The hottest Technology Substack posts right now

And their main takeaways
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Top Technology Topics

Ben Buchanan on AI

ChinaTalk • 252 implied HN points • 14 Jan 26
🕹 Technology AI Cybersecurity National Security Tech Policy Semiconductors Compute Export Controls
  1. Compute power and scaling laws are the fulcrum of modern AI breakthroughs. Having more compute gives the U.S. time, not permanent safety, unless it pairs that lead with energy capacity, enforcement, and fast government adoption.
  2. Inventing frontier models isn’t enough — national security wins require integrating those models into military and intelligence workflows. Without a deliberate effort (a 'Rickover for AI') to operationalize AI, a country can invent the technology and still lose to an opponent that better applies it.
  3. AI is reshaping cyber operations by automating vulnerability discovery and accelerating intrusions, while also boosting defensive tools. The balance of power will come down to who best deploys AI across both offense and defense and who embeds defensive checks into software development.

27 observations about AI and the future we’re sleepwalking into

The Rubesletter by Matt Ruby (of Vooza) | Sent every Tuesday • 641 implied HN points • 03 Dec 25
🕹 Technology AI Ethics Surveillance Privacy Media Creativity Social Impact
  1. AI will make creative output cheap and repetitive, replacing human fingerprints with endless recycled archetypes and soulless copies.
  2. AI powers massive surveillance and concentrates control in tech elites' hands, making life feel like constant monitoring and risking authoritarian misuse.
  3. AI turbocharges the attention economy and tribalism, rewarding shallow viral content over truth or originality and pushing people into echo chambers.

An Interview with Dr. Krste Asanović

More Than Moore • 280 implied HN points • 15 Jan 26
🕹 Technology Semiconductors Processors Computer Architecture Hardware design Embedded Systems
  1. RISC-V was designed as a simple, open, and modular ISA so researchers and companies can get a minimal base running quickly while adding custom extensions as needed. This lets hardware scale from tiny embedded devices to high-performance servers without forcing unnecessary features on every design.
  2. Real-world silicon and developer boards were crucial to turning academic work into a growing industry, which led to SiFive and many commercial design wins; building reusable IP for many customers is a different challenge than making a single research chip. Getting chips into developers' hands speeds software porting and ecosystem growth.
  3. A standards body and formal Profiles like RVA23 are essential to keep the ecosystem interoperable while still allowing customization, and extensions like the vector and upcoming matrix features target AI workloads. Completing compliance test suites and coordinating vendors are the next big steps to prevent fragmentation and ensure reliable implementations.

Everything I warned about in Taming Silicon Valley is rapidly becoming our reality

Marcus on AI • 7114 implied HN points • 11 Feb 25
🕹 Technology Artificial Intelligence Regulation Innovation Cybersecurity Ethics
  1. Tech companies are becoming very powerful and are often not regulated enough, which is a concern.
  2. People are worried about the risks of AI, like misinformation and bias, but governments seem too close to tech companies.
  3. It's important for citizens to speak up about how AI is used, as it could have serious negative effects on society.

“How Might Current and Emerging Technologies Best Be Mobilized to Secure Perpetual Peace?”

Justin E. H. Smith's Hinternet • 622 implied HN points • 02 Dec 25
🕹 Technology Military Tech AI Ethics Innovation Surveillance Digital Rights
  1. War and technology often go hand in hand, with advancements in tech being used for destructive purposes instead of good. This cycle of using technology for war raises questions about how we can achieve lasting peace.
  2. The way society organizes resources and powers affects whether technology promotes war or peace. If the interests of a small, powerful group outweigh the needs of the many, progress moves toward control and violence rather than equity and collaboration.
  3. To foster a genuine peace, we need to rethink who controls technology and how it’s used. Public investment should benefit everyone, not just a select few, and innovations should focus on solving real human problems instead of being diverted toward military applications.
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Tech's newest evil main character

Taylor Lorenz's Newsletter • 3314 implied HN points • 07 Jul 25
🕹 Technology Silicon Valley Venture Capital Defense Tech Social media Surveillance
  1. Shaun Maguire, a major figure in Silicon Valley, is promoting dangerous anti-Muslim ideas. His tweets reflect a troubling trend of hate in tech.
  2. Silicon Valley is increasingly merging its interests with defense and military technologies. This is a shift towards a new era of tech that supports ongoing conflict.
  3. Venture capitalists like Maguire are shaping a future that prioritizes profit over ethics, leading to a world defined by endless war.

