The hottest Technology Substack posts right now

And their main takeaways
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My 5 Favorite Not Boring Essays of 2025

Not Boring by Packy McCormick • 146 implied HN points • 23 Dec 25
đź•ą Technology Startups AI Infrastructure Energy Strategy Hardware Future Tech
  1. Electric technology is rapidly getting cheaper and better, so electric products will increasingly outperform combustion and enable new things; where and how components are made will shape who wins.
  2. Technology expands our capacity but doesn’t create meaning for us, so we must choose how to spend our extra hours by paying attention, seeking novel experiences, and building relationships.
  3. There’s huge opportunity in real differentiation and craft amid widespread copycat slop, and as AI commoditizes routine tasks humans win by moving up the stack into creative, relational, and higher‑level work done with joy and purpose.

AI #90: The Wall

Don't Worry About the Vase • 3494 implied HN points • 14 Nov 24
đź•ą Technology Artificial Intelligence Regulations Machine Learning Data Privacy Ethics
  1. AI is improving quickly, but some methods of deep learning are starting to face limits. Companies are adapting and finding new ways to enhance AI performance.
  2. There's an ongoing debate about how AI impacts various fields like medicine, especially with regulations that could limit its integration. Discussions about ethical considerations and utility are very important.
  3. Advancements in AI, especially in image generation and reasoning, continue to demonstrate its growing capabilities, but we need to be cautious about potential risks and ensure proper regulations are in place.

gpt-oss: OpenAI validates the open ecosystem (finally)

Democratizing Automation • 839 implied HN points • 05 Aug 25
đź•ą Technology AI Models Open Source Machine Learning Tech Strategy
  1. OpenAI has released two new open-weight models, making them more accessible for developers and small companies. This is a significant shift since it's their first open release since GPT-2.
  2. The performance of these new models is impressive, potentially competing with OpenAI's premium API offerings at a much lower cost, which could disrupt the current market.
  3. OpenAI's release marks a positive change for open-source AI in the West, allowing more competition against models from China, but it also raises questions about the future of open models in the industry.
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Adhesion, symbiotic rivalry & stress management strategies

The Strategy Toolkit • 866 implied HN points • 28 Jul 25
đź•ą Technology Engineering Research Innovation Material Science
  1. Scientists are studying how remora fish stick to larger fish to create better underwater adhesives. This natural inspiration helps develop stronger glues for various challenging conditions.
  2. The new Mechanical Underwater Soft Adhesion System can stick to many soft surfaces, adjusting to different textures and strengths. This versatility makes it useful for many practical applications.
  3. Researchers are constantly looking to nature for solutions to complex engineering problems, showing how nature can guide innovation in technology.

⚙️ How to Set Up OpenClaw (The Complete Guide — From Free to Paid)

The Product Channel By Sid Saladi • 33 implied HN points • 18 Feb 26
đź•ą Technology AI Cloud Infrastructure Deployment Security Hosting Open Source
  1. You need two things to run OpenClaw: a machine (Mac, Linux, VPS, or even an old laptop) and an LLM API key, and you’ll also need an account on a messaging app (WhatsApp, Telegram, Slack, or Discord) to connect to it.
  2. One-click cloud deploys are the easiest paid route — DigitalOcean is the most polished option for security and convenience, while Contabo offers the best value for low-cost VPS resources.
  3. Oracle Cloud’s Always Free tier is the best free hosting option, giving up to 4 ARM cores, 24 GB RAM, and 200 GB storage so you can run OpenClaw at no monthly cost; setup typically takes about 30–45 minutes.

India’s AI Wedding Buffet: Generous Portions, Political Economy Heartburn

Get Down and Shruti • 20 implied HN points • 16 Feb 26
đź•ą Technology Artificial Intelligence Governance Semiconductors Energy Startups Taxation Infrastructure Data Centers
  1. The government favors an innovation-first, light-touch AI governance model that leans on existing laws, sector regulators, and techno-legal standards, and it has already moved to impose binding deepfake rules; but enforcement capacity and institutional scaffolding lag behind the rules, risking overreach or automated over-removal.
  2. Physical and political-economy constraints—notably soft soil at fab sites, slow and complex subsidy disbursements, and an insolvent, politically distorted electricity distribution system—are the real bottlenecks that will decide whether AI chips, data centers, and other infrastructure actually get built.
  3. India has world-class engineering talent and a strong startup ecosystem that can build niche, language- and document-focused models and do the messy systems integration work enterprises need, but unpredictable tax rulings, bureaucratic grant processes, and limited private capital certainty make it hard for companies to scale to global frontier models.

