The hottest Technology Substack posts right now

And their main takeaways
Category
Top Technology Topics

How I use chatGPT

The Common Reader • 921 implied HN points • 09 Jun 23
🕹 Technology AI Copywriting
  1. The author discusses using ChatGPT for writing and editing, including feedback on a book manuscript.
  2. ChatGPT provided accurate summaries and assessments, along with helpful prompts for editing and copywriting.
  3. The post highlights utilizing ChatGPT for various tasks like book manuscript feedback, editing prompts, and copywriting assistance.

The Transition from Monolithic SIEMs to Data Lakes for Security Monitoring

Detection at Scale • 139 implied HN points • 23 Oct 23
🕹 Technology Security Cloud Platforms Open Source
  1. Transitioning from monolithic SIEMs to data lakes for security monitoring involves decoupled data architecture, cloud storage, open data formats, and distributed query engines for improved performance, scalability, and pricing models.
  2. Usability tradeoffs exist when shifting to data lakes, with a need for detection engineers specializing in tool accuracy and performance, while security analysts require tools for exhaustive answers and simplistic searches.
  3. The data pipeline in a transition involves components like data routing, transformation, storage, query engines, metadata, and real-time analysis, each playing a unique role in pulling, transforming, and analyzing security data in a data lake environment.

Your Feature is Not a Product

Nathan’s Substack • 79 implied HN points • 26 Jan 24
🕹 Technology Product Development Artificial Intelligence Tech industry Software Development User Experience
  1. A common mistake is mistaking a feature for a product, leading to incomplete solutions in the market.
  2. Customers care more about how a product solves their problem, rather than the specific technology used.
  3. Start with the customer experience and work back to the technology when designing products, a lesson exemplified by Steve Jobs.

The Libertarian Coder

Rethinking Software • 249 implied HN points • 10 Nov 24
🕹 Technology Software Development Programming Collaboration Work Culture Autonomy
  1. Working independently can be very rewarding, especially in coding. Some people thrive when they have control over their own projects and can focus deeply.
  2. There are different styles of collaboration in coding. Some prefer to share work with many people, while others like to work alone. Both ways can be valid and effective, depending on the person's preference.
  3. When you feel stuck at work, it's often not just your fault. It shows there might not be enough teamwork or communication. Asking lots of questions can help everyone succeed together.
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6 March is DMA-Day

Platform Papers • 59 implied HN points • 05 Mar 24
🕹 Technology Regulation Big Tech Compliance Market Impact Digital Platforms
  1. The Digital Markets Act (DMA) will enforce new rules on major digital platforms starting March 6, 2024, aiming to make markets fairer and more contestable for platforms like Apple, Google, Meta, TikTok, Amazon, and others.
  2. The DMA introduces obligations for gatekeepers to open up ecosystems, ensure fairness for business users, and promote transparency by submitting compliance plans publicly.
  3. The enforcement of DMA rules faces challenges from wealthy companies like Apple resisting compliance and the European Commission needing to balance limited resources with rigorous enforcement, highlighting the need for immediate action and collaboration with national agencies.

DeepSeek V3 and R1

From the New World • 188 implied HN points • 28 Jan 25
🕹 Technology AI Machine Learning Computing Innovation Data science
  1. DeepSeek has released a new AI model called R1, which can answer tough scientific questions. This model has quickly gained attention, competing with major players like OpenAI and Google.
  2. There's ongoing debate about the authenticity of DeepSeek's claimed training costs and performance. Many believe that its reported costs and results might not be completely accurate.
  3. DeepSeek has implemented several innovations to enhance its AI models. These optimizations have helped them improve performance while dealing with hardware limits and developing new training techniques.

Data Science Weekly - Issue 485

Data Science Weekly Newsletter • 319 implied HN points • 09 Mar 23
🕹 Technology Data science Machine Learning AI Data Engineering Data Visualization
  1. The newsletter shares interesting links about data science, machine learning, and AI each week. It’s a good way to keep up with new trends and knowledge in the field.
  2. There's a discussion on what databases should do but often don’t. Understanding these gaps can help you improve your data projects by knowing what to build yourself.
  3. AI's impact on jobs and industries is being researched, especially how language models like ChatGPT could change certain occupations. It's important to understand how AI can affect your career choices.

Meter: The Internet Utility

Not Boring by Packy McCormick • 183 implied HN points • 30 Jan 25
🕹 Technology Networking Internet Software Infrastructure Hardware
  1. Meter aims to make internet access as easy and universal as electricity. The founders believe that just like buildings come ready for power, companies should have straightforward internet setups too.
  2. By integrating hardware, software, and support into one package, Meter can provide better service at a lower cost. This approach helps them stand out from traditional network providers.
  3. Meter is working on creating advanced AI models to automate network management. This means that over time, networks could self-configure, get smarter, and require less human intervention.

