The hottest Software Development Substack posts right now

And their main takeaways
Category
Top Technology Topics

Memory Unsafety is a Culture Issue

Burning the Midnight Coffee • 6 HN points • 03 Mar 24
🕹 Technology Security Programming Languages Software Development Memory management Cybersecurity
  1. Memory unsafety is not just a technical problem, but a cultural issue, requiring a shift in mindset within the software development community.
  2. The convenience factor plays a crucial role in memory safety; even safe languages have pathways to create memory vulnerabilities that may be more convenient to use than safe alternatives.
  3. Prioritizing measures like preventing buffer overflows in languages like C and C++ can have a significant impact on reducing vulnerabilities before focusing on more complex memory management concerns.

Data Science Weekly - Issue 466

Data Science Weekly Newsletter • 19 implied HN points • 27 Oct 22
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Open Source
  1. Science education should focus on teaching scientific virtues first, rather than just tools and techniques. This approach helps students understand the core values of scientific inquiry.
  2. A data dictionary is essential for ensuring quality data collection and interpretation. It's best created before data collection to guide your research design.
  3. The Farama Foundation is aimed at improving open-source reinforcement learning by maintaining and standardizing existing libraries. This will help in developing more effective RL tools for the community.

Will PostgreSQL switch to a Thread-based model ?

Engineering At Scale • 15 implied HN points • 24 Jun 23
🕹 Technology Database Architecture Modeling Software Development Performance
  1. PostgreSQL currently uses a process-based model for handling client connections and managing data.
  2. The process-based model offers advantages like fault isolation, security guarantees, and efficient resource management.
  3. Although there are advantages to the process-based model, the community is considering a switch to a thread-based model for PostgreSQL in the future.
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Data Science Weekly - Issue 465

Data Science Weekly Newsletter • 19 implied HN points • 20 Oct 22
🕹 Technology AI Data science Machine Learning Software Development Neuroscience
  1. AI writing assistants are helping indie authors write faster and come up with story ideas. Tools like Lex are changing how creatives approach their writing.
  2. Recent research shows that parts of the brain, like the hippocampus, work similarly to AI models known as transformers. This discovery helps us understand both artificial intelligence and human memory.
  3. The State of AI Report 2022 reviews important trends in AI, including technology breakthroughs, commercial applications, and safety concerns. It provides valuable insights for both researchers and industry leaders.

Data Science Weekly - Issue 464

Data Science Weekly Newsletter • 19 implied HN points • 13 Oct 22
🕹 Technology Data science Artificial Intelligence Machine Learning Software Development Research Methods
  1. Building a community around R in the pharmaceutical industry can help users connect and share knowledge more effectively. It's important to identify who the users are and create a space for collaboration.
  2. Creating research ideas can start with understanding gaps in existing literature. By reading a single paper, you can learn frameworks to generate new ideas and improve your research quality.
  3. Data cleaning for machine learning models is crucial, starting from the ETL pipeline. It’s important to commit to high-quality data from the beginning to avoid common pitfalls that impact model accuracy.

Gradient Flow #38: Large Language Models, Infinite Laptop, Overhyping AI

Gradient Flow • 39 implied HN points • 01 Jul 21
🕹 Technology Data science Machine Learning Software Development Funding Tools
  1. Training large language models involves a new role referred to as 'prompt engineer'.
  2. TabNet, a deep neural network for tabular data, outperforms other models in classification and regression problems.
  3. Tools like AugLy for data augmentation and Flat Data for data acquisition simplify tasks and enhance model robustness.

Data Science Weekly - Issue 461

Data Science Weekly Newsletter • 19 implied HN points • 22 Sep 22
🕹 Technology Data science Machine Learning Natural Language Processing Artificial Intelligence Software Development
  1. Working in Natural Language Processing (NLP) involves keeping up with evolving models and figuring out how to effectively use data. It's still challenging for many to find practical applications for NLP.
  2. Generative AI has the potential to make workers significantly more efficient and creative. This could result in substantial economic value across various industries.
  3. Building trust in machine learning is crucial but challenging. It's important to address concerns about model reliability to maximize its business value.

