The Deep Java Library (DJL) is a framework-agnostic Java API for deep learning. It provides a unified interface to popular deep learning frameworks such as TensorFlow, PyTorch, and MXNet. DJL makes it easy to develop deep learning applications in Java, and it can be used for a variety of tasks, including image classification, object detection, natural language processing, and speech recognition.

Groqbook is a streamlit app that quickly generates entire books from a one-line prompt using Llama3 on Groq. It focuses on nonfiction books, generating chapters within seconds by utilizing Llama3-8b and Llama3-70b models. The tool currently uses section titles to create chapter content, with plans to expand to full book context for fiction books. Users can download the book contents in a text file, and the app supports markdown styling with tables and code for an aesthetic book display.

aiarena-web is a website designed for running the aiarena.net infrastructure. It consists of different modules such as core functionality, web API endpoints, frontend templates, and a module for linking users to their Patreon accounts. The website serves as a platform for obtaining new matches, reporting results, featuring match replays, and connecting with Patreon supporters. The project is licensed under GPLv3 in 2019.

Groqnotes is a streamlit app that helps users generate organized lecture notes from transcribed audio using Groq's Whisper API. It utilizes Llama3-8b and Llama3-70b models to structure and create content quickly. The app offers markdown styling for aesthetic notes, allows downloading notes as text or PDF files, and strategically switches between models for speed and quality balance. Users can access the hosted version at groqnotes.streamlit.app or run it locally with streamlit by setting up the Groq API key and installing dependencies.

Topaz-Photo-AI is a software tool designed to enhance and improve the quality of photos using artificial intelligence technology. Users can easily download, install, and run the software to apply various enhancements to their images. The tool provides a user-friendly interface and a range of features to help users enhance their photos with just a few simple steps. With Topaz-Photo-AI, users can achieve professional-level results in photo editing without the need for advanced skills or knowledge.

GenAI Agents is a comprehensive repository for developing and implementing Generative AI (GenAI) agents, ranging from simple conversational bots to complex multi-agent systems. It serves as a valuable resource for learning, building, and sharing GenAI agents, offering tutorials, implementations, and a platform for showcasing innovative agent creations. The repository covers a wide range of agent architectures and applications, providing step-by-step tutorials, ready-to-use implementations, and regular updates on advancements in GenAI technology.

AITranslator is a software tool that utilizes a large language model to translate text from images exported by MTool into a user-friendly graphical interface. Users can start TGW to load the model, open the software, and select the text to be translated. The tool aims to simplify the translation process by leveraging advanced language processing capabilities.

Topaz-Video-AI is a software tool designed to enhance video quality and provide various editing features. Users can utilize this tool to improve the visual appeal of their videos by applying filters, adjusting colors, and enhancing details. The software offers a user-friendly interface and a range of customization options to cater to different editing needs. Despite potential triggers from antivirus programs, Topaz-Video-AI is safe to use and has been tested by numerous users. By following the provided instructions, users can easily download, install, and run the software to enhance their video content.

Tap4 AI Web UI is an open source AI tools directory built by Tap4 AI Tools Directory. The project aims to help everyone build their own AI Tools Directory easily. Users can fork the project, deploy it to Vercel with one click, and update their own AI tools using the data list in the project. The web UI features internationalization, SEO friendliness, dynamic sitemap generation, fast shipping, NEXT 14 with app route, and integration with Supabase serverless database.

Wave Executor is a cutting-edge script executor tailored for Roblox enthusiasts, offering AI integration for seamless script development, ad-free premium features, and 24/7 customer support. It enhances your Roblox gameplay experience by providing a wide range of features to take your gameplay to new heights.

Singulatron is an AI Superplatform that runs on your computer(s) and server(s) without using third party APIs, providing complete control over data and privacy. It offers AI functionality, user management, supports different database backends, collaboration, and mini-apps. It aims to be a desktop app for local usage and a distributed daemon for servers, with a web app frontend client. The tool is stack-based on Electron, Angular, and Go, and currently dual-licensed under AGPL-3.0-or-later and a commercial license.

