The Missing Persons 2024 Antifinance Bill Demonstrations Kenya database is an AI-powered platform designed to track and identify individuals who have gone missing during the ongoing protests. It aims to assist in reuniting families by providing a centralized online resource for all Kenyans. The platform allows for crowdsourced information upload, monitoring disappearances, and tracking unidentified bodies to create a comprehensive database. Key features include a user-friendly interface, AI-powered search, real-time updates, secure handling of data, and detailed reporting.

AppFlowy.IO is an open-source alternative to Notion, providing users with control over their data and customizations. It aims to offer functionality, data security, and cross-platform native experience to individuals, as well as building blocks and collaboration infra services to enterprises and hackers. The tool is built with Flutter and Rust, supporting multiple platforms and emphasizing long-term maintainability. AppFlowy prioritizes data privacy, reliable native experience, and community-driven extensibility, aiming to democratize the creation of complex workplace management tools.

Dwata is a desktop application that allows users to chat with any AI model and gain insights from their data. Chats are organized into threads, similar to Discord, with each thread connecting to a different AI model. Dwata can connect to databases, APIs (such as Stripe), or CSV files and send structured data as prompts when needed. The AI's response will often include SQL or Python code, which can be used to extract the desired insights. Dwata can validate AI-generated SQL to ensure that the tables and columns referenced are correct and can execute queries against the database from within the application. Python code (typically using Pandas) can also be executed from within Dwata, although this feature is still in development. Dwata supports a range of AI models, including OpenAI's GPT-4, GPT-4 Turbo, and GPT-3.5 Turbo; Groq's LLaMA2-70b and Mixtral-8x7b; Phind's Phind-34B and Phind-70B; Anthropic's Claude; and Ollama's Llama 2, Mistral, and Phi-2 Gemma. Dwata can compare chats from different models, allowing users to see the responses of multiple models to the same prompts. Dwata can connect to various data sources, including databases (PostgreSQL, MySQL, MongoDB), SaaS products (Stripe, Shopify), CSV files/folders, and email (IMAP). The desktop application does not collect any private or business data without the user's explicit consent.

The AI Horde is an enterprise-level ML-Ops crowdsourced distributed inference cluster for AI Models. This middleware can support both Image and Text generation. It is infinitely scalable and supports seamless drop-in/drop-out of compute resources. The Public version allows people without a powerful GPU to use Stable Diffusion or Large Language Models like Pygmalion/Llama by relying on spare/idle resources provided by the community and also allows non-python clients, such as games and apps, to use AI-provided generations.

Your Smart Second Brain is a free and open-source Obsidian plugin that serves as your personal assistant, powered by large language models like ChatGPT or Llama2. It can directly access and process your notes, eliminating the need for manual prompt editing, and it can operate completely offline, ensuring your data remains private and secure.

Rakis is a decentralized verifiable AI network in the browser where nodes can accept AI inference requests, run local models, verify results, and arrive at consensus without servers. It is open-source, functional, multi-model, multi-chain, and browser-first, allowing anyone to participate in the network. The project implements an embedding-based consensus mechanism for verifiable inference. Users can run their own node on rakis.ai or use the compiled version hosted on Huggingface. The project is meant for educational purposes and is a work in progress.

The Persian License Plate Recognition (PLPR) system is a state-of-the-art solution designed for detecting and recognizing Persian license plates in images and video streams. Leveraging advanced deep learning models and a user-friendly interface, it ensures reliable performance across different scenarios. The system offers advanced detection using YOLOv5 models, precise recognition of Persian characters, real-time processing capabilities, and a user-friendly GUI. It is well-suited for applications in traffic monitoring, automated vehicle identification, and similar fields. The system's architecture includes modules for resident management, entrance management, and a detailed flowchart explaining the process from system initialization to displaying results in the GUI. Hardware requirements include an Intel Core i5 processor, 8 GB RAM, a dedicated GPU with at least 4 GB VRAM, and an SSD with 20 GB of free space. The system can be installed by cloning the repository and installing required Python packages. Users can customize the video source for processing and run the application to upload and process images or video streams. The system's GUI allows for parameter adjustments to optimize performance, and the Wiki provides in-depth information on the system's architecture and model training.

Recognize is a smart media tagging tool for Nextcloud that automatically categorizes photos and music by recognizing faces, animals, landscapes, food, vehicles, buildings, landmarks, monuments, music genres, and human actions in videos. It uses pre-trained models for object detection, landmark recognition, face comparison, music genre classification, and video classification. The tool ensures privacy by processing images locally without sending data to cloud providers. However, it cannot process end-to-end encrypted files. Recognize is rated positively for ethical AI practices in terms of open-source software, freely available models, and training data transparency, except for music genre recognition due to limited access to training data.

ChainForge is a visual programming environment for battle-testing prompts to LLMs. It is geared towards early-stage, quick-and-dirty exploration of prompts, chat responses, and response quality that goes beyond ad-hoc chatting with individual LLMs. With ChainForge, you can: * Query multiple LLMs at once to test prompt ideas and variations quickly and effectively. * Compare response quality across prompt permutations, across models, and across model settings to choose the best prompt and model for your use case. * Setup evaluation metrics (scoring function) and immediately visualize results across prompts, prompt parameters, models, and model settings. * Hold multiple conversations at once across template parameters and chat models. Template not just prompts, but follow-up chat messages, and inspect and evaluate outputs at each turn of a chat conversation. ChainForge comes with a number of example evaluation flows to give you a sense of what's possible, including 188 example flows generated from benchmarks in OpenAI evals. This is an open beta of Chainforge. We support model providers OpenAI, HuggingFace, Anthropic, Google PaLM2, Azure OpenAI endpoints, and Dalai-hosted models Alpaca and Llama. You can change the exact model and individual model settings. Visualization nodes support numeric and boolean evaluation metrics. ChainForge is built on ReactFlow and Flask.

