Open Source Software Projects

Today the UK's AI Safety Institute is open sourcing our safety evaluations platform. We call it "Inspect". Inspect is a software library which enables testers to assess specific capabilities of individual models. Released through an open source licence, it is now freely available for the AI community to use. As a team, we are big believers in the power of open source software - open source software can enable more people to contribute, counteract centralisation of power, improve transparency & reproducibility, give end users more control over their tools and reduce costs for all. However 'open' vs 'closed' is a complex topic. Large corporations can use 'open' as a business tactic to catch up and compete (e.g. Android vs iOS), and often something important will remain proprietary. See: https://lnkd.in/eWgtjKMN Within the AI space there are some remarkable efforts to drive forward openness - consider DeepMind's AlphaFold work or Meta's OpenCatalyst project. I am personally very attracted to projects that attempt to truly open up the full process of training AI models, for example GPT-NeoX, OLMo or Pythia which all have publicly available training data and OSI-licensed training and evaluation code and model weights. these projects are truly open source vs just open weight - you can see the data the model is trained on etc. To date these projects have mostly been developed by non-profits like EleutherAI and Allen Institute for AI (AI2). I'm not sure how common it is for governments to ship open source software, but I'm glad that the UK AI Safety Institute is taking this step. I'd like to especially thank JJ Allaire the legendary creator of ColdFusion who joined AISI and spearheaded this project. Thank you JJ! One of the structural challenges in AI is the need for coordination across borders and institutions. I believe academia, start-ups, large companies, government and civil society to all play a role, and open source can be a mechanism to coordinate more broadly. It may be an inconvenient truth, but open source software is currently one of the ways that America and China 'work together' on AI research - perhaps this points at another mechanism for international collaboration over safety https://lnkd.in/eYXDd-wy. This work is a continuation of the work Rishi Sunak and Michelle Donelan MP kicked off with the AI Safety Summit which brought together countries, academia, civil society and the private sector to coordinate around tackling risks from AI so we can enjoy the benefits. More details and github repo here https://lnkd.in/eXdDqcAt

After years of advising companies on open source, I kept noticing the same thing: everyone measures "OSS health" differently, and most either fall back to vanity metrics, stars and forks, or don't know what else to measure. And even if they measure, they don't know what needs to be done to improve them.                                                                        So I wrote down the 42 signals I actually look at, along with concrete recommendations for improving them.                                 Across 5 dimensions: Contributors, Activity, Responsiveness, Documentation, Security. Each scored as a percentile against ~1,600 calibrated peer repos in the same star bracket. So a 200-star project isn't compared against Kubernetes.                                                                       Every signal carries a stable reference ID (CTR-2, SEC-6, …) you can cite in a PR title, roadmap doc, or quarterly review.           The real value comes after the score: every weak signal generates a concrete recommendation: "add a CODEOWNERS file," "enable Dependabot," "speed up first-response time." This means improving your score isn't a mystery; it's a checklist. Fix one item, re-run, and watch the percentile move. Standing on the shoulders of two upstream projects worth knowing on their own:                              → CHAOSS: the open-source metrics framework (chaoss.community) → OpenSSF Scorecard: security checks (scorecard.dev)                                          Built with Claude Code, AI-assisted but human-reviewed. Open source. No sign-up wall.                                                                        📖 Read: https://lnkd.in/g-xbVxk5                      🔗 Try: https://lnkd.in/gdaMnJcE Try running it on your project and share feedback on what else you'd like to see.                                                                        #OpenSource #DevTools #CHAOSS #OpenSSF #OpenSourceHealth #SupplyChainSecurity   

🔬 𝐏𝐚𝐜𝐤𝐚𝐠𝐞 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: an OSS project by the OpenSSF to detect malicious open source packages using static and dynamic analysis. The project looks for behaviors that indicate malicious software: * What files do they access? * What addresses do they connect to? * What commands do they run? Packages are ran in a sandbox using gVisor, which allows it to capture strace data (how is the package interacting with the system) and packet data (network connections could be used to leak sensitive data or allow remote access). The project also tracks changes in how packages behave over time, to identify when previously safe software begins acting suspiciously. They’re currently scanning NPM, PyPI, and RubyGems, and the resulting data is stored in a public BigQuery dataset (linked in the README).