Edition 30: The SDLC is changing and so will AppSec (again)

Boring AppSec • 69 implied HN points • 22 Jul 25
🕹 Technology Software Development Cybersecurity AI Tools Code Review Software Engineering
  1. Software development is changing with new tools, especially those powered by AI. This means that AppSec will also need to adapt to keep up with these changes.
  2. The way we manage software development and security must evolve, focusing on how to handle code prompts and automated reviews more effectively.
  3. As non-developers start writing more code using AI tools, we need to be careful because this code might be less secure. Therefore, engaging with all team members involved in code creation is important.

What Does Hitting Scaling Law Limit Mean for US-China AI Competition

Interconnected • 246 implied HN points • 18 Nov 24
🕹 Technology AI Machine Learning International relations Global Competition Data science
  1. The scaling law for AI models might be losing effectiveness, meaning that simply using more data and compute power may not lead to significant improvements like it did before.
  2. US export controls on AI technology may become less impactful over time, as diminishing returns on AI model scaling could lessen the advantages of having the most advanced hardware.
  3. If AI development slows down, the urgency for a potential 'AI doomsday' scenario may decrease, allowing for a more balanced competition between the US and China in AI advancements.

Fuzzing Ladybird with tools from Google Project Zero

awesomekling • 522 HN points • 16 Mar 24
🕹 Technology Security Web Development Software Testing Open Source
  1. Using tools like Domato from Google Project Zero can stress test software and reveal potential security issues.
  2. Implementations in software can be prone to issues like null pointer dereferences, especially when assumptions about the DOM structure are not validated.
  3. Finding and fixing bugs, whether real bugs or spec bugs, is essential to improving software stability and ensuring it can handle unexpected inputs.

Data Science Weekly - Issue 500

Data Science Weekly Newsletter • 219 implied HN points • 23 Jun 23
🕹 Technology Data science Artificial Intelligence Machine Learning Data Visualization Data Engineering
  1. AI technology is advancing quickly and can even cover public meetings, but we need to think carefully about its readiness for everyday use.
  2. Engineers can improve their people skills and interactions by applying the same problem-solving mindset they use in their technical work.
  3. Generative AI is becoming important in data science for creating synthetic data, which helps in privacy and enhances analysis without losing useful information.

The Sequence Weekly Alpha #686: Kimi K2 is a Trillion Parameter Open Source Model You Must Know About

TheSequence • 77 implied HN points • 16 Jul 25
🕹 Technology AI Open Source Innovation Research Data science
  1. Kimi K2 is a huge open source AI model with a trillion parameters, which makes it very powerful. It's important to know about advancements like this, especially as they can change how we use AI.
  2. The model uses a special design called Mixture-of-Experts that improves its efficiency. This means it can perform tasks better by only activating the parts it needs to.
  3. Kimi K2 shows strong performance in areas like coding and reasoning. This highlights how rapidly AI is evolving, and we need to keep up with newer developments from around the world.

AI and productivity: Year-in-review with Microsoft, Google, and GitHub researchers

Engineering Enablement • 13 implied HN points • 17 Dec 25
🕹 Technology Software Engineering Artificial Intelligence Developer Tools Productivity Metrics Collaboration Career development Automation
  1. Lines of code is a poor measure of AI’s value — more output doesn’t equal more impact. Use broader measures like satisfaction, performance, collaboration, and efficiency to judge whether AI actually helps.
  2. AI is changing the developer role from code producer to director and validator of AI-assisted work, so hiring, career paths, and training must prioritize AI fluency, systems thinking, and judgment. Juniors might learn end-to-end problem solving faster, but only if teams preserve mentorship and opportunities to collaborate.
  3. The real wins come from enablement and focusing AI on real bottlenecks or tedious work, not from constantly switching tools or models. Also, don’t trust simple headlines — dig into context, and design tools to boost creativity and meaningful automation rather than just raw speed.

The GPT Era

Artificial Ignorance • 79 implied HN points • 10 Jul 25
🕹 Technology AI Software Innovation Data Development
  1. The development of AI from models like GPT-3 to GPT-4 has seen rapid improvements in technology and user experience. Each version has made it easier for people to interact with AI in more useful ways.
  2. Competition in the AI market has led to better products and features, such as enhanced memory, web integration, and advanced coding tools. Now many companies offer similar core functions, making it important to focus on product design and user experience.
  3. As AI continues to evolve, there's a growing focus on reasoning models that help systems think more deeply. This shift will be important for making AI even more effective and adaptable in the future.

