The hottest Technology Substack posts right now

And their main takeaways
Category
Top Technology Topics

4 Things You Probably Didn’t Know About Mastodon — The Anti-Twitter

Kristina God's Online Writing Club • 119 implied HN points • 17 Jan 23
🕹 Technology Social media Platforms Digital Communication Content creation User engagement
  1. Mastodon is growing while Twitter is losing users. Many people are leaving Twitter, and Mastodon is gaining traction as a new option.
  2. Creators are seeking alternatives to Twitter due to the changes made by Elon Musk. Mastodon offers a decentralized space where users can have more control.
  3. On Mastodon, you can post short messages called 'toots' that are up to 500 characters long. This is a great way for users to connect and share their thoughts.

Prompt Engineering for AI: A Valuable Skill for Security Professionals?

Rod’s Blog • 39 implied HN points • 13 Dec 23
🕹 Technology AI Security Training Tools Jobs
  1. Prompt engineering is a valuable skill for leveraging the power of AI in creative and efficient ways by improving the quality and accuracy of AI outputs.
  2. Effective prompt engineering can expand the capabilities and applications of AI systems, enabling them to perform tasks beyond their pre-defined scope using general knowledge and reasoning abilities.
  3. Prompt engineering is important for enhancing interaction and collaboration between humans and AI systems, making AI more human-like and relatable by crafting well-designed prompts.

The KQL Mysteries: The Holiday 2023 Episode Part 3

Rod’s Blog • 39 implied HN points • 13 Dec 23
🕹 Technology Cybersecurity Data Analysis
  1. The mysterious numbers given by the hacker were not random, but dates with a hidden significance, leading to a revelation about impending events.
  2. Through identifying patterns in network traffic using KQL, Jon and Sarah uncovered a hacker exploiting a security vulnerability and resolved to apply a critical patch.
  3. The duo set a trap to stop the hacker's planned attack, showcasing the importance of proactive security measures in monitoring and defending against cyber threats.

This is the Most Interesting Time in Human History. So far.

The Digital Anthropologist • 79 implied HN points • 22 Apr 23
🕹 Technology Digital Genetic Engineering Capitalism Democracy Artificial Intelligence
  1. This may be the most interesting time in human history due to the rapid advancements in digital technologies and societal changes.
  2. Humanity has always progressed through massive societal changes driven by revolutionary technologies, and the pace of such changes is accelerating.
  3. Key changes underway include a shift in our relationship with nature, advancements in genetic engineering for longer lifespans, the evolution of capitalism and democracy, and the impact of invisible technologies.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

Weekly Notes

Rethinking Software • 99 implied HN points • 21 Oct 24
🕹 Technology Software Development Agile Methodology Coding Practices Team Dynamics
  1. Managing programmers can be unpredictable. It's important to accept that things may not always go as planned.
  2. Euphemisms in corporate language can hide unpleasant truths. Words like 'alignment' often mean forcing compliance rather than true cooperation.
  3. Scrum practices may not be effective for all teams. Some core principles can actually create stress and hinder productivity instead of helping it.

The KQL Mysteries: The Holiday 2023 Episode Part 2

Rod’s Blog • 39 implied HN points • 12 Dec 23
🕹 Technology Cybersecurity Coding Data Analysis
  1. The hacker in the story had a personal connection to one of the characters, making the situation more intense and personal.
  2. Using Kusto Query Language (KQL), the characters tried to analyze the hacker's network traffic and database activity to uncover clues about the hacker's identity and location.
  3. Despite challenges in decoding the hacker's data, the characters discovered a message from the hacker in the database logs, prompting them to solve a mysterious puzzle involving numbers.

What's new in GHC 2021

Type Classes • 403 implied HN points • 14 Mar 23
🕹 Technology Programming
  1. Use GHC2021 as the language for Haskell projects to stay up-to-date.
  2. Haskell has evolved through different versions and compilers, with GHC being a major player.
  3. GHC 2021 introduces new features like expanding deriving power, more explicit type information, and new ways to write numbers.

