The hottest Technology Substack posts right now

And their main takeaways
Category
Top Technology Topics

Fit For Purpose

Doomberg • 6134 implied HN points • 26 Dec 24
🕹 Technology Cybernetics Artificial Intelligence Machine Learning Energy
  1. Cybernetics studies how information is used in complex systems, which helps in fields like AI and managing big teams. Understanding this can make complex situations easier to handle.
  2. The principle of POSIWID means that the real purpose of a system is shown by what it actually does, not just what it says it aims for. This can help us see the truth behind many actions and motives.
  3. Current hype around fusion energy suggests it might soon be commercially viable, but we should question if the excitement aligns with real progress or hidden agendas in energy politics.

Humanity’s “Oh shit!” AI moment?

Marcus on AI • 6639 implied HN points • 12 Dec 24
🕹 Technology Artificial Intelligence Machine Learning Cybersecurity Ethics Regulation
  1. AI systems can say one thing and do another, which makes them unreliable. It’s important not to trust their words too blindly.
  2. The increasing power of AI could lead to significant risks, especially if misused by bad actors. We might see more cybercrime driven by these technologies soon.
  3. Delaying regulation on AI increases the risks we face. There is a growing need for rules to keep these powerful tools in check.

AI #125: Smooth Criminal

Don't Worry About the Vase • 2195 implied HN points • 17 Jul 25
🕹 Technology Artificial Intelligence Machine Learning Tech Policy Data Privacy
  1. AI technology is evolving quickly, with language models being adopted for practical uses. However, there are concerns about their safety and reliability in decision-making.
  2. There are important discussions around AI companions and how they might affect human relationships. It's crucial to be cautious about interacting with seemingly friendly AI, as they don't have true understanding or care for users.
  3. Recent debates emphasize the need for proper regulations in AI development. There's a push for transparency and accountability in AI systems to prevent risks associated with their misuse.

Sam Altman Wants $7 Trillion

Astral Codex Ten • 16656 implied HN points • 13 Feb 24
🕹 Technology AI Machine Learning Artificial Intelligence Big Data Computing
  1. Sam Altman aims for $7 trillion for AI development, highlighting the drastic increase in costs and resources needed for each new generation of AI models.
  2. The cost of AI models like GPT-6 could potentially be a hindrance to their creation, but the promise of significant innovation and industry revolution may justify the investments.
  3. The approach to funding and scaling AI development can impact the pace of progress and the safety considerations surrounding the advancement of artificial intelligence.

Did Elon Musk just Mu$k Sam Altman?

Marcus on AI • 5138 implied HN points • 11 Feb 25
🕹 Technology AI Business Investments Competition Corporate Governance
  1. Sam Altman is struggling to keep OpenAI's nonprofit structure, and it's causing financial issues for the company. Investors are not happy with how things are going.
  2. Elon Musk's recent $97 billion bid for OpenAI's nonprofit has complicated the situation. Altman rejected the bid, which makes it tougher for him to negotiate a better deal.
  3. Musk's bid has raised the 'cost' for OpenAI's nonprofit to separate from the for-profit section, adding pressure on Altman and his financial plans.
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Data Science Weekly - Issue 558

Data Science Weekly Newsletter • 219 implied HN points • 01 Aug 24
🕹 Technology Data science Machine Learning AI Data Visualization Statistical Methods
  1. Data science and AI are rapidly evolving fields with plenty of interesting developments. Staying updated with the latest articles and news can really help you understand these changes better.
  2. Effective communication is key in data science. Using intuitive methods and visuals can make complex concepts easier to grasp for everyone.
  3. Using tools and methods like quantization can help make large models more accessible. It's important to find efficient ways to work with vast amounts of data to improve performance.

Analyzing A Critique Of The AI 2027 Timeline Forecasts

Don't Worry About the Vase • 2553 implied HN points • 24 Jun 25
🕹 Technology Artificial Intelligence Modeling Forecasting Data Analysis Automation
  1. Critiques are important for improving forecasts. It's good to get feedback and adjust predictions based on detailed analysis.
  2. Modeling progress in AI is tricky and uncertain. It's not easy to predict how quickly AI will advance, and different methods can give very different results.
  3. Forecasts should be communicated clearly, without overly negative language. Clear messaging helps everyone understand the importance and limitations of the predictions.