The Sequence Opinion #677: Glass-Box Transformers: How Circuits Illuminate Deep Learning’s Inner Workings

TheSequence • 84 implied HN points • 03 Jul 25
🕹 Technology AI Computers Research Innovation Data science
  1. Circuits are important for understanding how AI works, especially in transformer models. They help researchers see how different parts of the model work together.
  2. The circuits approach looks at groups of neurons that interact to perform tasks, not just single neurons. This helps in understanding the flow of information in AI.
  3. While circuits show promise for making AI more understandable, they might not be the only solution. There's still a lot to explore about how to really interpret these complex models.

Modular Deep Learning

MLOps Newsletter • 78 implied HN points • 27 Jan 24
🕹 Technology Deep Learning Generative models Classes
  1. Modular Deep Learning proposes splitting models into smaller, independent modules for specific subtasks.
  2. Modularity in AI development can lead to collaborative and efficient ecosystem and democratize AI development.
  3. PyTorch 2.0 introduces performance gains such as faster inference and training speeds, autotuning, quantization, and improved memory management.

10 things no one else will tell you about Apple Vision Pro

The Rubesletter by Matt Ruby (of Vooza) | Sent every Tuesday • 926 implied HN points • 06 Jun 23
🕹 Technology Tech news Tech Trends Virtual reality Artificial Intelligence Digital Culture
  1. Future of technology like Apple Vision Pro may have surprising uses beyond what we initially think.
  2. Passthrough feature in Apple Vision Pro allows mutual seeing - interesting concept for enhanced interaction.
  3. Reflect on the impact of excessive screen time and technology usage on real-life human interactions.

#1: Directing Attention + first ever article

12challenges • 171 implied HN points • 19 Feb 25
🕹 Technology Tech Analysis Media Satire Startups
  1. The publication '12 Challenges' has been rebranded to 'Directing Attention', aiming to create fun content about technology. It focuses on making tech exciting and offers a fresh perspective on the industry.
  2. The plan includes three types of content: playful tech analysis, satire, and interactive mini-sites. The writer plans to start by focusing on satire to quickly build an audience.
  3. A new website for 'Attention' is being created for maximum creative control, allowing for unique and interactive article presentations. This will help surprise and engage readers in new ways.

Space Tech and Science Fiction: Upgrading Your Inspiration through Sci-Fi

Space Ambition • 99 implied HN points • 22 Dec 23
🕹 Technology Space Tech Science fiction Innovation Inventions Media influence
  1. Science fiction movies often inspire real-life inventions. Films like 'Star Trek' and 'Back to the Future' have influenced technologies like mobile phones and self-lacing shoes.
  2. Many iconic sci-fi movies predicted future technology, such as tablets in '2001: A Space Odyssey' and digital billboards in 'Blade Runner.' These films sparked ideas that led to actual developments.
  3. Sci-fi doesn't just inspire inventors; it also motivates scientists. Movies like 'Interstellar' and 'The Martian' have pushed researchers to explore black holes and even name new plant species.

Running dbt-core on Github Actions: a comprehensive guide

The Orchestra Data Leadership Newsletter • 39 implied HN points • 18 Apr 24
🕹 Technology Data Transformation Automation Workflow management Orchestration
  1. Advantages of running dbt-core on GitHub Actions include easy workflow definition in Git, immediate access to latest code, and no need to provision instances for GitHub hosted runners.
  2. Disadvantages of running dbt-core on GitHub Actions include being limited by GitHub's workers, 'fire and forget' implementation, and overhead when connecting to external services.
  3. GitHub Actions workflows can be triggered from external sources like orchestrators using the repository dispatch event or the workflow_dispatch event, providing flexibility in integrating GitHub's CI/CD capabilities into larger automation strategies.

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.

Data at Depth Newsletter 5: On a Roll, My Free Courses, GPT-4 Guardrails For Code Generation

Data at Depth • 79 implied HN points • 25 Jan 24
🕹 Technology News Courses AI
  1. The newsletter author is experiencing a successful period with their Substack site and is considering if they are at the peak of their current cycle.
  2. The author is offering free 5-day email courses and discussing GPT-4 guardrails for code generation in their newsletter.
  3. The Data at Depth newsletter is reader-supported, and there is an option for a 7-day free trial to access full post archives.