AI Foundations Part 1: Transformers, Pre-Training and Fine-Tuning, and Scaling

Mule’s Musings • 378 implied HN points • 11 Apr 23
🕹 Technology AI Machine Learning Model Scaling Fine-tuning
  1. The Transformer model revolutionized Large Language Models (LLMs) with its parallel and scalable architecture.
  2. Pre-training and fine-tuning, as seen in GPT-1 and BERT, significantly improved model performance for various tasks.
  3. Bigger models, more data, and computing power have shown to lead to better performance in LLMs, but the relationship between model size, training tokens, and performance is more complex than initially thought.

Mixtral: The best open model, MoE trade-offs, release lessons, Mistral raises $400mil, Google's loss, vibes vs marketing

Democratizing Automation • 237 implied HN points • 11 Dec 23
🕹 Technology AI Models Community Machine Learning Ethics
  1. Mixtral model is a powerful open model with impressive performance in handling different languages and tasks.
  2. Mixture of Expert (MoE) models are popular due to their better performance and scalability for large-scale inference.
  3. Mistral's swift releases and strategies like instruction-tuning show promise in the open ML community, challenging traditional players like Google.

Micro-Benchmarking a RISC-V SBC (CanMV K230)

Fprox’s Substack • 20 implied HN points • 23 Aug 25
🕹 Technology Computing Software Development Hardware Benchmarking
  1. Micro-benchmarks help you measure how fast different instructions run on the RISC-V K230 chip. This is important for understanding the chip's performance.
  2. Data values can change how fast instructions execute, especially for operations like division. It's crucial to consider these variations in performance measurements.
  3. The RISE development image is a stable and feature-rich option for developers working with the CanMV K230. It makes connecting and running programs easier compared to earlier images.

Enterprise General Intelligence: The Emergent Mind of Organizations

Nano Thoughts • 1 implied HN point • 02 Feb 26
🕹 Technology Artificial Intelligence Enterprise Software Organizational Design Systems Architecture Product Strategy
  1. Companies need a nervous system — continuous sensing, shared memory, and homeostatic regulation — not a single omniscient center, so drift gets detected and corrected early.
  2. Culture is the organization's decision procedure, so make decision logic visible and teachable. Provide contextual memory that surfaces the right information at the moment of choice and traces provenance to resolve conflicts.
  3. Build a continuous, stateful, symbiotic system with clear governance and privacy (including a right to forget) rather than a stateless rented model or surveillance tool, because surveillance drives real thinking underground.

Security Throwing Toil Over the Fence

Resilient Cyber • 99 implied HN points • 10 May 23
🕹 Technology Cybersecurity Software Development DevOps Application Security Innovation
  1. It's important to shift security measures smartly rather than just shifting them left in the development cycle. We need the right context to effectively identify real risks in applications.
  2. Many security tools produce a lot of noise and false positives, which frustrates developers. If security teams provide context-rich insights instead, it would help everyone work better together.
  3. There’s a cultural gap where security teams dump problems on developers without proper context, leading to resentment. Improving communication and collaboration can help avoid this issue.

Prompt-RAG

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 20 Mar 24
🕹 Technology AI Machine Learning Data science Natural Language Processing Computing
  1. Prompt-RAG is a new method that improves language models without using complex vector embeddings. It simplifies how we retrieve information to answer questions.
  2. The process involves creating a Table of Contents from documents, selecting relevant headings, and generating responses by injecting context into prompts. It makes handling data easier.
  3. While this method is great for smaller projects and specific needs, it still requires careful planning when constructing the documents and managing costs related to token usage.

Intel Pushes the Nitro Button

Sector 6 | The Newsletter of AIM • 39 implied HN points • 11 Dec 23
🕹 Technology AI Chips Computing Trends Innovation
  1. Intel is planning a big event where they might announce new AI products to compete with NVIDIA and AMD. This shows how competitive the tech industry has become.
  2. One exciting product expected is the Gaudi3 AI accelerator chip, which will be much faster and better than the previous version. It promises improved performance with higher compute power and memory capacity.
  3. Looking ahead, Intel has plans for even more advanced chips, combining their AI technology with GPU power. This hints at more innovations coming in the future.

