The hottest Open Source Substack posts right now

And their main takeaways
Category
Top Technology Topics

GroupBy #38: Modernizing Uber’s Batch Data Infrastructure with Google Cloud Platform, Apache Iceberg - What Is It

VuTrinh. • 119 implied HN points • 04 Jun 24
🕹 Technology Data Engineering Cloud Computing Data Infrastructure Machine Learning Open Source
  1. Uber is upgrading its data system by moving from its huge Hadoop setup to Google Cloud Platform for better efficiency and performance.
  2. Apache Iceberg is an important tool for managing data efficiently, and it can help create a more organized data environment.
  3. Building data products requires a strong foundation in data engineering, which includes understanding the tools and processes involved.

The Sequence Opinion #476: The DeepSeek Effect: The Remarkable Innovations and Controversies Surrounding the New Challenger in Open-Source AI

TheSequence • 133 implied HN points • 24 Jan 25
🕹 Technology AI Open Source Innovation Controversies Models
  1. DeepSeek is a new player in open-source AI, quickly gaining attention for its innovative models. They have released powerful AI tools that can think and reason well, challenging the idea that only big models can do this.
  2. The company was founded in May 2023 and has shown rapid progress by continually improving its technology. This quick success highlights their commitment to pushing the limits of AI performance and efficiency.
  3. However, the fast advancements by DeepSeek have raised some controversies. People are discussing the implications of their rapid growth in the AI space, suggesting that it might impact the future of AI development.

Programmer Collaboration Styles

Rethinking Software • 299 implied HN points • 04 Nov 24
🕹 Technology Software Development Collaboration Open Source Remote work
  1. There are two main collaboration styles for programmers: individual stewardship and shared stewardship. Individual stewardship focuses on one person having full control, while shared stewardship means the whole team collaborates closely.
  2. Individual stewardship can lead to high-quality results because it allows for deep focus and mastery, but it might create knowledge silos. Shared stewardship promotes teamwork and knowledge sharing but may lead to average results due to differing skill levels.
  3. The right collaboration style can depend on the work being done. Tasks needing specialized skills might work better with individual stewardship, while general tasks benefit from shared stewardship and constant communication.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

Last Week in AI #254: DeepMind's AI cracks geometry problems, Meta commits to open-source AI, China and US firms hold secret AI safety talks, first AI chatbot for presidential candidate, and more!

Last Week in AI • 457 implied HN points • 22 Jan 24
🕹 Technology AI Open Source Safety Tech Companies
  1. DeepMind's AlphaGeometry AI solves complex geometry problems using a unique combination of language model and symbolic engine.
  2. Meta, under Zuckerberg, is focused on developing open-source AGI with the Llama 3 model and increasing compute infrastructure.
  3. US AI companies and Chinese experts engage in secret diplomacy on AI safety, signaling unprecedented collaboration amid technological rivalry.

($) DeepSeek Diffusion

Interconnected • 123 implied HN points • 07 Feb 25
🕹 Technology AI Open Source Geopolitics Cloud Computing Cybersecurity
  1. The ongoing discussion about DeepSeek focuses too much on the rivalry between the U.S. and China. It's more about whether technology is open source or closed source.
  2. Open source technology, like DeepSeek, can spread quickly and widely, getting adopted by various companies across the globe.
  3. Major cloud providers, including U.S. companies, are offering DeepSeek models to their customers, showing its significant impact in the tech world.

Monthly Python Data Engineering, September 2024

Monthly Python Data Engineering • 2 HN points • 26 Sep 24
🕹 Technology Data Engineering Open Source Python Software Development Libraries
  1. A new free book called 'How Data Platforms Work' is being created for Python developers. It will explain the inner workings of data platforms in simple terms, with one chapter released each month.
  2. The Ibis library has removed the Pandas backend and now uses DuckDB, which is faster and has fewer dependencies. This change is expected to improve performance and usability.
  3. Several popular libraries in Python, such as GreatTables and Shiny, have released updates with new features and improvements, focusing on better usability and integration with modern technologies.

OLMo 2 and building effective teams for training language models

Democratizing Automation • 245 implied HN points • 26 Nov 24
🕹 Technology AI Machine Learning Software Development Data science Open Source
  1. Effective language model training needs attention to detail and technical skills. Small issues can have complex causes that require deep understanding to fix.
  2. As teams grow, strong management becomes essential. Good managers can prioritize the right tasks and keep everyone on track for better outcomes.
  3. Long-term improvements in language models come from consistent effort. It’s important to avoid getting distracted by short-term goals and instead focus on sustainable progress.