Just took a huge leap of faith and open-sourced our codebase! 🚀 It's been a wild ride, and I want to share why we made this decision. Three years ago, we were struggling to gain traction in the crowded access gateway space. Our tool was the #1 product by far, but adoption was slow. We knew we had to do something drastic. That's when it hit us – what if we embraced radical transparency? We spent months debating, planning, and frankly, sweating over the implications. But last week, we finally pulled the last trigger. It started with a free SaaS plan, then free self-hosted, free open-binary, and now, we're also open-source! Here's why we believe this is a game-changer: • Community-driven innovation: By opening our codebase, we're tapping into the collective genius of developers worldwide. The improvements and new features that have already poured in are mind-blowing! 🤯 • Trust and credibility: In an era of data breaches and privacy concerns, showing our cards builds instant trust. Customers can see exactly what they're getting. • Faster bug fixes: More eyes on the code mean quicker identification and resolution of issues. Our response time has already improved by 40%! • Talent attraction: Top developers want to work on exciting, open projects. • Ecosystem growth: Third-party integrations and plugins are flourishing, expanding our tool's capabilities beyond what we ever imagined. Of course, it hasn't all been smooth sailing. We've had to adapt our business model, breakdown features and paywall our unique value props. But the energy and momentum we've gained far outweigh the challenges. And the surprising outcome: the features in the open-source package beat enterprise plans of all competitors. To my fellow tech leaders: consider the power of openness. It's scary, yes. But the potential for growth and innovation is enormous. Have you experimented with open-sourcing in your company? What were your experiences? Let's discuss in the comments!

How Do Open-Source Projects Transform Embedded Systems Development? In the intricate world of embedded systems, open-source projects are not just tools; they're the foundation for tomorrow's innovations. These projects empower developers, fuel technological advancements, and democratize access to technology. 🔹 Operating Systems & Frameworks - Linux Kernel is the stable and versatile core for a wide range of devices, from desktops to embedded systems. - FreeRTOS is a real-time operating system for microcontrollers, providing a lightweight, efficient kernel with a focus on simplicity and ease of use. - Zephyr Project offers a scalable real-time operating system for connected, resource-constrained devices, emphasizing security and modularity. - Yocto Project enables the creation of custom Linux distributions for embedded devices, optimizing customization. - Raspberry Pi OS supports educational and hobbyist projects with a vast community and comprehensive resources. 🔹 Development Platforms & Tools - Arduino simplifies prototyping and learning with its user-friendly platform, welcoming hobbyists and experts. - Espressif IDF (IoT Development Framework) enables advanced applications on ESP32 and ESP8266 SoCs, offering a comprehensive set of tools and libraries for high-performance wireless solutions, pushing the boundaries of IoT development. - OpenWrt revolutionizes networking projects with its open-source router firmware, offering unparalleled flexibility and control over network devices. - Eclipse offers a versatile IDE for diverse programming needs, preferred by developers worldwide. - PlatformIO is a cross-platform IoT development ecosystem that simplifies the process of programming and integrating microcontroller boards, supporting numerous platforms and frameworks. 🔹 Machine Learning & IoT - TensorFlow Lite and EdgeX Foundry enhance devices with smart decision-making and seamless IoT integration, driving forward the edge computing revolution. - OpenCV: Essential for computer vision projects, enabling powerful image processing and analysis capabilities on embedded devices. 🔹 Programming Languages & Scripting - Rust offers memory safety without a garbage collector, revolutionizing system-level programming with its focus on safety and performance. - MicroPython brings the simplicity and power of Python to microcontrollers, making programming accessible and fun for developers of all skill levels. 🔹 Hardware Platforms BeagleBoard, Adafruit Feather, and Pine64 champion open-source hardware, inspiring creators to explore and innovate Are you familiar with all of these open-source projects? Which ones have you used in your own embedded systems projects, and how have they influenced your work? 📢 Exciting Announcement! I've created a Telegram channel to share more interesting insights with students and professionals looking to scale their skills. Join us at https://lnkd.in/e5tSAtAN #embeddedSystems #OpenSource #IOT