AI Video Should Be Illegal

The Algorithmic Bridge • 711 implied HN points • 11 Nov 25
🕹 Technology AI Media Ethics Trust Society
  1. AI video creates deepfakes that can easily mislead people, damaging trust in society. This technology can mimic real people saying harmful things, which is scary and dangerous.
  2. Making AI videos illegal could protect society from misinformation, but it might also shield corrupt people from accountability. It's a tricky balance between safety and justice.
  3. Instead of banning AI videos, society might need to adapt its approach to trusting and verifying information. If everyone expects deepfakes, then finding the truth may become even harder.

AI still lacks “common” sense, 70 years later

Marcus on AI • 5968 implied HN points • 05 Jan 25
🕹 Technology Artificial Intelligence Machine Learning Robotics Cognitive Science Data science
  1. AI struggles with common sense. While humans easily understand everyday situations, AI often fails to make the same connections.
  2. Current AI models, like large language models, don't truly grasp the world. They may create text that seems correct but often make basic mistakes about reality.
  3. To improve AI's performance, researchers need to find better ways to teach machines commonsense reasoning, rather than relying on existing data and simulations.

New prototype is with the fab house

Single Board ESP32 ZX Spectrum • 439 implied HN points • 29 Jun 24
🕹 Technology Prototyping Firmware 3D Printing
  1. The new prototype is now in production after some delays, showing the importance of taking action despite fears.
  2. The process of sending the boards off involved some challenges with component availability, requiring adjustments.
  3. Future plans involve exploring software options, experimenting with hardware possibilities, and considering 3D printed cases.

AI and the Future of Human Autonomy

The Grand Redesign • 19 implied HN points • 15 Oct 24
🕹 Technology AI Automation Innovation Cybersecurity Ethics
  1. We should not limit AI too much. Trying to control it too tightly can backfire and prevent it from being truly helpful and innovative.
  2. AI should be trained on the best human data, not just average or flawed examples. The quality of what we put into AI will shape how it helps us.
  3. AI development should be open and transparent. Working behind closed doors can lead to issues, while open collaboration allows for better improvements and wider benefits for everyone.

Hard-forked! Casey Newton’s distorted portrait of Gary Marcus and AI skepticism

Marcus on AI • 6679 implied HN points • 06 Dec 24
🕹 Technology AI Machine Learning Data Ethics Tech Policy Regulation
  1. We need to prepare for AI to become more dangerous than it is now. Even if some experts think its progress might slow, it's important to have safety measures in place just in case.
  2. AI doesn't always perform as promised and can be unreliable or harmful. It's already causing issues like misinformation and bias, which means we should be cautious about its use.
  3. AI skepticism is a valid and important perspective. It's fair for people to question the role of AI in society and to discuss how it can be better managed.

My ADHD vs. the AlarmKit API

Jacob’s Tech Tavern • 1968 implied HN points • 28 Jul 25
🕹 Technology Software APIs Apple Development Productivity
  1. Setting alarms is crucial for daily management. They help keep a structured life, especially for those who might forget tasks easily.
  2. Apple's AlarmKit API allows users to create their own timers and alarms. This new feature can enhance control and personalization over reminders.
  3. Understanding how AlarmKit works can empower users to improve their productivity. It’s an exciting tool for anyone looking to manage their time better.

The First Hit Generative AI Product After ChatGPT? Somehow, It’s Snapchat+

Big Technology • 17388 implied HN points • 05 Jan 24
🕹 Technology AI Social media Generative AI Subscription Messaging
  1. Snapchat+ is a popular AI-powered subscription service with generative AI features.
  2. The success of Snapchat+ shows that generative AI may be best as a feature within existing apps rather than standalone products.
  3. Generative AI technology is being utilized to enhance user experiences and could be a new revenue stream for companies.

At least five things for your weekend (#30)

Noahpinion • 15235 implied HN points • 09 Mar 24
🕹 Technology Energy Social media Urban planning
  1. Consumer sentiment may not always align with economic fundamentals like interest rates or unemployment, showing the influence of 'vibes' and media narratives.
  2. Tokyo and Seoul have a unique city development pattern with gradually sloping density, allowing for more people without feeling crowded, achieved through upzoning suburbs and excellent train systems.
  3. The age of energy abundance is upon us as technologies like solar power and batteries become cheaper, alongside increased fossil fuel drilling in the U.S.

What comes next, if Claude Code is as good as people say.

