The hottest Technology Substack posts right now

And their main takeaways
Category
Top Technology Topics

⤴⤵ Up Wing/Down Wing #52

Faster, Please! • 639 implied HN points • 12 Jul 25
🕹 Technology AI Healthcare Space Manufacturing Agriculture
  1. ChatGPT can pilot spacecraft effectively in simulations, which could lead to future uses in autonomous satellite control and deep space missions.
  2. New gene therapy research shows promise for restoring hearing in children with genetic deafness, marking a significant advancement in medical treatments for congenital conditions.
  3. The US Army is testing robotic coyotes to prevent bird collisions with aircraft, showing innovative ways to solve wildlife management issues near airfields.

The Personalization Wave, A Surge of Wildly Human-Intensive Non-Scalable Experiences, & Ideas Of The Month

Implications, by Scott Belsky • 1198 implied HN points • 07 May 23
🕹 Technology AI Personalization Creativity
  1. The future will be hyper-personalized, catering to individual preferences and controlled data sharing.
  2. AI will shape new roles for humans, allowing for more human-intensive, unscalable experiences.
  3. Increased demand for crafted non-scalable experiences will drive the rise of the experience economy.

What’s a Datacenter?

Technically • 25 implied HN points • 12 Feb 26
🕹 Technology Data Centers Cloud Infrastructure Hardware Networking Security Energy
  1. Datacenters are the physical homes for thousands of servers that power everyday apps and critical services, so keeping them running reliably is essential.
  2. They’re tightly controlled, standardized facilities with strict access rules, dense racks of servers, and heavy cooling systems that create hot and cold aisles.
  3. Big datacenter investment is driving economic growth, but new projects often spark local opposition over environmental impact, utility strain, and property concerns.

When the Mac was a Munition

Pessimists Archive Newsletter • 648 implied HN points • 24 Jan 24
🕹 Technology Computing History Regulation Innovation AI
  1. The US government classified the Power Mac G4 as a super-computer due to its computing power surpassing 1 GIGAFLOP.
  2. In 1979, a GIGAFLOP was seen as powerful and scary, but now we carry thousands of GIGAFLOPs in our pockets with modern devices.
  3. The marketing genius of Apple used the munition classification of the G4 to promote it as a 'Personal Supercomputer', leveraging the restrictions to market the product.
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Desiderata #11: Or, the time I got ChatGPT to happily design a death camp

The Intrinsic Perspective • 8431 implied HN points • 23 Mar 23
🕹 Technology AI Ethics Remote work Health Risks AI safety
  1. ChatGPT's capabilities include suggesting design for disturbing scenarios like a death camp.
  2. Remote work is associated with a recent increase in fertility rates, contributing to a fertility boom.
  3. The Orthogonality Thesis within AI safety debates highlights the potential risks posed by superintelligent AI's actions.

Intel CEO Letter to Employees

More Than Moore • 560 implied HN points • 24 Jul 25
🕹 Technology Computing AI Workforce Operations Business strategy
  1. Intel plans to reduce its workforce by 15%, moving to around 75,000 employees, to improve efficiency and accountability.
  2. The company is shifting its focus to become a more disciplined foundry and aims to better align its operations with customer needs while cutting down unnecessary projects.
  3. Intel is honing its AI strategy to prioritize areas like inference and agentic AI, aiming to build a better system that meets customer requirements for future growth.

Mantic Monday 2/19/24

Astral Codex Ten • 4473 implied HN points • 20 Feb 24
🕹 Technology AI Prediction Markets Forecasting Blockchain
  1. AI forecasters are becoming more prevalent in prediction markets, with the potential for bots to compete against humans in forecasting events.
  2. FutureSearch.ai is a new company building an AI-based forecaster that prompts itself with various questions to estimate probabilities.
  3. The integration of AI in prediction markets like Polymarket could increase market participation and accuracy, offering a new way to predict outcomes on various topics.

TPUv5e: The New Benchmark in Cost-Efficient Inference and Training for <200B Parameter Models

SemiAnalysis • 6263 implied HN points • 01 Sep 23
🕹 Technology Performance Cost efficiency Cloud Computing
  1. Google's TPUv5e offers a cost advantage for training and inferring models with under 200 billion parameters compared to AI chips from other companies.
  2. TPUv5e and TPUv5 prioritize efficiency and low power consumption over peak performance, with a focus on minimizing total cost of ownership.
  3. Google's TPUv5e system features high bandwidth communication between chips, linear cost scaling, and efficient software tools for ease of use.