Where can I find open-source opportunities in bioinformatics? A curated list of paid and unpaid open-source opportunities, projects, and resources for bioinformatics beginners to gain experience, build portfolios and grow in the field. 💰 Paid Programs 🔸Outreachy - $7,000 for 12 weeks. Focused on open source projects and underrepresented groups in tech. 🔗 https://www.outreachy.org/ 🔸Google Summer of Code (GSoC) - Great for students and beginners in coding. Paid stipends, flexible projects. 🔗 https://lnkd.in/dMWHSG-5 🔸Linux Foundation Mentorship - Year-round projects, varied stipends, focused on real-world open source contributions. 🔗 https://lnkd.in/d-cQ-TBu 🔸MLH Fellowship - 12 weeks, $5,000 stipend, mentorship + project work. 🔗 https://fellowship.mlh.io ⸻ 🌍 Unpaid Communities where you can contribute 🔹Snakemake - reproducible workflow management. 🔗 https://lnkd.in/dGnaCvYe Contribute: https://lnkd.in/dkj-mcYz 🔹rOpenSci - R packages for open science. 🔗 https://ropensci.org/ Contribute: https://lnkd.in/d9ueng-7 🔹Open Bioinformatics Foundation (OBF) - umbrella org for projects like BioRuby & BioSQL. 🔗 https://www.open-bio.org/ 🔹Biopython - Python tools for sequence + structural biology. 🔗 https://biopython.org/ Contribute: https://lnkd.in/daV2UwhX 🔹Galaxy Project - workflow platform for life science research. 🔗 https://galaxyproject.org/ Contribute: https://lnkd.in/dGts_YtT 🔹Bioconductor - R-based ecosystem for bioinformatics. 🔗 https://lnkd.in/dRYcDCuc 🔹Jupyter - interactive notebooks powering data science. 🔗 https://jupyter.org/ Contribute: https://lnkd.in/dkaecJzP 🔹Arvados - large-scale genomic data management platform. 🔗 https://arvados.org/ Contribute: https://lnkd.in/djyefP84 For guides, timelines for paid open-source opportunities and more resources on how to actually contribute to each, check/ star ⭐️ this repo: https://lnkd.in/dXy-STEx

Many of us face the challenge of selecting open source projects for long-term use. This could involve choosing dependencies for your own open source project, or simply selecting software you plan to run and rely on over time. After experiencing multiple failures, disappointments with projects that turned proprietary, or even the complete disappearance of some repositories, I decided to compile a list of parameters, indicators, and signals that might help identify solid, sustainable open source projects, as well as warning signs that could indicate potential risks. 📖 https://lnkd.in/ehBKuh7T #opensource #freesoftware #foss #floss

We decided to build an open-source project and here are a few tips that helped us grow and get huge companies like Amazon, Microsoft, IBM and Google to use and promote our product. 1. Organic reach: we published the project everywhere we could, and repeated that. Hacker News seemed to be the best place to get that first momentum. Yes, the website looks like it was taken from the 90s, but you'd be surprised at how many industry leaders are reading through posts there on a daily basis. Also worked well for us are dedicated Reddit communities, and to some extend Twitter/X. 2. Friendly Experience: we made our OSS friendly for first-time contributors from day 1. We opened around 10 issues in the repository with various degrees of complexity, tagged some with "good first issue" so that GitHub search engine can index our repo and opened a community slack workspace so people can ask questions or request guidance easily. 3. Quick Response: we monitored our open-source activity closely. We set up Zappier integrations so we get notified whenever someone opened an issue or a PR on the repo - so we can respond quickly. The first few contributors are looking for a quick feedback and may quickly abandon your project if they don't see maintainer activity. Community: we actively engaged with the community. We arranged webinars, answered questions, and were quick to fix bugs that were opened. This helped gain the trust that we need to make this succeed. Building and maintaining an open-source requires constant dedication of time and effort. But once you do it right, it’s a great way to get exposure to what you’re building. What is your story? How do you grow your open-source projects?