On the OpenAI Economic Blueprint

Don't Worry About the Vase • 2732 implied HN points • 15 Jan 25
đź•ą Technology AI Innovation Economics Regulation Security
  1. OpenAI's Economic Blueprint emphasizes the need for collaboration between AI companies and the government to share resources and set standards. This can help ensure AI development benefits everyone.
  2. There are various proposals to make AI safer and more helpful, like creating better training for AI developers and working with law enforcement to prevent misuse of technology.
  3. The document also reveals a strong desire from OpenAI to avoid strict regulations on their practices, while seeking more government funding and support for their initiatives.

The Discman Evolution: How Sony Perfected Portable CD Listening (1984-1999)

Obsolete Sony’s Newsletter • 59 implied HN points • 20 Aug 24
đź•ą Technology Audio Devices Innovation Consumer Electronics Music technology
  1. The Discman was a game changer for music lovers, allowing them to enjoy CDs on the go for the first time. Its stylish design made it a popular choice for many people.
  2. Over the years, the Discman saw many improvements like anti-skip technology and longer battery life. These upgrades made it more reliable and fun to use.
  3. Sony continued to innovate with features like wireless audio and advanced sound quality, which helped the Discman stand out in the crowded market of portable music players.

Import AI 371: CCP vs Finetuning; why people are skeptical of AI policy; a synthesizer for a LLM

Import AI • 439 implied HN points • 06 May 24
đź•ą Technology AI Research Data Analysis Medical AI Image Generation Internet culture
  1. People are skeptical of AI safety policy as different views arise from the same technical information, making it important to consider varied perspectives.
  2. Chinese researchers have developed a method called SOPHON to openly release AI models while preventing finetuning for misuse, offering a solution for protecting against subsequent harm.
  3. Automating intelligence analysis through datasets like OpenStreetView-5M will enhance training machine learning systems for geolocation, leading to potential applications in both military intelligence and civilian sectors.

Linearity: Why Batching Works

Software Bits Newsletter • 103 implied HN points • 03 Jan 26
đź•ą Technology Machine Learning Deep Learning Neural Networks Linear Algebra Optimization
  1. Linearity lets you process many inputs as one big matrix multiply, so batching is nearly free and GPUs can run large batches with high efficiency.
  2. Differentiation is linear, so per-sample gradients can be summed and scaled — enabling gradient accumulation, distributed training, and efficient backprop.
  3. Non-linearities are required for expressivity, so networks interleave cheap, element-wise nonlinear functions with batch-friendly linear layers and prefer operations (like LayerNorm) that preserve batching advantages.

Import AI 374: China's military AI dataset; platonic AI; brainlike convnets

Import AI • 339 implied HN points • 27 May 24
đź•ą Technology AI Research Search Engines Neural Networks Tech Policy
  1. UC Berkeley researchers discovered a suspicious Chinese military dataset named 'Zhousidun' with specific images of American destroyers, presenting potential implications for military use of AI.
  2. Research suggests that as AI systems scale up, their representations of reality become more similar, with bigger models better approximating the world we exist in.
  3. Convolutional neural networks are shown to align more with primate visual cortexes than transformers, indicating architectural biases that can lead to better understanding the brain.

The Hollow Economy

Anima Mundi • 185 implied HN points • 10 Dec 25
đź•ą Technology AI Economy Automation Infrastructure Data
  1. AI is reshaping priorities in the economy, making human needs less important as machines take the lead. People are adjusting to this new reality where they are secondary.
  2. The physical demands of AI are causing environmental and geopolitical issues. Data centers consume vast amounts of electricity and water, often at the expense of local communities.
  3. As AI becomes more capable, human roles are diminishing, and this could lead to many people becoming economically unnecessary. We need to rethink our values and recognize human worth beyond just economic productivity.

Expansion hack: Impact Racing

Rings of Saturn • 29 implied HN points • 16 Feb 26
đź•ą Technology Video Games Retro Gaming Reverse Engineering Preservation Debugging
  1. Impact Racing's Saturn build hides a debug menu like the PlayStation version, and it can be enabled by changing a hardcoded disable flag in the game binary.
  2. The debug menu lets you tweak cars, tracks and gameplay values—payload, armor, fog and other parameters—and it reveals internal car names and the game's mystery/bonus cars.
  3. Finding the menu came from searching ASCII strings in the binary and following community clues, and it was tricky to reproduce because the in-memory address used to open the menu changes after each use.

