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Announcing the second cohort, delivering value to projects, and driving a new frontier.
We are excited to welcome 11 open source AI projects to the 2024 GitHub Accelerator.
It’s clear that AI innovation is not just thriving—it’s accelerating at a breathtaking pace across the globe and in the open. Our commitment to funding open source developers is stronger than ever as they forge the future and make a global impact.
The fierce competition for a seat in the GitHub Accelerator is a testament to the exceptional quality and determination of work by developers worldwide. Throughout the selection process, we evaluated projects based on their potential to catalyze new careers, impact the broader community, enhance security, and improve the productivity and happiness of developers building with open source AI.
The applications showcased the diverse set of open source projects on GitHub, including frameworks for ML and AI; biology, and disease discovery; tools for model training and fine tuning, simulation, deployment, and full productionized systems; multi-modal and 3D AI capabilities; and emerging interfaces and devices from wearables to AI-powered robotics, spanning languages like Rust, Python, PHP, Ruby, and JavaScript.
These projects, developers, and companies represent the bedrock for innovation—where open source AI leads the way.
We are excited to announce the next cohort of GitHub Accelerator.
Founded by Australian brothers, Daniel and Michael Han, unsloth’s goal is to make custom AI models more accessible. unsloth fine-tunes open source models 2-5x faster with 70% less memory than its competitors, utilizing emerging techniques and capabilities to make models more performant with maintained accuracy.
Founder, Alex Combessie, CEO, and machine learning R&D engineer, Weixuan XIAO, have built an open source library for testing and evaluating large language models (LLMs). Giskard raises the bar for open source AI model quality, advancing overall adoption, research, transparency, and accountability. Designed for data scientists and developers, Giskard can help ensure the quality, security, and compliance of its customers’ AI models.
Diego Marcos, co-creator and maintainer, began developing A-Frame as a framework to make AR/VR and 3D content development accessible to anyone in web browsers. Now focusing on the integration of AI workflows like 3D Gaussian Splatting and generative AI for images and environments, A-Frame has enabled tens of thousands of developers worldwide. The project stands for its commitment to accessibility, community, and availability of resources.
Roboticist Steve Macenski is a pioneer in the Robot Operating System (ROS) navigation framework. Today, Nav2 is used in production worldwide and is the most deployed autonomous mobile robotics (AMR) navigation solution, trusted by more than 100 companies including NVIDIA, Dexory, Polymath Robotics, Stereolabs, and more. Nav2 makes it easy to reliably and efficiently deploy robotics technologies so that users can focus on building their product applications.
Founder Tim Baek, based in Canada, wanted to build the best user interface for AI and LLMs to provide opportunities for individuals with limited to no internet access to leverage AI technology and its benefits. OpenWebUI is powered by a web interface that can run LLMs locally making LLMs and AI more secure and private. The project looks to grow both its community of contributors, as well as the project’s reach and impact in communities around the world.
Founder Namee Oberst is on her second career after a first in law. Together with CEO, Darren Oberst, and Stefan Bachhofner, recognizing the privacy and sensitivity concerns many industries face, Namee sought to build safe and secure LLM AI Agents and Retrieval Augmented Generation (RAG) models for financial and legal institutions. LLMWare provides a comprehensive set of tools that anyone can use—from a beginner to the most sophisticated AI developer—to rapidly build industrial-grade, knowledge-based enterprise LLM applications.
Michael Vandi, founder and CEO, and Spatika, founding engineer, built an LLM email agent to respond to emails during a Masters at Carnegie Mellon University (CMU). After some learning, they realized making LLMs accessible with lower GPU needs could benefit more developers and be easier for all. Today, LangDrive serves as a simple framework to train and deploy production-grade fine-tuned language models all via an API and configuration files. This will improve the maintainability of codebases by abstracting the finetuning process and reducing the number of lines for finetuning from hundreds of lines to just 10 lines.
Austria-based Andreas Happe, former security engineer, and PenTester turned PhD, Jurgen Cito, want to help ethical hackers and security professionals leverage LLMs to make the world a safer place. What started as a research project has now resulted in an autonomous hacking partner with human-in-the-loop infrastructure, a web and API testing platform, and an active directory security management platform.
UK-based open source advocate Alicia Sykes is a former British Army reservist and previous Oxford intern. Her mission is to make the internet more secure with AI-powered security insights based on open data from any website or server. She built Web-Check to democratize security by making it easier for developers to get a complete view of a website, infrastructure, and server.
Cofounders Akshay Agrawal and Myles Scolnick set out to fix all the issues that exist in using notebooks for data science and machine learning. A next-generation Python notebook for AI and machine learning, marimo’s objective is to provide a reproducible, maintainable, and productionizable notebook for AI/ML developers. Today, marimo provides a production-ready notebook that can be deployed as an interactive web app, executed as a script, and versioned with Git.
Brazil-based founder, Vinicious Mesel, started working part-time on Talkd.ai to build a unified LLM Chat API that provides an abstraction layer for multiple LLMs and contexts. A first for the Brazilian open source community, the Unified API will enable the LLM to always have and manage context to preprocess the input and generate the prompt from memory or context. Its goal is to facilitate and disseminate the use of the RAG technique in LLMs.
GitHub will surround each project with resources, community, and expertise to help each maintainer rapidly advance toward their goals. Projects will receive a variety of support totaling nearly $400,000 in value: $40,000 in total non-dilutive sponsorship funding via GitHub Sponsors, up to $350,000 in Microsoft and technology benefits through the Microsoft for Startups Founders Hub including Azure credits to access leading AI models through Azure where eligible, access to credits and resources from Open AI, free Copilot and other GitHub products, and connection to GitHub Fund and M12, Microsoft’s Venture Fund.
The cohort will also receive industry-leading insights and executive engagement; explore managing the complexities of expenses within AI; and dive into complex topics like ethical, security, and legal considerations. Stay tuned as the projects progress and showcase their impact on the world.
You can Star or follow each project on GitHub, share with other developers, or consider sponsoring or investing in a project. If you would like to keep updated on the GitHub Accelerator, selected projects, or upcoming announcements, please sign up for updates here.
GitHub is on a mission to enable a world where 1 billion individuals call themselves developers. GitHub Accelerator is one of many possible ways to support open source—but that impact is really made when everyone supports the technology they rely on. We want to ensure that open source thrives, developers have the choice to contribute full-time to the projects they care about most, and those depending on open source benefit from the innovation and sustainability. Together, we can invest, build, and nurture more open source categories, projects, and people.
Let’s keep building!