Official provincial commentary on DeepSeek

Pekingnology • 113 implied HN points • 29 Jan 25
🕹 Technology AI Open Source Innovation Global Competition Startups
  1. DeepSeek, a Chinese AI company, has gained international attention for its open-source technology, which allows researchers around the world to access and use it. This approach is seen as a major strength of the company.
  2. The cost-effectiveness of DeepSeek's AI model is highlighted, showing that it achieves high performance at a fraction of the cost compared to similar models in the U.S. This makes AI development more accessible.
  3. The rise of DeepSeek shows that innovation and technological progress can flourish even when facing challenges like export restrictions and competition. Trusting young talent and fostering collaboration are key to success in tech development.

The Sequence Engineering #479: Dify.AI: A Deep Dive into its Open-Source LLM Application Development Platform

TheSequence • 112 implied HN points • 29 Jan 25
🕹 Technology AI Software Development Open Source Platforms
  1. Dify.AI is an open-source platform that helps developers create applications using large language models (LLMs). Its user-friendly setup makes it easier to build AI solutions like chatbots or complex workflows.
  2. The platform is designed to be flexible and keeps evolving to meet the needs of developers in the fast-paced world of generative AI. This adaptability is key when choosing a tech stack for projects.
  3. Dify.AI includes advanced features like Retrieval Augmented Generation (RAG), which enhances how applications gather and use information. This makes it a powerful tool for building sophisticated AI applications.

Does Decentralized Machine Learning Need Crypto? Bittensor (TAO)

DeFi Education • 599 implied HN points • 27 Oct 23
🕹 Technology AI Crypto Decentralization Machine Learning Open Source
  1. Bittensor is a platform that uses decentralized machine learning to connect users with miners who run AI models. It aims to create a more open and fair AI ecosystem where everyone can participate.
  2. The platform rewards miners and validators with TAO tokens based on their contributions, similar to how Bitcoin operates. This incentive system encourages the best AI models to be selected for user queries.
  3. There's a growing trend of open source AI projects that show promise without needing huge corporate funding, making it possible for smaller teams to create effective AI tools without significant expenses.

Is Kimball Still Relevant?

Joe Reis • 648 implied HN points • 22 Jul 23
🕹 Technology Data Modeling Open Source Hardware
  1. There are abundant tools and computing power available, but focusing on delivering business value with data is still crucial.
  2. Data modeling, like Kimball's dimensional model, remains relevant for effective analytics despite advancements in technology.
  3. Ignoring data modeling in favor of performance considerations can lead to a loss of understanding, business value, and overall impact.

Finding Data Bugs in dbt Pull Requests

clkao@substack • 39 implied HN points • 17 Aug 24
🕹 Technology Data Engineering Software Development Open Source Machine Learning Quality Assurance
  1. Data bugs can be costly for companies, with bad data potentially costing up to 25% of their revenue. These issues often arise from problems in data-centric systems like dbt.
  2. Using dbt allows data engineers to implement software practices like version control and testing, helping to ensure the correctness of their data transformations. However, relying solely on post-processing tests has its limits.
  3. Manual spot checks are still crucial in ensuring data accuracy during code reviews. Tools like Recce aim to streamline this process, making it easier for developers to validate and document their changes.

Setting up NextJS with GitHub Actions and feature flags using Flagsmith

The Open Source Expert • 59 implied HN points • 05 Jul 24
🕹 Technology Web Development Software Engineering DevOps Open Source Automation
  1. Using NextJS helps streamline your project with standardized setups, making it easier to onboard and rapidly develop features.
  2. Automating tasks with GitHub Actions can save time and reduce errors, giving you quick feedback on your code changes.
  3. Feature flags from Flagsmith allow you to control which features are visible without needing to redeploy your app, making it easier to manage updates and A/B tests.