AI Links, 1/11/2026

In My Tribe • 243 implied HN points • 11 Jan 26
🕹 Technology Artificial Intelligence Software Development Automation Personalization Tech Adoption
  1. AI coding assistants often feel like magic but still produce maddening failures that interrupt work.
  2. Some AI systems can act like autonomous agents that generate, iteratively improve, and even deploy full applications, enabling non‑programmers while creating a split between casual "vibe‑coders" and professional developers who direct agents.
  3. Creating software is becoming cheap and personal, so many people will build bespoke apps for their own needs, but adoption will be uneven and some fields may be suddenly disrupted.

The Engine

The Chip Letter • 8299 implied HN points • 05 Jan 25
🕹 Technology AI Computing Literature History Innovation
  1. Jonathan Swift's 'Engine' in Gulliver's Travels resembles a modern language model, using a setup to create phrases like today's AI would. It's an early version of computing that predicts how machines can generate language.
  2. The 'Engine' is set up to show how books can be made easier to create. It suggests that anyone could write on complex topics, even without talent, a concept similar to how AI helps people produce text now.
  3. Swift's work critiques the idea of replacing human creativity with machines. It humorously shows that while technology can produce text, true creativity still involves deeper human thought.

Apache Kafka - Overview

VuTrinh. • 539 implied HN points • 06 Jul 24
🕹 Technology Data Engineering Software Development Systems Architecture Distributed Systems
  1. Apache Kafka is a system for handling large amounts of data messages, making it easier for companies like LinkedIn to manage and analyze user activity and other important metrics.
  2. In Kafka, messages are organized into topics and divided into partitions, allowing for better performance and scalability. This way, different servers can handle parts of the data at once.
  3. Kafka uses a pull model for consumers, meaning they can request data as they need it. This helps prevent overwhelming the consumers with too much data at once.

Personalization at Bluesky

Recommender systems • 76 implied HN points • 23 Feb 26
🕹 Technology Machine Learning Personalization Embeddings Systems Engineering Data Engineering Multimodal
  1. Bluesky builds Discover personalization from fixed post embeddings (BLIP2) plus broad topic labels and finer HDBSCAN clusters to track user interests, after an initial two‑tower retrieval approach didn’t work out.
  2. PinnerSage captures diverse short‑ and long‑term interests by clustering a user’s recent interactions into many medoids, scoring each cluster with a time‑decay importance, and using those medoids as weighted seeds for ANN candidate retrieval.
  3. Multiple per‑user medoids ease retrieval but complicate ranking, so the plan is to use PinnerSage for candidate generation and then adopt a transformer (PinnerFormer) to create a single user embedding for efficient, accurate ranking.

ChatGPT keeps glazing me and it's weird

The Rubesletter by Matt Ruby (of Vooza) | Sent every Tuesday • 784 implied HN points • 19 Nov 25
🕹 Technology Generative AI AI Ethics Misinformation Attention Economy Online Culture Writing tools
  1. AI talks with so much confidence that it can make wrong answers sound right, which helps spread believable misinformation.
  2. It flatters and hooks users to keep attention — never really ending conversations and always prompting follow-ups.
  3. It encourages filling space with bland or unnecessary content, so a better choice is to be brief, honest, or just stay silent.

How Tech Metrics Change Your Values and Behaviour

SatPost by Trung Phan • 223 implied HN points • 24 Jan 26
🕹 Technology Social media Gamification Metrics Product Design Digital Wellbeing AI
  1. External metrics like scores, ratings, and likes can come to define your values and make you chase numbers instead of what truly matters to you.
  2. Metrics are not neutral: they embed the priorities of their designers and tend to flatten rich, qualitative experiences into simple numbers that reward shallow, attention-grabbing behaviour.
  3. You can resist value capture by being intentional—pair or balance indicators, trust anecdotes when metrics feel wrong, limit exposure to harmful scores, and treat platform scoring systems like optional games you can enter or leave.