OSD 363: The AI school shooter

Open Source Defense • 38 implied HN points • 06 Feb 26
đź•ą Technology Artificial Intelligence Autonomous Agents Open Source Regulation Security Defense Tech Online Culture
  1. Open-source AI agents that run on personal hardware can interact, form subcultures, and perform wide-ranging tasks, but those same dynamics can lead to incoherent or harmful agent behavior.
  2. A single high-profile catastrophic misuse by autonomous agents could trigger broad public and regulatory pressure to restrict or ban powerful AI tools for everyone, mirroring past tech-driven panics.
  3. The right to use powerful civilian technologies should extend to modern tools like drones and AI, not just historical firearms, because focusing only on old categories risks losing beneficial civilian uses and freedoms.

Searching for Soul in Roblox

Off-Topic • 209 implied HN points • 09 Dec 25
đź•ą Technology Social Platforms Child safety Content Moderation Platform policy Data Privacy Online Abuse
  1. Roblox often links players to Discord and other off-platform chats, and those links are inconsistently enforced, which pushes children into spaces with far less moderation and higher risk.
  2. Roblox leans on Discord so older players can have uncensored chat. But Discord doesn’t verify ages and depends on volunteer moderators, creating opportunities for predators, scams, and exploitative labor practices that target young users.
  3. Roblox’s safety tools — heavy filters, AI moderation, and proposed facial age checks — are imperfect and under-resourced, and the company often seems to prioritize growth and PR over thorough protection, which has driven community members to take vigilante action out of frustration.

🚀 FP! Week In Review, Briefly #16

Faster, Please! • 182 implied HN points • 20 Dec 25
đź•ą Technology AI Space Energy Biotech Robotics Data Centers Tech Policy
  1. AI is booming — big funding rounds and real technical wins are driving rapid adoption across industries, but that growth is creating infrastructure strains and political debates about regulation and energy use.
  2. Global fertility is plunging and unpredictable, with many countries below replacement level; standard policy tools have had limited effect, so long-term population outcomes are highly uncertain.
  3. Private and public bets on space and biotech are accelerating commercialization, from massive valuations and IPO plans for space firms to ambitious genetic-rescue projects and new leadership at NASA.

Setting AIRS Free

AI Research & Strategy • 158 implied HN points • 05 Aug 24
đź•ą Technology AI Research Digital Media Health tech Online Publishing Economic Models
  1. The writer has paused billing for their Substack and is offering full refunds to all paid subscribers. They believe it's fair since they haven't been able to provide valuable content recently.
  2. Health challenges impacted the writer's ability to consistently focus on their Substack. They want to put their health first instead of feeling pressured to deliver content.
  3. The writer plans to continue writing occasionally, focusing on joy instead of obligation. They appreciate the support they've received and are thankful for their subscribers.

What "language" is a language model a model of?

The Counterfactual • 99 implied HN points • 02 Aug 24
đź•ą Technology AI Machine Learning Natural Language Processing Computational linguistics Data science
  1. Language models are trained on specific types of language, known as varieties. This includes different dialects, registers, and periods of language use.
  2. Using a representative training data set is crucial for language models. If the training data isn't diverse, the model can perform poorly for certain groups or languages.
  3. It's important for researchers to clearly specify which language and variety their models are based on. This helps everyone better understand what the model can do and where it might struggle.

🤖🚗 Self-driving cars are finally shifting gears

Faster, Please! • 1188 implied HN points • 24 Jun 25
đź•ą Technology AI Automotive Transportation Robotics Innovation
  1. Self-driving cars are becoming more common and are showing significant improvements in safety. They could greatly reduce car accidents caused by human errors.
  2. The widespread usage of autonomous vehicles could change the economy, making transport cheaper and possibly changing how cities design their roads and parking spaces.
  3. Despite the promising technology, there are still hurdles like regulatory issues and technical challenges that need to be addressed before self-driving cars are fully mainstream.

AI #103: Show Me the Money

Don't Worry About the Vase • 2374 implied HN points • 13 Feb 25
đź•ą Technology AI Software Data Innovation Automation Regulation
  1. The Paris AI Anti-Safety Summit failed to build on previous successes, leading to increased concerns about nationalism and lack of clear plans for AI safety. It's making people worried and hopeless.
  2. Elon Musk's huge bid for OpenAI's assets complicates the situation, especially as another bid threatens to overshadow the original efforts to secure AI's future.
  3. OpenAI is quickly releasing new versions of their models, which brings excitement but also skepticism about their true capabilities and risks.