The Days Are Long but the Years Are Short

Steve Coast’s Musings • 470 HN points • 09 Aug 24
🕹 Technology Open Source Mapping Innovation Volunteering Data Sharing
  1. OpenStreetMap has shown that with teamwork and volunteer efforts, we can create something valuable from scratch. It's amazing how people from different backgrounds come together to improve mapping.
  2. Fear and vanity can hold us back from trying new things. It's important to move beyond just thinking about ideas and actually take action to create something new.
  3. Even if new projects don't succeed, it's okay to experiment. Many ideas might need to evolve or even be completely abandoned to find what really works.

The Rise of Indian Llamas

Sector 6 | The Newsletter of AIM • 399 implied HN points • 25 Dec 23
🕹 Technology AI Language Models Open Source Innovation Enterprise
  1. Llama 2 is a popular open-source language model with many downloads worldwide. In India, people are using it to create models that work well for local languages.
  2. A new Hindi language model called OpenHathi has been released, which is based on Llama 2. It offers good performance for Hindi, similar to well-known models like GPT-3.5.
  3. There is a growing interest in using these language models for business in India, indicating that the trend of 'Local Llamas' is just starting to take off.

OpenAI's moat

TechTalks • 334 implied HN points • 15 Jan 24
🕹 Technology AI Open Source Modeling Monetization Innovation
  1. OpenAI is building new protections to safeguard its generative AI business from open-source models
  2. OpenAI is reinforcing network effects around ChatGPT with features like GPT Store and user engagement strategies
  3. Reducing costs and preparing for future innovations like creating their own device are part of OpenAI's strategy to maintain competitiveness

Why I build open language models

Democratizing Automation • 261 implied HN points • 30 Oct 24
🕹 Technology AI Development Open Source Language Models Ethics Regulation
  1. Open language models can help balance power in AI, making it more available and fair for everyone. They promote transparency and allow more people to be involved in developing AI.
  2. It's important to learn from past mistakes in tech, especially mistakes made with social networks and algorithms. Open-source AI can help prevent these mistakes by ensuring diverse perspectives in development.
  3. Having more open AI models means better security and fewer risks. A community-driven approach can lead to a stronger and more trustworthy AI ecosystem.

Open Source Data Engineering Landscape 2024

Practical Data Engineering Substack • 299 implied HN points • 28 Jan 24
🕹 Technology Data Engineering Open Source Software Tools Data processing Data Integration
  1. The open-source data engineering landscape is growing fast, with many new tools and frameworks emerging. Staying updated on these tools is important for data engineers to pick the best options for their needs.
  2. There are different categories of open-source tools like storage systems, data integration, and workflow management. Each category has established players and new contenders, helping businesses solve specific data challenges.
  3. Emerging trends include decoupling storage and compute resources and the rise of unified data lakehouse layers. These advancements make data storage and processing more efficient and flexible.

Clues Say Generative AI’s Future Will Be Revealed in 2024

The Algorithmic Bridge • 700 implied HN points • 19 Jan 24
🕹 Technology AI Generative AI AGI Open Source
  1. 2024 is a significant year for generative AI with a focus on revelations rather than just growth.
  2. There is uncertainty on whether GPT-4 is the best we can achieve with current technology or if there is room for improvement.
  3. Mark Zuckerberg's Meta is making a strong push towards AGI, setting up a high-stakes scenario for AI development in 2024.

Open LLMs don’t need to beat OpenAI

The AI Frontier • 119 implied HN points • 09 May 24
🕹 Technology AI Machine Learning Open Source Software Development Data science
  1. Open LLMs, like Llama 3, are getting really good and can perform well in many tasks. This improvement makes them a strong option for various applications.
  2. Fine-tuning open LLMs is becoming more attractive because of their improved quality and lower costs. This means smaller, specialized models can be more easily developed and used.
  3. However, open models likely won't surpass OpenAI's offerings. The proprietary models have a big advantage, but open LLMs can still thrive by focusing on efficiency and specific use cases.

Triplex — a SOTA LLM for Knowledge Graph Construction

Owen’s Substack • 59 implied HN points • 19 Jul 24
🕹 Technology AI Machine Learning Data science Open Source Software Development
  1. Triplex is a new tool that helps create knowledge graphs quickly and cheaply. It's much cheaper to use than older methods, making it easier for more people to utilize.
  2. This tool is small enough to run on regular laptops, which means you don't need powerful computers to build knowledge graphs. This makes technology more accessible to everyone.
  3. Triplex is open-source, allowing anyone to use and improve it. The community can experiment with it freely and innovate new ways to organize and understand information.