A UXer's guide to neurodiversity

UX Psychology • 158 implied HN points • 13 May 22
🕹 Technology Design Neurodiversity Inclusion Accessibility User Experience
  1. Neurodiversity encompasses a wide range of neurological variations in the human population, emphasizing the positive aspects and uniqueness of different thinking styles and cognitive functions.
  2. When designing for neurodiversity, consider factors like font choice, error prevention, clear copywriting, sensory issues, and consistency in design to create inclusive user experiences.
  3. In the workplace, it's important to foster understanding and flexibility to support neurodiverse individuals, from adjusting hiring practices to creating accommodating work environments and providing education and resources.

Demystifying GPU Compute Architectures

The Chip Letter • 210 HN points • 04 Feb 24
🕹 Technology Machine Learning
  1. Understanding GPU compute architectures is crucial for maximizing their potential in machine learning and parallel computing.
  2. The complexity of GPU architectures stems from differences in terminology, architectural variations, legacy terminology, software abstractions, and specific dominance by CUDA.
  3. Examining the levels in GPU compute hardware - basic units, grouped units (Streaming Multiprocessor or Compute Unit), and final GPU architecture - reveals a high level of computational power compared to CPUs.

As Above, So Garage

Breaking Smart • 83 implied HN points • 07 Dec 24
🕹 Technology Engineering Philosophy Innovation Entrepreneurship Mysticism
  1. Hermeticism blends mysticism with practical engineering. It encourages creativity and experimentation, much like how tinkerers and inventors think today.
  2. Modern technology can sometimes feel dull and overly cautious compared to the adventurous spirit of past inventors. The best innovations often come from taking risks and trusting your gut.
  3. The ideal of the 'garage hacker' symbolizes a deeper, more soul-driven approach to innovation, focusing on passion rather than just profits or strict theories.

Why you should analyze the distribution of your Data [Math Mondays]

Technology Made Simple • 59 implied HN points • 14 Mar 23
🕹 Technology Data Analysis Math Software Engineering Modeling Statistics
  1. Analyzing the distribution of your data is crucial for accurate analysis results, helps in choosing the right statistical tests, identifying outliers, and confirming data collection systems.
  2. Common techniques to analyze data distribution include histograms, boxplots, quantile-quantile plots, descriptive statistics, and statistical tests like Shapiro-Wilk or Kolmogorov-Smirnov.
  3. Common mistakes in analyzing data distribution include ignoring or dropping outliers, using the wrong statistical test, and not visualizing data to identify patterns and trends.

What is Generative AI?

Technically • 27 implied HN points • 22 Jul 25
🕹 Technology AI Machine Learning Data science Software Development Innovation
  1. Generative AI predicts not just numbers or yes/no answers but creates full sentences, images, and even videos from prompts.
  2. There are various types of Generative AI models, with the main ones being Transformers for text and Diffusion models for images.
  3. Despite its advancements, Generative AI is still rooted in the basic principles of machine learning, which involves learning patterns from data.

Digital Twins in Supply Chain Management

philsiarri • 22 implied HN points • 11 Aug 25
🕹 Technology AI Manufacturing Logistics Data Simulation
  1. Digital twins are real-time models that reflect physical objects or systems. They help businesses keep track of operations and respond to changes quickly.
  2. Using digital twins can help companies test different scenarios and spot issues before they become big problems. This leads to better decision-making in logistics.
  3. However, challenges like data quality and costs can make it hard to use digital twins effectively. Still, they are becoming popular tools for improving supply chain management.

The 6 reasons why your AI strategy is stalling

Dev Interrupted • 28 implied HN points • 10 Jul 25
🕹 Technology AI Software Engineering Infrastructure Governance
  1. It's not just about having the right tools for AI, but having a solid foundation of knowledge and data. If your information is messy or outdated, the AI won't work well.
  2. Your infrastructure needs to be set up for AI to work smoothly. If it's too complex or manual, it can slow everything down rather than speeding things up.
  3. Governance is important for AI. You need to make sure there are clear rules and oversight to build trust in the system and ensure AI helps rather than harms your workflow.

Visualizing Sound, Lorenz in Blender, and Painterly Shaders

Generative Arts Collective • 92 implied HN points • 09 Nov 24
🕹 Technology Creative Coding Generative Arts 3D Modeling Deep Learning
  1. Using technology like deep learning can help identify nature sounds, like birds, which can be both fun and scientific.
  2. Blender and Python are great tools for visualizing complex concepts, like the Lorenz attractor, in a visually appealing way.
  3. Creating artistic effects in 3D, such as painterly shaders, allows artists to bring unique styles and expressions to their digital work.