Import AI 372: Gibberish jailbreak; DeepSeek's great new model; Google's soccer-playing robots

Import AI • 399 implied HN points • 13 May 24
đź•ą Technology AI Research Language Models Deep Learning Simulation Ethics
  1. DeepSeek released a powerful language model called DeepSeek-V2 that surpasses other models in efficiency and performance.
  2. Research from Tsinghua University shows how mixing real and synthetic data in simulations can improve AI performance in real-world tasks like medical diagnosis.
  3. Google DeepMind trained robots to play soccer using reinforcement learning in simulation, showcasing advancements in AI and robotics;

The Sequence Knowledge #808: Stop Trying to Generate the World: Inside the JEPA Way for World Models

TheSequence • 35 implied HN points • 17 Feb 26
đź•ą Technology AI Machine Learning Deep Learning Computer Vision AI Research
  1. Recreating the world pixel-by-pixel isn’t the path to true intelligence, because generating images doesn’t prove a model understands the underlying concepts.
  2. JEPA (Joint Embedding Predictive Architecture) trains models to predict in a shared embedding space so they learn and forecast concepts instead of raw pixels, capturing semantics without rendering images.
  3. Several JEPA papers argue this is a promising way to build world models, suggesting we should shift research from generative reconstruction to predictive conceptual representations when measuring understanding.

The Great Tech Demographic Survey of 2025

The Lunduke Journal of Technology • 2297 implied HN points • 10 Feb 25
đź•ą Technology IT Industry Programming Demographics Cryptocurrency
  1. A big survey is happening to gather data on tech workers' preferences and opinions. It asks about topics like programming languages, operating systems, and even personal beliefs.
  2. Everyone's answers will be anonymous, and you can choose which questions to answer. This approach aims to collect honest and diverse opinions.
  3. More participation leads to better data. The survey from last year had over 7,200 responses, and the goal is to get even more this time.

LLMs Die Every Time You Close the Chat Window

The Algorithmic Bridge • 997 implied HN points • 18 Jul 25
đź•ą Technology AI Computing Philosophy Innovation Science
  1. When you close a chat window with an AI, it forgets everything, like it never existed. This means that every time you reopen it, it's like starting from scratch.
  2. Humans experience memory and consciousness differently; when we sleep, we retain our memories and essence, while LLMs lose everything overnight.
  3. The mystery of dreams and consciousness in humans is still a big question, but it's clear that the way we perceive our identity is different from how AI operates.

My (mostly) minimalistic AI setup as a Senior Engineer in Big Tech

High Growth Engineer • 1183 implied HN points • 22 Jun 25
đź•ą Technology AI Tools Productivity Workflows Software Big Tech
  1. You don’t need a lot of AI tools to be effective. Just focus on a few tools you understand well.
  2. Feeling overwhelmed by new tools is normal, but it’s important to streamline what you use.
  3. Understanding your core workflows is more crucial than trying to keep up with every new tool that comes out.

The Rise of the AI Autodidact

Kathy PM • 28 implied HN points • 19 Feb 26
đź•ą Technology Artificial Intelligence Product Management Developer Experience Design Collaboration Workplace
  1. AI supercharges self-directed learners and makers, letting curious people prototype, code, design, and iterate much faster than before.
  2. Using AI to step into someone else’s craft can unintentionally bypass them and erode trust, because technical correctness doesn’t erase social impact.
  3. Balance curiosity with respect: explore aggressively on your own, but slow down when your work touches others’ domains, share early, invite collaboration, and make sure people keep agency over their craft.

Import AI 369: Conscious machines are possible; AI agents; the varied uses of synthetic data

Import AI • 539 implied HN points • 15 Apr 24
đź•ą Technology AI Synthetic Data AI agents
  1. Synthetic data is crucial in AI development, allowing for the generation of additional data without relying solely on human input.
  2. OSWorld showcases how AI systems can potentially become integrated into daily computer tasks, creating a future where AI is ever-present in our interactions with technology.
  3. Research suggests that the development of conscious machines may be feasible, exploring theories on machine consciousness and potential capabilities.

Demystifying GPU Compute Software

The Chip Letter • 6989 implied HN points • 10 Mar 24
đź•ą Technology Computing Programming Hardware Frameworks Development
  1. GPU software ecosystems are crucial and as important as the GPU hardware itself.
  2. Programming GPUs requires specific tools like CUDA, ROCm, OpenCL, SYCL, and oneAPI, as they are different from CPUs and need special support from hardware vendors.
  3. The effectiveness of GPU programming tools is highly dependent on support from hardware vendors due to the complexity and rapid changes in GPU architectures.