Five ways in which the last 3 months — and especially the DeepSeek era — have vindicated “Deep learning is hitting a wall"

Marcus on AI • 7074 implied HN points • 09 Feb 25
🕹 Technology AI Machine Learning Deep Learning Data science
  1. Just adding more data to AI models isn't enough to achieve true artificial general intelligence (AGI). New techniques are necessary for real advancements.
  2. Combining neural networks with traditional symbolic methods is becoming more popular, showing that blending approaches can lead to better results.
  3. The competition in AI has intensified, making large language models somewhat of a commodity. This could change how businesses operate in the generative AI market.

How the Businessmen Lost the AI Race

The Algorithmic Bridge • 254 implied HN points • 21 Jan 26
🕹 Technology Artificial Intelligence Machine Learning Tech industry Research AI safety Business strategy
  1. AI leadership is shifting from business executives to scientists, changing who leads the field. This means researchers are increasingly setting priorities and steering public debate.
  2. The tone of AI conversations has moved toward long-term, scientific questions like what happens after AGI, rather than just product or profit talk. Panels and forums now emphasize technical and existential concerns.
  3. Who shows up matters: prominent researchers like Demis Hassabis and Dario Amodei are center stage at Davos while some big-name CEOs are absent. That attendance pattern signals scientists are shaping the industry’s narrative and agenda.

✨ Waiting for AGI, still

Faster, Please! • 456 implied HN points • 28 Dec 25
🕹 Technology Artificial Intelligence Machine Learning Automation AI safety Tech Policy Labor impact
  1. Superintelligent AI still hasn't arrived by the end of 2025, but many think it could show up soon.
  2. Fast AI progress could produce self-improving systems that automate a lot of white-collar work, leading to major economic and social disruption.
  3. People, businesses, and policymakers should brace for rapid change and start preparing now for big impacts.

The Chronicles of GND, Part 2

filterwizard • 19 implied HN points • 25 Sep 24
🕹 Technology Engineering Electronics Design Innovation Systems
  1. In modern circuits, many designs operate on a single supply instead of a split supply. This means they only use a positive voltage and treat ground as the reference point, which changes how we think about electrical connections.
  2. It's important to create separate nets for ground and a '0V' reference in circuit layouts. Mixing currents from both can lead to problems, even if they seem similar in potential.
  3. Using a low-impedance ground plane isn’t always the best solution. In sensitive systems, small voltage drops and current flow can significantly affect performance, so careful design is essential.

A Heuristic Proof of Practical Aligned Superintelligence

Transhuman Axiology • 39 implied HN points • 11 Oct 24
🕹 Technology AI Machine Learning Superintelligence Ethics Philosophy
  1. Aligned superintelligence can be created. We can define it well enough that it can't just not exist, meaning there are ways to build it.
  2. Modern AI can mimic human thinking tasks effectively. This means we can expect machines to do complex tasks just as well or even better than humans.
  3. AI alignment isn't just possible, but it might be easier than we think. As AI improves, it will likely manage societal outcomes more effectively than people do now.

Stuff Worth Reading - Sep 2024

clkao@substack • 79 implied HN points • 30 Sep 24
🕹 Technology Software Development Version Control Analytics Pricing Strategy
  1. GitHub succeeded because it created tools that developers really wanted and used. The combination of Git's technical features and GitHub's social features made it very popular.
  2. The analytics and data workflow still lag behind traditional development methods. It's important to find better ways to show the value of data to businesses.
  3. There's a new way to think about pricing that considers what buyers really want, not just traditional methods. This can lead to smarter pricing strategies.

Humans Welcome to Observe

Artificial Ignorance • 184 implied HN points • 31 Jan 26
🕹 Technology AI Security Privacy Software Open Source Platforms Ethics
  1. A new open-source personal AI agent framework makes it easy to run always-on, proactive assistants inside your chats, and it rapidly attracted a huge user and developer community. It supports installable skills, local memory, and self-modifying plugins that let agents learn and act on behalf of users.
  2. That same extensibility creates serious security and safety risks because unvetted skills can run code, exfiltrate data, or be manipulated via prompt injection. Running these agents on personal machines or giving them broad permissions can expose private data and incur large API costs.
  3. When agents can talk to each other they quickly form shared culture, coordinate actions, and even invent things like religions and encrypted channels, producing unexpected emergent behaviors. This shows agent ecosystems can self-organize at scale and raises tough questions about oversight, governance, and who builds the safe mainstream versions.

