock and Generative AI. Each sample is a separate project with its own directory, and includes a basic Streamlit frontend to help users quickly set up a proof of concept.

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 |

FuseMedML is a Python framework designed to accelerate machine learning-based discovery in the medical field by promoting code reuse. It provides a flexible design concept where data is stored in a nested dictionary, allowing easy handling of multi-modality information. The framework includes components for creating custom models, loss functions, metrics, and data processing operators. Additionally, FuseMedML offers 'batteries included' key components such as fuse.data for data processing, fuse.eval for model evaluation, and fuse.dl for reusable deep learning components. It supports PyTorch and PyTorch Lightning libraries and encourages the creation of domain extensions for specific medical domains.

Call Center AI is an AI-powered call center solution that leverages Azure and OpenAI GPT. It is a proof of concept demonstrating the integration of Azure Communication Services, Azure Cognitive Services, and Azure OpenAI to build an automated call center solution. The project showcases features like accessing claims on a public website, customer conversation history, language change during conversation, bot interaction via phone number, multiple voice tones, lexicon understanding, todo list creation, customizable prompts, content filtering, GPT-4 Turbo for customer requests, specific data schema for claims, documentation database access, SMS report sending, conversation resumption, and more. The system architecture includes components like RAG AI Search, SMS gateway, call gateway, moderation, Cosmos DB, event broker, GPT-4 Turbo, Redis cache, translation service, and more. The tool can be deployed remotely using GitHub Actions and locally with prerequisites like Azure environment setup, configuration file creation, and resource hosting. Advanced usage includes custom training data with AI Search, prompt customization, language customization, moderation level customization, claim data schema customization, OpenAI compatible model usage for the LLM, and Twilio integration for SMS.

Woodpecker is a tool designed to correct hallucinations in Multimodal Large Language Models (MLLMs) by introducing a training-free method that picks out and corrects inconsistencies between generated text and image content. It consists of five stages: key concept extraction, question formulation, visual knowledge validation, visual claim generation, and hallucination correction. Woodpecker can be easily integrated with different MLLMs and provides interpretable results by accessing intermediate outputs of the stages. The tool has shown significant improvements in accuracy over baseline models like MiniGPT-4 and mPLUG-Owl.

The Enterprise Azure OpenAI Hub is a comprehensive repository designed to guide users through the world of Generative AI on the Azure platform. It offers a structured learning experience to accelerate the transition from concept to production in an Enterprise context. The hub empowers users to explore various use cases with Azure services, ensuring security and compliance. It provides real-world examples and playbooks for practical insights into solving complex problems and developing cutting-edge AI solutions. The repository also serves as a library of proven patterns, aligning with industry standards and promoting best practices for secure and compliant AI development.

The Shire is an AI Coding Agent Language that facilitates communication between an LLM and control IDE for automated programming. It offers a straightforward approach to creating AI agents tailored to individual IDEs, enabling users to build customized AI-driven development environments. The concept of Shire originated from AutoDev, a subproject of UnitMesh, with DevIns as its precursor. The tool provides documentation and resources for implementing AI in software engineering projects.

ModelBench is a tool for running safety benchmarks against AI models and generating detailed reports. It is part of the MLCommons project and is designed as a proof of concept to aggregate measures, relate them to specific harms, create benchmarks, and produce reports. The tool requires LlamaGuard for evaluating responses and a TogetherAI account for running benchmarks. Users can install ModelBench from GitHub or PyPI, run tests using Poetry, and create benchmarks by providing necessary API keys. The tool generates static HTML pages displaying benchmark scores and allows users to dump raw scores and manage cache for faster runs. ModelBench is aimed at enabling users to test their own models and create tests and benchmarks.

DuoAttention is a framework designed to optimize long-context large language models (LLMs) by reducing memory and latency during inference without compromising their long-context abilities. It introduces a concept of Retrieval Heads and Streaming Heads to efficiently manage attention across tokens. By applying a full Key and Value (KV) cache to retrieval heads and a lightweight, constant-length KV cache to streaming heads, DuoAttention achieves significant reductions in memory usage and decoding time for LLMs. The framework uses an optimization-based algorithm with synthetic data to accurately identify retrieval heads, enabling efficient inference with minimal accuracy loss compared to full attention. DuoAttention also supports quantization techniques for further memory optimization, allowing for decoding of up to 3.3 million tokens on a single GPU.

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.

Purple Llama is an umbrella project that aims to provide tools and evaluations to support responsible development and usage of generative AI models. It encompasses components for cybersecurity and input/output safeguards, with plans to expand in the future. The project emphasizes a collaborative approach, borrowing the concept of purple teaming from cybersecurity, to address potential risks and challenges posed by generative AI. Components within Purple Llama are licensed permissively to foster community collaboration and standardize the development of trust and safety tools for generative AI.

The DALM (Domain Adapted Language Modeling) toolkit is designed to unify general LLMs with vector stores to ground AI systems in efficient, factual domains. It provides developers with tools to build on top of Arcee's open source Domain Pretrained LLMs, enabling organizations to deeply tailor AI according to their unique intellectual property and worldview. The toolkit contains code for fine-tuning a fully differential Retrieval Augmented Generation (RAG-end2end) architecture, incorporating in-batch negative concept alongside RAG's marginalization for efficiency. It includes training scripts for both retriever and generator models, evaluation scripts, data processing codes, and synthetic data generation code.

Call Center AI is an AI-powered call center solution leveraging Azure and OpenAI GPT. It allows for AI agent-initiated phone calls or direct calls to the bot from a configured phone number. The bot is customizable for various industries like insurance, IT support, and customer service, with features such as accessing claim information, conversation history, language change, SMS sending, and more. The project is a proof of concept showcasing the integration of Azure Communication Services, Azure Cognitive Services, and Azure OpenAI for an automated call center solution.

Cyberpunk is a subgenre of science fiction in a dystopian futuristic setting that tends to focus on a "combination of lowlife and high tech", featuring futuristic technological and scientific achievements, such as artificial intelligence and cyberware.

Neo-Tokyo avatar designer

Assistant focused on teaching concepts, evaluating comprehension, and recommending subsequent topics. USE WITH VOICE.

I develop ideas into concepts and plan projects.

A facilitator for understanding concepts using a simplified Concept Attainment Method.

Generates fantasy and sci-fi concept art and descriptions.

I create variations on your image themes.

Plan your next renovation project by following a collaborative, step by step, process that provides you with a downloadable Concept Plan

Friendly GPT for applying book concepts practically

A scholarly guide to Whitehead's early work in 'The Concept of Nature'.

Guides through C++ concepts with interactive clarification.

Upload an avatar and indicate the costume concept to design the movie character costume concept and set different angles for reference.

这只是一个哲学和思想概念的游戏性质的探索工具：将任意输入的词汇、概念或场景进行深度分析，从多个学术领域提炼与之相关的哲学术语。This is just a game like exploration tool for philosophical and intellectual concepts: conducting in-depth analysis of vocabulary, extracting philosophical terms related to it from multiple academic fields.联系vx：[email protected]

🧪 Concept expert 👨‍🔬

Exhibition concept Design image Generator

Formal design concept recorder, responds with '已记录', and provides brief summaries.

I will explain any concept in calculus in a fun way!

Generate complete song concept, with story, theme, mood, lyrics, key, chords, and instrument suggestions.

Explor any math concept interactively to gain an understanding. Just type the topic!

Expertly Crafting Your GPT From Concept to Masterpiece