AI Roundup 102: The Stargate Project

Artificial Ignorance • 71 implied HN points • 24 Jan 25
🕹 Technology Artificial Intelligence Data Centers Geopolitics Corporate strategy Research & Development
  1. The Stargate Project is a huge partnership by OpenAI, SoftBank, and Oracle to build new AI data centers in the U.S., promising up to $500 billion investment. This is much larger than past projects like the Manhattan and Apollo projects.
  2. China is making fast progress in AI, with new models from companies like DeepSeek that can compete with major Western models. This raises concerns for leading U.S. labs about staying ahead in AI technology.
  3. There are new challenges in measuring AI performance since current benchmarks are not effective anymore. A new test called 'Humanity's Last Exam' highlights this issue as AI systems advance beyond human-level capabilities.

How soon until we can afford robot butlers?

Alex's Personal Blog • 65 implied HN points • 13 Feb 25
🕹 Technology AI Robotics Finance Business News
  1. Robot butlers may become affordable in the near future due to advancements in technology. This could change how we manage household tasks.
  2. Recent investments in AI and robotics indicate a growing market. Companies are receiving significant funding to improve technology and services.
  3. The political landscape is affecting tech policies and decisions. Changes in leadership might lead to new directions for tech regulations and innovations.

The Most Amazing Week in Gen AI Releases

TheSequence • 84 implied HN points • 15 Dec 24
🕹 Technology AI Software Innovation Research Modeling
  1. Several major tech companies like OpenAI, Google, and Microsoft launched new AI models in a single week. This shows how quickly AI technology is progressing.
  2. OpenAI's Sora model allows users to create videos from text descriptions, but it has some limitations. It's an exciting step for video generation!
  3. Google's Gemini 2.0 has improved capabilities, allowing it to handle more complex tasks and interact more effectively with users.

AI, Institutions, and the Future of Human Flourishing with Sam Hammond

Moral Mayhem Podcast • 19 implied HN points • 19 Mar 24
🕹 Technology AI Institutions Ethics Future Humanity
  1. AI can greatly impact how we organize and run our institutions. It's important for us to think about the good and bad effects AI might have on these systems.
  2. Human flourishing should be a priority in discussions about AI. We need to make sure that technology helps people live better lives.
  3. The role of institutions is crucial in shaping a positive future with AI. Strong institutions can guide the development of technology in a way that benefits society.

Taiwan vs. US Chip Subsidies: Bolstering the Sacred Mountain

ChinaTalk • 192 implied HN points • 07 Mar 24
🕹 Technology Semiconductors Incentives Manufacturing
  1. Taiwan allows companies to choose which technologies to invest in, unlike the US and South Korea which target specific areas to strengthen the supply chain.
  2. Taiwanese lawmakers grant significant discretion to government ministries in managing subsidies, in contrast to the US and EU where subsidies are tightly regulated.
  3. Taiwan's central government manages and funds the most significant incentive programs for the semiconductor industry, a strategy that reflects a commitment to enhancing existing strengths.

How do I get everyone to use AI?

The Engineering Manager • 5 implied HN points • 18 Dec 25
🕹 Technology Artificial Intelligence Software Engineering Dev Tools Tech Strategy Productivity
  1. AI adoption follows a J-curve: there’s early hype, a frustrating trough where things feel slower, and then real productivity gains once people and processes adapt.
  2. Forcing AI can work for a few big-brand companies, but heavy mandates usually breed resentment and risk losing good people, so coercion is risky for most orgs.
  3. Help adoption by investing in training, time to experiment, and the right tools, and make a clear business case for costs versus expected gains to get finance on board.

Boeing Reading List

Construction Physics • 208 implied HN points • 31 Jan 24
🕹 Technology Aviation
  1. The aircraft industry has many enthusiasts interested in commercial aircraft aspects for fun.
  2. This post is for paid subscribers only.
  3. There are extremely accurate flight and air traffic control simulators available.