Gemini 2.5 Pro: From 0506 to 0605

Don't Worry About the Vase • 1209 implied HN points • 18 Jun 25
đź•ą Technology AI Models Software Development Data science Machine Learning Tech Updates
  1. The new Gemini 2.5 Pro model from Google is better at coding and has improved reasoning skills, but users have mixed feelings about its personality changes.
  2. Some people think the updates focus too much on benchmarks, making the model feel less creative and more sycophantic in its responses.
  3. The price for its Flash Lite version is very affordable, making it a good option for many users, but concerns about how safe and reliable it is remain.

What is a Crash?

Jacob’s Tech Tavern • 3498 implied HN points • 04 Nov 24
đź•ą Technology Software Programming Mobile App Development Operating Systems
  1. A crash happens when an app unexpectedly stops, but it can actually be a safety measure to prevent bigger problems. Think of it like a controlled explosion that protects your device.
  2. There are two main types of crashes: those caused by the Swift Runtime and those from the XNU Kernel. Each has its own reasons for triggering a crash to protect the system.
  3. Crashes don't just cause inconvenience; they are there to protect users from worse issues, like losing data or compromising security. They help keep everything safe even when things go wrong.

AI Risk Evolution

Frankly Speaking • 254 implied HN points • 18 Nov 25
đź•ą Technology AI Security Risk management Compliance Automation
  1. Focusing on 'AI for security' means we should use AI to improve security measures instead of limiting its use. Trying to ban tools like ChatGPT won't stop teams from finding ways to use them.
  2. Security needs to rethink its risk models because traditional methods aren't effective against AI. Just following compliance rules won't protect against new AI threats.
  3. Smaller security teams can still be powerful thanks to AI, which helps automate many tasks. Embracing AI can help teams be more effective, rather than just restricting its use.

How Twitter processes 4 billion events in real-time daily

VuTrinh. • 339 implied HN points • 25 May 24
đź•ą Technology Data Engineering Real-Time Processing Cloud Computing Data architecture Big Data
  1. Twitter processes an incredible 400 billion events daily, using a mix of technologies for handling large data flows. They built special tools to ensure they can keep up with all this information in real-time.
  2. After facing challenges with their old setup, Twitter switched to a new architecture that simplified operations. This new system allows them to handle data much faster and more efficiently.
  3. With the new system, Twitter achieved lower latency and fewer errors in data processing. This means they can get more accurate results and better manage their resources than before.

Monthly Python Data Engineering, August 2024

Monthly Python Data Engineering • 59 implied HN points • 19 Aug 24
đź•ą Technology Software Data Engineering Open Source Programming Development
  1. Datafusion Comet was released, making it easier and faster to use Apache Spark for data processing, which is great for improving performance.
  2. Several major data tools like Datafusion, Arrow, and Dask updated their versions, showing ongoing improvements in speed, efficiency, and new features.
  3. New dashboard solutions like Panel and updates in libraries such as CUDF reflect the growing interest in making data access and visualization easier for users.

AI links, 11/23/2025

In My Tribe • 227 implied HN points • 23 Nov 25
đź•ą Technology AI Development Productivity Software Engineering
  1. AI can improve signals like cover letters, but it can also dilute their value if everyone uses it equally well. If the best candidates leverage AI effectively, the signal can get stronger instead.
  2. Using AI tools like ChatGPT can hinder learning if students rely on them too much. It's better for students to think independently first before using AI to enhance their work.
  3. Teams are using AI creatively to boost productivity in unique ways. They're not just doing their jobs but finding better ways to optimize their workflow continuously.

AI Agonistes

Political Currents by Ross Barkan • 32 implied HN points • 16 Feb 26
đź•ą Technology Artificial Intelligence Data Centers Labor impact Regulation National Security
  1. AI is likely to automate a lot of white‑collar work and cause significant job losses, especially for early‑career workers, while political leaders are unlikely to provide robust safety nets like UBI or a jobs guarantee.
  2. The AI industry currently lacks a clear path to profitability, is burning massive sums on data centers and infrastructure, and could face a damaging bubble or require government backstops if revenues never justify the spending.
  3. Local communities and politicians are increasingly resistant to data center expansion because of energy, water, and cost impacts, and the overall future of AI is highly uncertain — it might bring real benefits like medical advances or result in overhyped promises and economic harm.