Open Source Security Landscape 2024

Resilient Cyber • 139 implied HN points • 21 Apr 24
🕹 Technology Cybersecurity Open Source Software Development Risk management
  1. Most codebases now use a lot of open source software, which can come with serious security risks. This means many systems are more vulnerable because they contain known vulnerabilities that might not be addressed.
  2. The number of components in applications is increasing, leading to software bloat. This makes it tough for teams to manage security and keep everything up to date, which can create more risks for users.
  3. Licensing issues are common in open source software, with many projects having conflicts or unclear licenses. This can lead to legal problems for businesses that use these components in their software.

Edge 462: What is Fast-LLM. The New Popular Framework for Pretraining your Own LLMs

TheSequence • 126 implied HN points • 02 Jan 25
🕹 Technology AI Models Open Source Scalability Research Innovation
  1. Fast-LLM is a new open-source framework that helps companies train their own AI models more easily. It makes AI model training faster, cheaper, and more scalable.
  2. Traditionally, only big AI labs could pretrain models because it requires lots of resources. Fast-LLM aims to change that by making these tools available for more organizations.
  3. With trends like small language models and sovereign AI, many companies are looking to build their own models. Fast-LLM supports this shift by simplifying the pretraining process.

($) DeepSeek's Three Idiosyncratic Advantages

Interconnected • 138 implied HN points • 03 Jan 25
🕹 Technology AI Open Source Machine Learning Global Competition Data science
  1. DeepSeek-V3 is an AI model that is performing as well or better than other top models while costing much less to train. This means they're getting great results without spending a lot of money.
  2. The AI community is buzzing about DeepSeek's advancements, but there seems to be less excitement about it in China compared to outside countries. This might show a difference in how AI news is perceived globally.
  3. DeepSeek has a few unique advantages that set it apart from other AI labs. Understanding these can help clarify what their success means for the broader AI competition between the US and China.

Death Knell of the NVD?

Resilient Cyber • 199 implied HN points • 11 Mar 24
🕹 Technology Cybersecurity Software Data Management Vulnerability Management Open Source
  1. The NIST National Vulnerability Database (NVD) is an important source for understanding software vulnerabilities, but it is facing significant issues. Many vulnerabilities lack timely analysis and critical information.
  2. There is a need for better tagging and categorization of vulnerabilities, such as associating Common Vulnerability Enumeration (CVE) identifiers with specific products. Without this, organizations struggle to know what vulnerabilities affect their systems.
  3. Alternatives to the NVD like the Sonatype OSS Index and the Open-Source Vulnerabilities (OSV) Database are emerging, but they focus primarily on open-source software. The effectiveness and reliability of the NVD remain crucial for broader security practices.

RAG Foundry By Intel

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 13 Aug 24
🕹 Technology Artificial Intelligence Software Development Open Source Data science Machine Learning
  1. RAG Foundry is an open-source framework that helps make the use of Retrieval-Augmented Generation systems easier. It brings together data creation, model training, and evaluation into one workflow.
  2. This framework allows for the fine-tuning of large language models like Llama-3 and Phi-3, improving their performance with better, task-specific data.
  3. There is a growing trend in using synthetic data for training models, which helps create tailored datasets that match specific needs or tasks better.

A Comprehensive Approach to Using LLMs

Gradient Flow • 519 implied HN points • 05 Oct 23
🕹 Technology Machine Learning Open Source Deployment Data security
  1. Starting with proprietary models through public APIs, like GPT-4 or GPT-3.5, is a common and easy way to begin working with Large Language Models (LLMs). This stage allows exploration with tools like Haystack.
  2. Transitioning to open source LLMs provides benefits like cost control, speed, and stability, but requires expertise in managing models, data, and infrastructure. Using open source LLMs like Llama models from Anyscale can be efficient.
  3. Creating custom LLMs offers advantages of tailored accuracy and performance for specific tasks or domains, though it requires calibration and domain-specific data. Managing multiple custom LLMs enhances performance and user experience but demands robust serving infrastructure.

Edge 460: Anthropic's New Protocol to Link AI Assistants to Data Sources

TheSequence • 119 implied HN points • 26 Dec 24
🕹 Technology AI Software Open Source Data Frameworks
  1. Anthropic has created the Model Context Protocol (MCP) to help AI assistants connect with different data sources. This means AI can access more information to assist users better.
  2. MCP is open-source, which allows developers to use and improve the protocol freely. This encourages collaboration and innovation in AI tools.
  3. Anthropic is expanding its focus beyond AI models to include workflows and developer tools, showing that they're growing in new areas within AI technology.