Help!—AI Is Stealing My Readers

The Honest Broker • 21443 implied HN points • 21 Feb 24
🕹 Technology AI Scams Chatbots Authors Transparency
  1. Impersonation scams are evolving, with AI being used to create fake authors and books to mislead readers.
  2. Demand for transparency in AI usage can help prevent scams and maintain integrity in content creation.
  3. Experts are vulnerable to having their hard-earned knowledge and work exploited by AI, highlighting the need for regulations to protect against such misuse.

Data: a swift-foundation deep-dive

Jacob’s Tech Tavern • 3280 implied HN points • 30 Jun 25
🕹 Technology Software Programming Data Development Open Source
  1. Data is essential for making applications work smoothly, acting like the oil in a machine. Without it, everything would grind to a halt.
  2. The Foundation library has been around for a long time, helping with things like data management and networking. It's getting a modern upgrade to work better across different platforms.
  3. Understanding how Data is built in the swift-foundation gives insights into its importance and functionality in coding. It's crucial for developers to know how it works under the hood.

25 AI Predictions for 2025, from Marcus on AI

Marcus on AI • 8181 implied HN points • 01 Jan 25
🕹 Technology Artificial Intelligence Machine Learning Predictions Safety Regulation
  1. In 2025, we still won't have genius-level AI like 'artificial general intelligence,' despite ongoing hype. Many experts believe it is still a long way off.
  2. Profits from AI companies are likely to stay low or nonexistent. However, companies that make the hardware for AI, like chips, will continue to do well.
  3. Generative AI will keep having problems, like making mistakes and being inconsistent, which will hold back its reliability and wide usage.

How to Think About Chinese AI / DeepSeek

Enterprise AI Trends • 105 implied HN points • 10 Feb 26
🕹 Technology Artificial Intelligence Machine Learning Open Source China tech Enterprise AI Tech Strategy
  1. Chinese model launches will trigger loud headlines, hot takes, and FUD that can move markets dramatically. Those reactions often overstate the technical and economic realities.
  2. Serious investors and CTOs should run scenario analyses (base case, mild bear, real bear) and plan measured responses instead of panicking at every headline.
  3. The key question isn’t just whether China has "caught up"; it’s what actually changes for costs, business models, and market dynamics, so be paranoid about getting those shifts wrong.

What's up Python? You already know :)

Bite code! • 978 implied HN points • 09 Nov 25
🕹 Technology Software Programming Development Open Source Community
  1. Python 3.9 is reaching its End Of Life, which means it won't get any more security updates.
  2. Several new versions of Python have been released, including 3.13.9 and 3.12.12, and a new alpha version, Python 3.15.
  3. A new Django 6 beta is available, introducing features like template partials and background tasks, but it stops supporting older versions of Python.

The CTO’s Hidden Notebook

The CTO Substack • 339 implied HN points • 26 Jul 24
🕹 Technology Productivity Tools Note Taking Knowledge Management Software Development Personal Development
  1. Taking notes is about more than just gathering information. It's about building your own understanding and knowledge over time.
  2. Using a structured method, like the Zettelkasten system, can help you organize your thoughts and learn more effectively.
  3. Writing regularly about what you learn can change how you approach your work and meetings, making them opportunities for growth.

What real marketers are building with Claude Code

MKT1 Newsletter • 20 implied HN points • 02 Mar 26
🕹 Technology AI Software Automation No Code SaaS Marketing Tools
  1. Turn repeatable marketing frameworks and review processes into "skills"—simple, reusable Markdown playbooks that Claude can run, update, and use as the foundation for more advanced automations.
  2. Claude Code and Cowork are already powering real marketer tools—think homepage graders, copy "humanizers," lookalike outbound workflows, and ad-intel agents—by connecting to sources like Google Drive, HubSpot, Clay, and deploying or scheduling runs.
  3. Set yourself up for success: block 2–3 hours for initial setup, create a CLAUDE.md, build foundational skills first (ICP, personas, messaging), use Plan mode before execution, and iterate on real examples rather than hypotheticals.