New decisions in a cloudy world

do clouds feel vertigo? • 99 implied HN points • 08 Apr 23
🕹 Technology AI Digital Media Copyright Society Information
  1. AI is creating new divisions in society, leading to more debates about our future and survival. It's making conversations about technology very heated and complex.
  2. Deepfakes and manipulated images are changing how we perceive reality. We can no longer trust everything we see, which can have big implications for privacy and reputation.
  3. In a world full of uncertainty, having a clear mind and being skeptical about information is essential. Embracing ambiguity instead of fearing it can help us navigate changes better.

Clouded Judgement 11.20.25 - The AI Platform Wars

Clouded Judgement • 8 implied HN points • 21 Nov 25
🕹 Technology AI Software Platforms Integration Applications
  1. AI companies are shifting their focus from just improving model quality to creating strong platforms. This means they're not just making better models but also figuring out how to distribute and integrate their services more effectively.
  2. Google is bundling its new Gemini model with all its services, making it a central part of its ecosystem, while OpenAI is creating a super app with ChatGPT to attract users directly to its platform.
  3. Anthropic is aiming for a trusted spot in the enterprise market by prioritizing safety and reliability, while Meta is pushing open-source models to make competition tougher at the base level, encouraging differentiation at higher moments.

Performing Multiple LLM Calls & Voting On The Best Result Are Subject To Scaling Laws

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 19 Mar 24
🕹 Technology AI Machine Learning Data science Systems Design Performance optimization
  1. Making more calls to Large Language Models (LLMs) can help with simple questions but may actually make it harder to answer tough ones.
  2. Finding the right number of calls to use is crucial for getting the best results from LLMs in different tasks.
  3. It's important to design AI systems carefully, as just increasing the number of calls doesn't always mean better performance.

Computer self-help

My Home Office Hacks • 5 implied HN points • 15 Dec 25
🕹 Technology Software Operating Systems Troubleshooting Productivity
  1. Try fixing problems yourself by searching online before calling IT or going to a store; many issues have simple step‑by‑step solutions.
  2. Use built‑in command‑line tools like sfc /scannow and DISM (e.g., DISM.exe /Online /Cleanup-image /Restorehealth) to repair system issues, and run Command Prompt as administrator then reboot.
  3. Learning to follow instructions and try fixes on your own saves time, reduces downtime, and builds confidence working from home.

GroupBy #27: Balancing HDFS DataNodes in the Uber DataLake, How Figma’s databases team lived to tell the scale

VuTrinh. • 19 implied HN points • 19 Mar 24
🕹 Technology Data Engineering Infrastructure Software Development AI/ML Web Technologies
  1. Balancing your data infrastructure is key for efficiency and reliability. Companies like Uber face challenges in maintaining this balance as they scale up their data needs.
  2. Figma's database team has successfully handled a massive growth in data since 2020, showing that scaling can lead to new technical challenges but also growth opportunities.
  3. Optimizing data pipelines can save significant costs. Techniques to reduce data shuffling in processes like Apache Spark can help make data handling more efficient.

Alignment-as-a-Service: Scale AI vs. the new guys

Democratizing Automation • 205 implied HN points • 07 Feb 24
🕹 Technology AI Alignment
  1. Scale AI is experiencing significant revenue growth from data services for reinforcement learning with human feedback, reflecting the industry shift towards RLHF.
  2. Competition in the market for human-in-the-loop data services is increasing, with companies like Surge AI challenging incumbents like Scale AI.
  3. Alignment-as-a-service (AaaS) is a growing concept, with potential for startups to offer services around monitoring and improving large language models through AI feedback.

Land of the Rising Robot

Diane Francis • 399 implied HN points • 05 Aug 21
🕹 Technology Robotics Automation Japan Healthcare Innovation
  1. Japan is a leader in automation and robotics, using technology to solve labor shortages due to its aging population. This means they create robots to do many jobs, helping to keep the economy strong.
  2. The country showcases its robotic innovations, especially during events like the Olympics, where robots assist in hospitality and care roles. This shows how much they trust and embrace technology in everyday life.
  3. Japanese robots are not just for work; they also help with caring for the elderly at home. This includes robots that can make life easier and safer for seniors, proving that technology can improve quality of life.