Nibble #12

The Nibble • 14 implied HN points • 18 Jun 23
🕹 Technology AI Data Breach AGI Software Development
  1. CoWIN experienced an alleged data breach involving sensitive personal information like Aadhar and passport details.
  2. Google recently sold its domain business to Squarespace.
  3. OpenAI released new updates, including powerful API enhancements and feature additions.

🧙‍♂️ You’re an AI wizard, Harry!

HackerPulse Dispatch • 5 implied HN points • 05 Mar 24
🕹 Technology AI Software Development Tech stack User Feedback AI Tools
  1. AI-powered Wisary transforms software planning into a united front of understanding and collaboration, saving engineering teams billions annually
  2. Wisary, founded by Ala Stolpnik, aims to compensate for human limitations in software project planning by seamlessly integrating AI expertise
  3. Wisary's features like structured guidance, AI-powered drafting, and comprehensive review benefit product managers, engineering managers, and the entire organization, ensuring timely project success

Data Science Weekly - Issue 457

Data Science Weekly Newsletter • 19 implied HN points • 25 Aug 22
🕹 Technology AI Data science Machine Learning Software Development Collaboration
  1. AI systems struggle with language limitations and won't fully replicate human thinking. This shows that our understanding of thought and language needs to evolve.
  2. Observable launched Free Teams to encourage more open collaboration in data science. It allows users to easily work together on projects and share insights for free.
  3. There is a problem in the data industry where roles are too narrowly defined, leading to a lack of collaboration. This makes it hard for teams to communicate and understand each other's work.

Data Science Weekly - Issue 456

Data Science Weekly Newsletter • 19 implied HN points • 18 Aug 22
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Analytics
  1. Machine learning models need ongoing maintenance after they're deployed. The world changes, and so do the needs for the models.
  2. Using machine learning can make software testing more efficient, especially in complex applications like browsers.
  3. There are many resources available for people who want to get into machine learning and deep learning, including courses, videos, and discussions on best practices.

Making a Rider plugin, because JetBrains won't

Dennis’s Substack • 1 HN point • 12 May 24
🕹 Technology Debugging Software Development
  1. Debugger in JetBrains Rider has limitations like not being able to attach to multiple processes easily through the UI.
  2. Extending JetBrains IDEs' functionality with plugins can help users address software limitations and improve their workflow.
  3. Developing plugins for JetBrains IDEs, like Rider, involves challenges such as lack of documentation, UI implementation, and handling concurrency.

Consistency is Key

Tribal Knowledge • 19 implied HN points • 25 May 22
🕹 Technology Software Development Tech Debt
  1. Consistency is crucial in various aspects like reliability and understanding code.
  2. Introducing new patterns can be beneficial but may lead to tech debt and increased cognitive load.
  3. Startups often struggle with consistency due to rapid changes, creating tech debt that can burden growth.

Data Science Weekly - Issue 452

Data Science Weekly Newsletter • 19 implied HN points • 21 Jul 22
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Data Engineering
  1. The role of data scientist remains popular and well-paid, with growth expected in the field by 2029.
  2. Large language models (LLMs) are rapidly evolving and are becoming integral to various applications in our daily lives.
  3. Many industries are seeing the rise of domain experts who can now create and work with deep learning models without needing advanced degrees.

When Standalone AI Apps Meet Existing Systems of Record

Venture Reflections • 5 implied HN points • 16 Feb 24
🕹 Technology AI Software Integration Enterprise Solutions Workflow management Software Development
  1. AI-powered applications face challenges when integrating with existing core systems of record that were not initially designed for AI
  2. Successful standalone AI apps now need to connect with existing workflows and systems like HRIS, ATS, ERP platforms, and CRMs
  3. The need for AI apps to integrate with established infrastructure offers opportunities for differentiation and defensibility in the market

On Developer Marketing

Optimism (for the web) • 4 implied HN points • 24 Mar 24
🕹 Technology Software Development Marketing Strategies Trust Building Community Engagement
  1. Building trust is key in developer marketing. Developers want to know that a product is reliable and that they can turn to it without worry.
  2. Great marketing for developers should be clear and useful. Instead of using fancy terms, it should focus on how to help developers create better products.
  3. Engagement with the community is crucial. Hosting events and talking to developers can guide product improvements and create valuable content ideas.