The Future, Now and Then • 198 implied HN points • 15 Jan 26
🕹 Technology Artificial Intelligence AI Ethics Automation Startups Research tools Internet culture
  1. Powerful AI agents can autonomously build and launch products and startups, letting individuals generate quick, small incomes with very little effort.
  2. Because the tools are widely available, those early gains will be copied and flooded across the internet, creating lots of low-quality, indistinguishable offerings and collapsing the initial market advantage.
  3. In science and academia, AI will boost individual productivity but steer research toward easy, AI-friendly topics, making evaluation more about taste than discovery and risking long-term harm unless institutions consciously adapt.

What's a Forward Deployed Engineer?

Technically • 26 implied HN points • 05 Mar 26
🕹 Technology Enterprise Software AI Data Infrastructure Startups Sales Product
  1. A Forward Deployed Engineer (FDE) is a highly technical, customer-facing engineer who embeds with customers to build custom solutions and then generalizes those learnings into the core product.
  2. The FDE model is exploding because deploying AI and other complex systems is uncertain and rapidly changing, so companies want real experts to clear the fog and make things work in production.
  3. Enterprise sales are slow and messy—security, procurement, legacy systems, and institutional inertia mean white‑glove support is often needed, so FDEs can help win big deals but they’re costly and not right for every startup.

Top Links 948 Data centers replace offices. AI replaces teachers. Poems on petroleum & the war on Bohemia.

Chartbook • 386 implied HN points • 11 Dec 25
🕹 Technology AI Data Centers Remote work Education Infrastructure
  1. Data centers are becoming more popular than offices as remote work increases. This shows a big change in how we think about workspaces.
  2. AI is starting to take over roles that used to be filled by teachers. This raises questions about the future of education.
  3. There are interesting discussions happening about poetry related to oil and cultural issues. It highlights how art reflects important social themes.

Where will AI be at the end of 2027? A bet

Marcus on AI • 6007 implied HN points • 30 Dec 24
🕹 Technology Artificial Intelligence Human-computer interaction AI Policy Machine Learning
  1. A bet has been placed on whether AI can perform 8 out of 10 specific tasks by the end of 2027. It's a way to gauge how advanced AI might be in a few years.
  2. The tasks include things like writing biographies, following movie plots, and writing screenplays, which require a high level of intelligence and creativity.
  3. If the AI succeeds, a $2,000 donation goes to one charity; if it fails, a $20,000 donation goes to another charity. This is meant to promote discussion about AI's future.

New Is The New Black

Software Design: Tidy First? • 1612 implied HN points • 15 Aug 25
🕹 Technology Software Design Learning Consulting Innovation Education
  1. Trying new things can be hard, but it's essential for learning. Embrace the unfamiliar instead of being afraid of it.
  2. When you feel lost while learning, take a break. Clearing your mind can help you reset and make connections later.
  3. When you start to understand something, slow down and think carefully. This moment is special and deserves focus.

The Substack AI Report

Substack • 1915 implied HN points • 24 Jul 25
🕹 Technology AI Tools Content creation Publishing Research Productivity
  1. About 45% of publishers on Substack are using AI tools, mainly for tasks like research and proofreading rather than full content creation.
  2. While many appreciate how AI helps with productivity, there are concerns about losing personal creativity and the risks of plagiarism or ethical issues.
  3. Younger publishers tend to use AI for translation and writing help, while older ones focus more on research and image generation, showing a divide in how AI is used based on age.

The Sequence Knowledge #680: Can we Evaluate Creativity in AI Models?

TheSequence • 2297 implied HN points • 08 Jul 25
🕹 Technology AI Creativity Benchmarks Research Evaluation
  1. Evaluating creativity in AI is tricky because creativity involves personal feelings and tastes. Researchers have created special tests to help measure how creative AI really is.
  2. There are different benchmarks available to assess AI creativity, focusing on originality and emotional impact. These benchmarks help researchers understand how well AI can mimic human-like creativity.
  3. OpenAI's HumanEval benchmark is one important tool that helps measure AI's ability to write code creatively. It plays a key role in assessing how AI can perform tasks that require innovative thinking.

Codex Built My Startup In A Weekend

Sudo Apps • 32 implied HN points • 27 Feb 26
🕹 Technology AI Software Dev Tools Automation Architecture Startups Product
  1. Writing code is no longer the main bottleneck — modern coding models can build working products and CLIs in days, making implementation much cheaper.
  2. Different models have different strengths: Codex follows explicit direction and executes quickly, while models like Opus infer missing details and act more like a senior engineer.
  3. The human role shifts to architecture and judgment — engineers must plan systems end-to-end, define clear acceptance criteria, manage failure modes, and focus on product tradeoffs.

Is AI Over-Hyped?