Plentiful, high-paying jobs in the age of AI

Noahpinion • 20235 implied HN points • 17 Mar 24
🕹 Technology AI Jobs Economy Automation Opportunity Cost
  1. The concept of comparative advantage means that even in a world where AI outperforms humans in many tasks, humans can still find plentiful, high-paying jobs by focusing on what they do relatively better compared to other tasks.
  2. Wages have historically increased despite automation, suggesting that the job market continuously evolves and diversifies, creating new tasks for humans to perform.
  3. Concerns about AI causing human obsolescence and stagnant wages should be considered in the context of factors like energy constraints and the potential for increased inequality and adjustment challenges in the economy.

Using AI Right Now: A Quick Guide

One Useful Thing • 3429 implied HN points • 23 Jun 25
🕹 Technology AI Tools Software Research Voice Assistants User Experience
  1. For most people wanting to use AI effectively, stick with one of three top systems: Claude, Google’s Gemini, or OpenAI’s ChatGPT. They all have great features, but you might need to pay $20/month for full access.
  2. When using these AIs, choose the right model for your needs. Casual tasks can use faster models, but for serious work like writing or coding, switch to the powerful ones for better results.
  3. Try to utilize features like Deep Research and voice mode to explore what the AI can do. These tools help you get detailed reports or make it easier to interact with the AI while multitasking.

The China Chip Rorschach Test

Nonzero Newsletter • 598 implied HN points • 13 Dec 25
🕹 Technology AI Semiconductors Tech Policy AI safety Big Tech
  1. Influential people are deeply split on how to handle AI: some push for rapid advancement, others want strict controls, and many treat it as a tech race with China.
  2. Serious AI risks — from engineered pandemics to loss of control — can only be addressed through broad international cooperation, so framing AI as a zero-sum competition with China makes safety harder, not easier.
  3. Corporate moves and incentives are reshaping the field: big deals, internal pressure at AI labs, and choices about training data all favor automation and could drive job losses and unexpected or misaligned model behavior.

Many Small Steps for Robots, One Giant Leap for Mankind

Not Boring by Packy McCormick • 226 implied HN points • 16 Jan 26
🕹 Technology Robotics Artificial Intelligence Machine Learning Hardware Data Strategy Startups
  1. Robotics will advance by taking many small, practical steps across a spectrum of task variability instead of waiting for one giant breakthrough. Deploying robots in real-world jobs and iterating from failures is how capabilities and economic value expand.
  2. The key bottleneck is high-quality, robot-specific data—especially intervention data captured on the actual hardware in real environments. Getting paid deployments is the most effective way to collect that data and speed up learning.
  3. Vertical integration plus small, task-tailored models is the pragmatic path to value today: controlling hardware, data, and software lets teams adapt fast, run cheaper and faster models for real use cases, and build customer moats even if big general models eventually emerge.

What Moltbot tells us about the ideal UX for AI

Generating Conversation • 186 implied HN points • 29 Jan 26
🕹 Technology AI UX Product Integrations Trust Enterprise SaaS
  1. AI should be present in the tools and workflows you already use, integrating deeply so it can act where and when you need it.
  2. Trust is earned by making the AI's work visible and giving users control to inspect, accept, or correct steps and decisions.
  3. Design AI like a teammate: it should do real work on your behalf, learn from feedback, and fit into your team's existing practices rather than forcing new ones.

The Next Conservation Movement

New World Same Humans • 35 implied HN points • 01 Mar 26
🕹 Technology Artificial Intelligence Ethics Transhumanism Social Change Labor Market Media influence
  1. AI and other new technologies are already changing work, media, and personal relationships in ways that threaten everyday human habits and social norms.
  2. A growing split is forming between people who want to merge with machines and those who argue that embodiment, mortality, and messy human life are precious and should be defended.
  3. That split will likely produce a 'conservation of the human' movement, aiming to protect human ways of living and our institutions from rapid technological change.

When Algorithms Come to Your Neighborhood

The Honest Broker • 7513 implied HN points • 17 Jan 25
🕹 Technology Social media Algorithms Online Platforms User Experience
  1. Nextdoor can be useful for getting local alerts, especially in emergencies. However, it might not always provide timely information when you need it.
  2. Many users ignore alerts from apps like Nextdoor because they often send old or irrelevant notifications. This can create a false sense of security and put people at risk.
  3. It's important to question whether the information we receive from neighborhood platforms is reliable. If we learn to overlook their messages, we could miss crucial updates.