18/36 :Product Discovery - Risks & Mitigations

Product Mindset's Newsletter • 17 implied HN points • 21 May 23
💼 Business Risk management Technology Project management Software Development Strategic Planning
  1. Understanding product risks involves assessing the impact of uncertainty on developing a product.
  2. Risk management in IT projects is crucial for maximizing results, effective communication, and allocating funds for high risks.
  3. Managing risks involves identifying, analyzing, and mitigating them through strategies like avoiding, reducing likelihood, and reducing impact.

Naming Things

The 418 • 1 HN point • 06 May 24
🕹 Technology Coding Software Development Naming Conventions Programming Engineering
  1. Good names are crucial in programming as they become the building blocks of our shared tools, maintaining order and helping us recall resources.
  2. Well-named things should be SEO-friendly, follow conventions, be concise but meaningful, consider collisions, guessable, and even bring a smile.
  3. Injecting humor or cleverness into naming can add personality and help with team bonding, as well as make code memorable.

Why are non-DRY specs more maintainable?

The Daily Developer • 2 HN points • 20 Feb 24
🕹 Technology Software Development Code Quality
  1. Non-DRY specs prioritize duplication over the wrong abstraction, promoting simple code with locality over complexity.
  2. Locality in code refers to its ability to be easily understood without relying on larger context, making it more maintainable.
  3. Compression in code, which requires understanding context, is seen as the wrong abstraction, leading to complexity and less maintainable code.

Data Science Weekly - Issue 448

Data Science Weekly Newsletter • 19 implied HN points • 23 Jun 22
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Data Engineering
  1. Machine learning can help the IRS process a huge amount of tax data more efficiently, improving enforcement actions on tax compliance.
  2. Denoising Diffusion Probabilistic Models are showing great success in generating images and audio, making them popular in creative AI applications like DALL-E 2.
  3. Training and developing skills in SQL can greatly enhance your data handling abilities, leading to better opportunities in data analysis and engineering.

Data Science Weekly - Issue 447

Data Science Weekly Newsletter • 19 implied HN points • 16 Jun 22
🕹 Technology Artificial Intelligence Machine Learning Data science Software Development Natural Language Processing
  1. Natural language processing is getting better, but it's important to remember that it's just imitating consciousness, not actually having it.
  2. Scaling AI models may improve performance, but there are limits due to the quality of the data they learn from.
  3. Emerging techniques like optical neural networks are being developed to speed up image classification significantly.

Episode 17: Burkhard on Qt Embedded Systems

burkhardstubert • 39 implied HN points • 03 May 21
🕹 Technology Embedded Systems Software Development Programming Languages Licensing Decision-making
  1. Qt LGPLv3 is good for many projects, and less than 25% of modules are under commercial licenses. This makes Qt accessible for many developers and companies.
  2. Effective decision making is important in projects. It involves knowing when to step back and let the expert handle specific decisions to keep the project on track.
  3. The Qt Company is acquiring other companies, like froglogic, to enhance their tools which will benefit developers. This shows a commitment to improving the software development process.

What I learned failing to outsource an MVP

Remus’s Symposium • 2 HN points • 15 Feb 24
🕹 Technology Outsourcing Software Development Developers Entrepreneurship
  1. Building an MVP requires more than just outsourcing; becoming technical as a founder can be crucial for success.
  2. Choosing fancy new technologies for an MVP, like Flutter, may lead to unexpected challenges and delays; sticking to tried-and-true web technologies can simplify the process.
  3. Outsourcing software development as a non-technical founder can be risky due to communication difficulties and lack of control over the project; learning to code can empower you to have a hands-on approach and clearer vision.