Fake Noûs • 436 implied HN points • 06 Dec 25
🕹 Technology AI Automation History Philosophy Ethics Society Science
  1. AI is probably over-hyped — so many extreme claims make it unlikely we're underestimating its importance.
  2. History shows dramatic tech predictions often miss the mark. Real innovations change lives but usually in unexpected ways, and current AI has been helpful without being transformative for most people.
  3. Current large language models learn from text patterns and lack real-world understanding, so they are unlikely by themselves to solve the deepest scientific problems or produce genuinely new insights.

"Cache me" if you can!

System Design Classroom • 659 implied HN points • 01 Jun 24
🕹 Technology Software Systems Data Engineering Architecture
  1. The type of caching strategy you choose depends on your read and write ratios. If you read a lot, caching is very helpful, but if you write often, you need a more complex approach.
  2. Data consistency is crucial for some applications. Using methods like Write-Through helps keep data in cache and databases aligned, while other methods, like Write-Behind, prioritize speed over immediate consistency.
  3. To see if your caching is effective, you should track metrics like how many times data is successfully retrieved from the cache versus not retrieved. This will help you understand how well your caching is working.

An AI rumor you won’t want to miss

Marcus on AI • 7153 implied HN points • 10 Nov 24
🕹 Technology AI Deep Learning Scaling Data Computing
  1. The belief that more scaling in AI will always lead to better results might be fading. It's thought we might have reached a limit where simply adding more data and computing power is no longer effective.
  2. There are concerns that scaling laws, which have worked before, are just temporary trends, not true laws of nature. They don’t actually solve issues like AI making mistakes or hallucinations.
  3. If rumors are true about a major change in the AI landscape, it could lead to a significant loss of trust in these scaling approaches, similar to a bank run.

OpenAI's masterplan for ChatGPT, and Concierge Internet

Enterprise AI Trends • 316 implied HN points • 24 Dec 25
🕹 Technology Artificial Intelligence Platforms Developer Tools Product Strategy User Experience Monetization Integrations
  1. ChatGPT is shifting from a text-only chatbot to a more visual, interactive experience with dynamic/generative UI like cards and GUI-style responses.
  2. The Apps SDK lets third-party developers inject interactive experiences and deep integrations, making ChatGPT the central context manager across multiple apps rather than just a data connector.
  3. This strategy both creates new ad and engagement surfaces and, more importantly, aims to lock users into a single pane of glass for productivity by owning cross-app context and workflows.

How Substack's follow feature betrays its original mission

Taylor Lorenz's Newsletter • 7643 implied HN points • 28 Oct 24
🕹 Technology Social media Content creation Digital marketing User Experience
  1. The follow feature on Substack helps creators gain visibility but makes them lose ownership of their audience. This is a shift from Substack's original purpose of allowing creators to connect directly with their subscribers.
  2. Writers are now juggling between growing their follower counts and keeping their newsletter subscriptions growing. This split can make them feel pressured to create even more content, complicating their strategies.
  3. Substack's follow feature could confuse users, as some may think they are subscribed when they're only following. Educating users on this difference could help creators maintain stronger connections with their audience.

2025: The Year in Review

Gonzo ML • 252 implied HN points • 06 Jan 26
🕹 Technology Artificial Intelligence Machine Learning Hardware Research Software Ethics Infrastructure
  1. 2025 was the year of agents — they’re being built into every product and API, but many still fail often and lag traditional reliability standards, so expect more focus on making them robust.
  2. Code agents and agentic tools for science made big practical gains, with autonomous multi-step work across repositories and early successes in automated research and math.
  3. The hardware and model landscape shifted: TPUs and strong Chinese open models reduced dependence on a single vendor, AGI hype cooled with timelines pushed out, and world-model research kept advancing.

4.3.1 Skin Depth & Litz Wire

Fields & Energy • 299 implied HN points • 17 Jul 24
🕹 Technology Electronics Engineering Physics Energy
  1. Skin depth refers to how electric current mainly flows close to the surface of a wire, especially at high frequencies. This means most of the current doesn't penetrate deep into the conductor.
  2. Litz wire is made up of many fine strands that help reduce resistance by allowing current to flow through a larger area. This is especially useful at high frequencies where skin depth is very small.
  3. Using litz wire not only reduces energy loss due to resistance but also makes wires more flexible and less likely to fail mechanically compared to solid wires.