The Sequence Knowledge #685: About LMArena-Type Evals, Do They Work or Don't

TheSequence • 77 implied HN points • 15 Jul 25
🕹 Technology AI Research Evaluation Startup Benchmarks
  1. LMArena is becoming important in how we evaluate AI models. It helps compare different language models in a clear and fair way.
  2. The platform started as a research project but has grown into a successful startup worth a lot of money. This shows how valuable good benchmarking is in the AI field.
  3. The post also talks about a debated paper called 'The Leaderboard Illusion,' which raises important questions about how AI performance is measured.

"We Once Again Need to Raise More Capital than We Had Imagined": Watching OpenAI Say It Needs a New Structure

Brad DeLong's Grasping Reality • 207 implied HN points • 30 Dec 24
🕹 Technology AI Startups Investment Innovation Economy
  1. OpenAI is looking for more money than they expected, which highlights how important funding is for their progress towards AGI. This means they need to attract investors willing to take risks.
  2. They plan to change their structure to a Public Benefit Corporation, balancing profit with broader social goals. This structure aims to raise capital more effectively while still focusing on their mission.
  3. OpenAI's current success is compared to how Netscape was for the internet. This suggests that OpenAI is leading a new wave of technology and investment in artificial intelligence.

Weekly Top Picks #94

The Algorithmic Bridge • 201 implied HN points • 13 Jan 25
🕹 Technology AI Software Innovation Ethics Music
  1. OpenAI's new model is not just a chatbot; it's designed to help users think and set goals differently.
  2. AI progress is happening fast, but many people aren't aware of it, making it hard to get ready for big changes ahead.
  3. There are worries about AI tools and trust issues, so it's essential to think carefully about how we use and talk about AI.

The Sequence Engineering #676: Hacking with Gemini CLI

TheSequence • 84 implied HN points • 02 Jul 25
🕹 Technology AI Tools Software Command-line Development Programming
  1. Gemini CLI uses Google's powerful AI to improve command-line tasks. It makes using command-line tools easier and more efficient.
  2. The system logs its decisions and shows its thought process, which helps users understand what the AI is doing. This makes it trustworthy and easy to troubleshoot.
  3. With its flexible design, Gemini CLI allows for added features through plugins, creating a customizable experience tailored to users' needs.

What would a $2,000-a-month ChatGPT look like?

Enterprise AI Trends • 168 implied HN points • 19 Feb 25
🕹 Technology AI Software Pricing Enterprise Markets
  1. The future of AI will see two main pricing categories: low-end for general users and high-end for specialized, enterprise-focused users. There's not much room in the middle.
  2. High-end AI products will need to be built on strong industry knowledge and proprietary data to be successful. This means startups might struggle to compete.
  3. AI companies can charge a lot because their products provide immense value in competitive fields, where even a small advantage can lead to big profits.

Weekly Dose of Optimism #146

Not Boring by Packy McCormick • 97 implied HN points • 30 May 25
🕹 Technology Biotech Aerospace Genetics Startups Innovation
  1. A startup called Orchid helps parents select embryos with lower disease risks using genetic testing. This raises both hope for healthier babies and ethical questions about how much we should design our kids.
  2. Doctors successfully transplanted a gene-edited pig kidney into a man, helping him avoid dialysis. This could change the future of organ transplants, as pig organs might be a solution to the shortage of human donors.
  3. Radiant, a nuclear startup, raised $165 million to develop a small reactor that can power remote areas and possibly aid in future Mars colonization. This shows growth in clean energy innovations.

U.S. Cyber Trust Mark

Resilient Cyber • 79 implied HN points • 24 Jan 24
🕹 Technology Cybersecurity Consumer Products Software Development
  1. The U.S. Cyber Trust Mark is a new program that helps consumers identify smart devices that are safer from cyber attacks. It's like an energy efficiency label but for cybersecurity.
  2. This program helps manufacturers create standards that make devices both secure and easy to sell internationally. It aims to solve problems that come from different security rules across countries.
  3. Consumers need better information when buying tech products because many devices, especially IoT ones, can pose security risks. The labeling will educate consumers on the safety of their purchases.

Building developer community and trust in today’s AI-first world

Dev Interrupted • 14 implied HN points • 11 Dec 25
🕹 Technology Software Development Developer Experience Documentation APIs
  1. AI assistants are becoming a primary discovery channel for developers, so content must work well for both humans and machines.
  2. Treat documentation as a product: structure docs in machine-readable formats and make them authoritative so AI gives accurate, trusted answers.
  3. Keep humans at the center. Use AI to scale support and mixed-mode experiences, and update metrics to measure AI visibility and developer trust.