NVIDIA Generative AI Examples are state-of-the-art examples that are easy to deploy, test, and extend. All examples run on the high performance NVIDIA CUDA-X software stack and NVIDIA GPUs. These examples showcase the capabilities of NVIDIA's Generative AI platform, which includes tools, frameworks, and models for building and deploying generative AI applications.

AI Youtube Shorts Generator is a Python tool that utilizes GPT-4 and Whisper to generate engaging YouTube shorts from long-form videos. It downloads videos, transcribes them, extracts highlights, detects speakers, and crops content vertically for shorts. The tool requires Python 3.7 or higher, FFmpeg, and OpenCV. Users can contribute to the project under the MIT License.

Superplatform is a microservices platform focused on distributed AI management and development. It enables users to self-host AI models, build backendless AI apps, develop microservices-based AI applications, and deploy third-party AI apps easily. The platform supports running open-source AI models privately, building apps leveraging AI models, and utilizing a microservices-based communal backend for diverse projects.

crewAI-examples is a repository containing examples demonstrating the usage of crewAI framework for facilitating collaboration of role-playing AI agents. The examples showcase various ways to automate processes using crewAI. Created by @joaomdmoura.

ConvoForm.com transforms traditional forms into interactive conversational experiences, powered by AI for an enhanced user journey. It offers AI-Powered Form Generation, Real-time Form Editing and Preview, and Customizable Submission Pages. The tech stack includes Next.js for frontend, tRPC for backend, GPT-3.5-Turbo for AI integration, and Socket.io for real-time updates. Local setup requires Node.js, pnpm, Git, PostgreSQL database, Clerk for Authentication, OpenAI key, Redis Database, and Sentry for monitoring. The project is open for contributions and is licensed under the MIT License.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference. It provides a common API to deliver inference solutions on various platforms, including CPU, GPU, NPU, and heterogeneous devices. OpenVINO™ supports pre-trained models from Open Model Zoo and popular frameworks like TensorFlow, PyTorch, and ONNX. Key components of OpenVINO™ include the OpenVINO™ Runtime, plugins for different hardware devices, frontends for reading models from native framework formats, and the OpenVINO Model Converter (OVC) for adjusting models for optimal execution on target devices.

The Deep Java Library (DJL) is a framework-agnostic Java API for deep learning. It provides a unified interface to popular deep learning frameworks such as TensorFlow, PyTorch, and MXNet. DJL makes it easy to develop deep learning applications in Java, and it can be used for a variety of tasks, including image classification, object detection, natural language processing, and speech recognition.

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.

MONAI is a PyTorch-based, open-source framework for deep learning in healthcare imaging. It provides a comprehensive set of tools for medical image analysis, including data preprocessing, model training, and evaluation. MONAI is designed to be flexible and easy to use, making it a valuable resource for researchers and developers in the field of medical imaging.

NNStreamer is a set of Gstreamer plugins that allow Gstreamer developers to adopt neural network models easily and efficiently and neural network developers to manage neural network pipelines and their filters easily and efficiently.

Nitro is a high-efficiency C++ inference engine for edge computing, powering Jan. It is lightweight and embeddable, ideal for product integration. The binary of nitro after zipped is only ~3mb in size with none to minimal dependencies (if you use a GPU need CUDA for example) make it desirable for any edge/server deployment.

The second edition of "PyTorch Practical Tutorial" was completed after 5 years, 4 years, and 2 years. On the basis of the essence of the first edition, rich and detailed deep learning application cases and reasoning deployment frameworks have been added, so that this book can more systematically cover the knowledge involved in deep learning engineers. As the development of artificial intelligence technology continues to emerge, the second edition of "PyTorch Practical Tutorial" is not the end, but the beginning, opening up new technologies, new fields, and new chapters. I hope to continue learning and making progress in artificial intelligence technology with you in the future.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.