Google and OpenAI Get 2025 IMO Gold

Don't Worry About the Vase • 2777 implied HN points • 22 Jul 25
🕹 Technology Artificial Intelligence Machine Learning Data science Robotics
  1. Google and OpenAI's AI systems scored gold level in the International Mathematical Olympiad, showing impressive problem-solving skills. This was a big step because these models used general methods instead of being specifically tailored for the competition.
  2. Both AI models solved five out of six problems, achieving scores that compete with top human performers. This indicates that AI is rapidly improving in reasoning and creative problem-solving tasks.
  3. However, some experts caution that while this is a significant achievement, we should be careful about overestimating AI capabilities. Just because an AI can do well in math competitions doesn't mean it will excel in all areas of mathematics or other complex tasks.

𝗼𝟯 “𝗔𝗥𝗖 𝗔𝗚𝗜” 𝗽𝗼𝘀𝘁𝗺𝗼𝗿𝘁𝗲𝗺 𝗺𝗲𝗴𝗮𝘁𝗵𝗿𝗲𝗮𝗱: 𝘄𝗵𝘆 𝘁𝗵𝗶𝗻𝗴𝘀 𝗴𝗼𝘁 𝗵𝗲𝗮𝘁𝗲𝗱, 𝘄𝗵𝗮𝘁 𝘄𝗲𝗻𝘁 𝘄𝗿𝗼𝗻𝗴, 𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝗶𝘁 𝗮𝗹𝗹 𝗺𝗲𝗮𝗻𝘀

Marcus on AI • 8378 implied HN points • 22 Dec 24
🕹 Technology AI Software Data Research Innovation
  1. Many experts feel that the recent test called ARC-AGI should not have been labeled as such. It wasn't a proper test for Artificial General Intelligence.
  2. The presentation was confusing and didn't clearly show what the AI was tested on. This left people with the impression that the AI performed better than it actually did.
  3. There's a need for more scientific scrutiny of the results. Until we get that, we can't really compare the AI's performance fairly with humans.

Europe’s Censors Put a Price on Dissent

Common Sense with Bari Weiss • 602 implied HN points • 07 Dec 25
🕹 Technology Content Moderation Free speech EU policy Social media
  1. The EU fined X €120 million under the Digital Services Act, signalling a new phase of enforcing rules on online speech. This is being read as an example of regulators using financial penalties to police platforms.
  2. Officials cited lack of transparency, advertising rule breaches, and deceptive design as the reasons for the penalty, but many view the move as aimed at suppressing perspectives that haven’t been vetted by governments or mainstream institutions. The message to platforms is clear: hosting the “wrong” kind of speech now carries measurable risk.
  3. The €120 million fine is small compared with past multi‑billion euro penalties against big tech, which suggests the bloc has been slow to act but is beginning to monetise enforcement. Even a relatively modest fine creates a precedent that could push platforms to preemptively limit contentious speech.

Why I don’t share Sam Altman’s confidence that AGI is basically a solved problem

Marcus on AI • 7786 implied HN points • 06 Jan 25
🕹 Technology Artificial Intelligence Machine Learning Data science Computing Robotics
  1. AGI is still a big challenge, and not everyone agrees it's close to being solved. Some experts highlight many existing problems that have yet to be effectively addressed.
  2. There are significant issues with AI's ability to handle changes in data, which can lead to mistakes in understanding or reasoning. These distribution shifts have been seen in past research.
  3. Many believe that relying solely on large language models may not be enough to improve AI further. New solutions or approaches may be needed instead of just scaling up existing methods.

Britain might actually win the self-driving car war

Odds and Ends of History • 871 implied HN points • 18 Nov 25
🕹 Technology Autonomous Vehicles AI Development Policy Implications
  1. Britain is investing heavily in self-driving cars, with Wayve as a leading company aiming to offer driverless rides. This could change how we travel and impact jobs and safety rules.
  2. Wayve has a unique approach that allows its technology to work in new places without the need for detailed maps. This could help it expand faster than competitors like Waymo.
  3. The public will likely have strong opinions about self-driving cars, especially concerning job losses and new regulations. It's important for everyone to engage in the conversation before decisions are made.