Data Science Weekly - Issue 560

Data Science Weekly Newsletter • 139 implied HN points • 15 Aug 24
🕹 Technology Data science AI Machine Learning Software Development Programming
  1. The Turing Test raises questions about what it means for a computer to think, suggesting that if a computer behaves like a human, we might consider it intelligent too.
  2. Creating a multimodal language model involves understanding different components like transformers, attention mechanisms, and learning techniques, which are essential for advanced AI systems.
  3. A recent study tested if astrologers can really analyze people's lives using astrology, addressing the ongoing debate about the legitimacy of astrology among the public.

“Sometimes I Forget I'm Paralyzed.” How Neuralink’s First Patient Found Freedom by Connecting His Brain to a Computer.

Big Technology • 6004 implied HN points • 18 Dec 24
🕹 Technology Artificial Intelligence Health tech Neuroscience Innovation Medical Devices
  1. Noland Arbaugh, a quadriplegic, was able to control a computer with his mind after getting a Neuralink device implanted. This technology allows him to communicate and interact with others in ways he couldn't before.
  2. Neuralink's goal is to connect human brains to computers, helping people with disabilities regain some lost functions. Arbaugh's participation in the first human trial symbolizes hope for future advancements in brain-computer interfaces.
  3. The ethical implications of brain technology are significant. While it can be used for good, like helping those with disabilities, there are risks and potential for misuse that society will need to address.

Google could become a major security player in the next few years

Frankly Speaking • 50 implied HN points • 12 Feb 26
🕹 Technology Cybersecurity Cloud Computing Artificial Intelligence Enterprise Software Infrastructure M&A Identity
  1. Google could become a major security player by consolidating essential "plumbing" tools like SSO, EDR, and email into a neutral infrastructure layer, with Wiz providing visibility and Gemini automating workflows. This would let builders customize and remediate problems instead of battling closed, admin-focused tools.
  2. AI is collapsing the per-seat SaaS and point-product model; security must scale with code, agents, and automation rather than more headcount. Organizations that automate extensively shorten breach lifecycles and lower costs.
  3. Google’s vertical integration—cloud, Workspace, and a powerful AI model—plus usage-based pricing and targeted acquisitions could make it a builder-friendly alternative to legacy security vendors. That positioning plays to engineers who want API-first, customizable infrastructure rather than proprietary, admin-heavy systems.

Artificial Intelligence

Doomberg • 293 implied HN points • 19 Dec 25
🕹 Technology Machine Learning AI Policy Automation Research Ethics Software Data science
  1. AI is the defining topic of 2025 and is likely to shape the year ahead.
  2. As the cost of cognitive work approaches zero, AI will drastically change how work and value are produced, so understanding it is essential.
  3. There are pro-level paid briefings and learning notes available for people who want deeper, practical insight into AI’s implications.

Crossrail 2 ...and a big pile of rubbish

Odds and Ends of History • 469 implied HN points • 08 Dec 25
🕹 Technology Innovation Research Infrastructure Science AI
  1. The London Assembly wants the Mayor to restart planning for HS2 and is looking into Crossrail 2 construction updates.
  2. There is a big pile of rubbish in Oxfordshire causing concern and discussions about local waste management.
  3. A new proposal for national laboratories aims to innovate and create breakthrough technologies in the UK.

Hotel California

benn.substack • 5421 implied HN points • 10 Jan 25
🕹 Technology Digital Culture Artificial Intelligence Social media Virtual reality Data Privacy
  1. Moving large amounts of gold or money isn't easy, as it requires trust and logistics, unlike digital transactions which can be done quickly with a few clicks.
  2. In our digital world, many people feel disconnected from reality, as they spend so much time on their devices and forget the hard work behind everyday things.
  3. Natural disasters can't be controlled or fixed with technology; they remind us that no app can change the basic laws of nature or the complexities of life.

Model-Market Fit

Nicolas Bustamante • 179 implied HN points • 19 Jan 26
🕹 Technology Artificial Intelligence Machine Learning Startups Product Strategy Model Evaluation
  1. A model must be capable of doing the core job before product-market fit can happen; if the underlying AI can’t reliably deliver the task, great UX or marketing won’t make customers adopt it.
  2. When a model crosses a capability threshold, a whole vertical can grow fast, and the winners are usually teams that had already built domain-specific data, workflows, and trust to take advantage of that moment.
  3. If Model-Market Fit is missing, human-in-the-loop becomes a crutch and you must decide to wait for model improvements or invest now in long-term assets; a simple MMF test is whether the model, given the same inputs as a human, produces production-quality output without significant correction.