Deploying simple Streamlit apps

Mostly Python • 524 implied HN points • 06 Feb 24
🕹 Technology Deployment GitHub Open Source
  1. You can deploy Streamlit apps to Streamlit's Community Cloud hosting service with a straightforward process.
  2. Make sure to be aware of the privacy concerns when granting Streamlit permissions for GitHub repositories.
  3. Streamlit sets a web hook on the repository, so any changes pushed to the repository's main branch will automatically update the deployed project.

The Sequence Engineering #488: Txtai, Maybe the Simplest Way to do Embeddings

TheSequence • 63 implied HN points • 12 Feb 25
🕹 Technology AI Software Open Source Databases Development
  1. Embeddings are important for generative AI applications because they help with understanding and processing data. A good embedding framework should be simple and easy for developers to use.
  2. Txtai is an open-source database that combines different tools to make working with embeddings easier. It allows for semantic search and supports creating various AI applications.
  3. This framework can help build advanced systems like autonomous agents and search tools, making it a versatile choice for developers creating LLM apps.

LAION-5B, Stable Diffusion 1.5, and the Original Sin of Generative AI

Cybernetic Forests • 279 implied HN points • 03 Jan 24
🕹 Technology AI Generative AI Open Source
  1. The article discusses the implications of AI infrastructure and the lack of input from the right experts in the field.
  2. It highlights the presence of concerning content within AI training datasets like LAION-5B, raising ethical issues in generative AI systems.
  3. The author mentions being quoted in a Wired Magazine article about Generative AI in relation to Mickey Mouse, hinting at upcoming content on this topic.

No more shell scripts!

Wednesday Wisdom • 94 implied HN points • 29 Jan 25
🕹 Technology Software Development Programming Languages Open Source Automation
  1. Shell scripts used to be great for automating tasks, but they have many limitations now. New programming languages do a better job and are more reliable.
  2. The Unix system made software development easier with tools and commands that could be combined. This modular approach set a solid foundation for coding.
  3. While shell scripts were revolutionary, modern programming languages and libraries have improved our ability to write better and more efficient programs.

No RSS Feed? No Problem. Using Claude Sync, Claude Projects and GitHub Copilot Workspace to automate everything

Olshansky's Newsletter • 114 implied HN points • 08 Jan 25
🕹 Technology AI Tools Software Development Automation Open Source Productivity
  1. Missing RSS feeds can be a hassle, but there are tools available to create them easily for any blog. Using platforms like Claude Projects and GitHub Copilot, people can automate the feed generation process.
  2. Using AI tools like Claude and GitHub Copilot can make daily tasks more efficient. They help simplify coding tasks and can significantly boost team productivity.
  3. By building custom RSS feed generators, developers can keep track of content from blogs that don’t offer subscription options. This means staying updated on favorite blogs is still possible, even without traditional feeds.

Managing Open Source and SBOM's

Resilient Cyber • 299 implied HN points • 13 Dec 23
🕹 Technology Cybersecurity Software Open Source Supply Chain Governance
  1. It's important for organizations using open source software (OSS) to know the responsibilities of developers and suppliers. They should track updates and manage licenses to avoid risks.
  2. Creating a secure internal repository for OSS can help organizations ensure that the components meet safety and compliance standards before using them in products.
  3. Using Software Bill of Materials (SBOM) and Vulnerability Exploitability eXchange (VEX) documents helps improve transparency about the software components. This makes it easier to manage risks related to vulnerabilities.

AI Roundup 095: QwQ

Artificial Ignorance • 37 implied HN points • 29 Nov 24
🕹 Technology AI Models AI Development Open Source Tech investment AI Ethics
  1. Alibaba has launched a new AI model called QwQ-32B-Preview, which is said to be very good at math and logic. It even beats OpenAI's model on some tests.
  2. Amazon is investing an additional $4 billion in Anthropic, which is good for their AI strategy but raises questions about possible monopolies in AI tech.
  3. Recently, some artists leaked access to an OpenAI video tool to protest against the company's treatment of them. This incident highlights growing tensions between AI companies and creative professionals.