Digma is a Continuous Feedback platform that provides code-level insights related to performance, errors, and usage during development. It empowers developers to own their code all the way to production, improving code quality and preventing critical issues. Digma integrates with OpenTelemetry traces and metrics to generate insights in the IDE, helping developers analyze code scalability, bottlenecks, errors, and usage patterns.

The Machine Learning for Public Policy Lab is a project-based course focused on solving real-world problems using machine learning in the context of public policy and social good. Students will gain hands-on experience building end-to-end machine learning systems, developing skills in problem formulation, working with messy data, communicating with non-technical stakeholders, model interpretability, and understanding algorithmic bias & disparities. The course covers topics such as project scoping, data acquisition, feature engineering, model evaluation, bias and fairness, and model interpretability. Students will work in small groups on policy projects, with graded components including project proposals, presentations, and final reports.

Nuwa is an AI platform where users pay directly to developers for AI models and agents. Payments are made using cryptocurrencies secured by blockchain. User data and authentications are based on Decentralized Identity (DID). Nuwa aims to reduce friction for users, enhance their daily AI experience, and provide direct monetization for developers. The platform offers an agent-first approach, protocol-powered solutions, and user-aligned services. It includes a Nuwa Client for AI chat with DID-based authentication and cryptocurrency payments, and Nuwa Kit for developers to build and launch AI models and agents into Caps (capabilities). The repository contains various components of the Nuwa Protocol, including Nuwa Improvement Proposals, smart contracts, client agent implementation, development kits, reference implementations of key services, and websites for documentation and landing pages.

LangGraph-learn is a community-driven project focused on mastering LangGraph and other AI-related topics. It provides hands-on examples and resources to help users learn how to create and manage language model workflows using LangGraph and related tools. The project aims to foster a collaborative learning environment for individuals interested in AI and machine learning by offering practical examples and tutorials on building efficient and reusable workflows involving language models.

Mahilo is a flexible framework for creating multi-agent systems that can interact with humans while sharing context internally. It allows developers to set up complex agent networks for various applications, from customer service to emergency response simulations. Agents can communicate with each other and with humans, making the system efficient by handling context from multiple agents and helping humans stay focused on specific problems. The system supports Realtime API for voice interactions, WebSocket-based communication, flexible communication patterns, session management, and easy agent definition.

The 'jobs' repository by comma.ai focuses on solving self-driving cars by building a robotics stack that includes state-of-the-art machine learning models, operating system design, hardware development, and manufacturing. The company aims to deliver constant incremental progress in self-driving technology to users, with a focus on practical solutions rather than hype. Job opportunities at comma.ai include technical challenges, phone screenings, and paid micro-internships, with perks such as chef-prepared meals, on-site gym access, and health insurance. The teams at comma.ai are organized into web, systems, infrastructure, product, design, and electrical engineering, with specific challenges for each team. The repository also offers opportunities for non-job seekers to participate in challenges and win prizes.

AimStar is a free and open-source external cheat for CS2, written in C++. It is available for Windows 8.1+ and features ESP, glow, radar, crosshairs, no flash, bhop, aimbot, triggerbot, language settings, hit sound, and bomb timer. The code is mostly contributed by users and may be messy. The project is for learning purposes only and should not be used for illegal activities.

The Missing Persons 2024 Antifinance Bill Demonstrations Kenya database is an AI-powered platform designed to track and identify individuals who have gone missing during the ongoing protests. It aims to assist in reuniting families by providing a centralized online resource for all Kenyans. The platform allows for crowdsourced information upload, monitoring disappearances, and tracking unidentified bodies to create a comprehensive database. Key features include a user-friendly interface, AI-powered search, real-time updates, secure handling of data, and detailed reporting.

LoLLMs WebUI (Lord of Large Language Multimodal Systems: One tool to rule them all) is a user-friendly interface to access and utilize various LLM (Large Language Models) and other AI models for a wide range of tasks. With over 500 AI expert conditionings across diverse domains and more than 2500 fine tuned models over multiple domains, LoLLMs WebUI provides an immediate resource for any problem, from car repair to coding assistance, legal matters, medical diagnosis, entertainment, and more. The easy-to-use UI with light and dark mode options, integration with GitHub repository, support for different personalities, and features like thumb up/down rating, copy, edit, and remove messages, local database storage, search, export, and delete multiple discussions, make LoLLMs WebUI a powerful and versatile tool.

The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.

MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads.

Mage is an open-source data pipeline tool for transforming and integrating data. It offers an easy developer experience, engineering best practices built-in, and data as a first-class citizen. Mage makes it easy to build, preview, and launch data pipelines, and provides observability and scaling capabilities. It supports data integrations, streaming pipelines, and dbt integration.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.

Airbyte is an open-source data integration platform that makes it easy to move data from any source to any destination. With Airbyte, you can build and manage data pipelines without writing any code. Airbyte provides a library of pre-built connectors that make it easy to connect to popular data sources and destinations. You can also create your own connectors using Airbyte's no-code Connector Builder or low-code CDK. Airbyte is used by data engineers and analysts at companies of all sizes to build and manage their data pipelines.

Labelbox is a data-centric AI platform for enterprises to develop, optimize, and use AI to solve problems and power new products and services. Enterprises use Labelbox to curate data, generate high-quality human feedback data for computer vision and LLMs, evaluate model performance, and automate tasks by combining AI and human-centric workflows. The academic & research community uses Labelbox for cutting-edge AI research.