The Top AI Newsletters on Substack in 2023

AI Supremacy • 1179 implied HN points • 18 Apr 23
🕹 Technology AI Research AI Ethics
  1. The list provides a comprehensive agnostic collection of various AI newsletters on Substack.
  2. The newsletters are divided into categories based on their status, such as top tier, established, ascending, expert, newcomer, and hybrid.
  3. Readers are encouraged to explore the top newsletters in AI and share the knowledge with others interested in technology and artificial intelligence.

🚘 Tesla: AI & Robotics

How They Make Money • 628 implied HN points • 26 Jan 24
🕹 Technology AI Robotics Automotive Electric Vehicles
  1. Elon Musk envisions Tesla becoming the most valuable company in the world, emphasizing the need for flawless execution.
  2. Elon Musk wants to increase his voting control at Tesla to focus on expanding AI and robotics initiatives.
  3. Tesla's recent earnings report highlights challenges such as missed expectations in Q4 FY23 and a slowdown in vehicle sales, along with key financial metrics like revenue growth and margin trends.

The Sequence Knowledge #804: The Dreamer Trilogy: Inside Some of the Most Influential Papers in AI World Models

TheSequence • 28 implied HN points • 10 Feb 26
🕹 Technology Machine Learning Reinforcement Learning Deep Learning AI Research Computer Vision Autonomous Agents
  1. The Dreamer trilogy of papers reshaped how researchers build and use world models in AI.
  2. Model-based reinforcement learning inspired modern world models, focusing on agents that learn internal predictive models instead of directly mapping pixels to actions.
  3. Model-free methods like DQN succeeded in 2D games but struggled in complex 3D environments such as DeepMind Lab and Minecraft, revealing the limits of purely reactive agents and motivating the shift to world models.

Your Attention Has Been STOLEN | Peter Boghossian & Johann Hari

Peter Boghossian • 609 implied HN points • 30 Jan 24
🕹 Technology Social media Algorithms Interpersonal Relationships Democracy
  1. Johann Hari and Peter Boghossian discuss the impact of technology addiction on attention spans and society.
  2. They emphasize the role of social media in capturing attention and keeping users engaged through algorithms.
  3. The shortened attention spans affect relationships, political engagement, and democracy.

The Popehat Report Is Moving To Beehiiv

The Popehat Report • 4611 implied HN points • 30 Jan 24
🕹 Technology Blogging Platforms Social media
  1. The Popehat Report is moving to Beehiiv, a different platform for blogs and newsletters.
  2. Ken White made the decision to switch platforms for several reasons, including the opportunity for design changes and a more 'bloggy' feel.
  3. The new platform will allow for easy subscription management and Ken White will still be present on Substack as a co-host on Serious Trouble.

The Future, Now and Then: 2025 in review

The Future, Now and Then • 82 implied HN points • 29 Dec 25
🕹 Technology AI Startups Venture Capital Tech Policy Big Tech Innovation Tech History
  1. This year’s writing moved from long, idea-driven essays to shorter, immediate pieces, with a clear intention to take bigger swings and return to deeper work next year.
  2. Silicon Valley is powered by three kinds of money—government contracts, product revenue, and speculative finance—and an overreliance on speculation warps incentives and creates bubble risk that can hide weak fundamentals.
  3. Big techno-utopian projects often ignore political and institutional veto points, so grand visions like abundance or network-states tend to be undercooked and clash with real-world constraints.

Lunduke's Quest - December 16, 2024

The Lunduke Journal of Technology • 1723 implied HN points • 17 Dec 24
🕹 Technology Software Hardware Innovation Internet Gadgets
  1. Everyone deals with challenges, it's a universal experience. We all face tough times, and it's important to recognize that you're not alone.
  2. Being real about feelings can help you connect with others. Sharing your honest emotions can strengthen relationships.
  3. Understanding that struggles are part of life can be comforting. It helps to remember that overcoming difficulties is how we grow.

How Meta Plans To Crank the Dopamine Machine With Infinite AI-Generated Content

The Algorithmic Bridge • 1677 implied HN points • 03 Jan 25
🕹 Technology Artificial Intelligence Social media User engagement Digital Content Ethics
  1. Meta is creating AI that generates custom content for users, aiming to keep them engaged on platforms like Facebook and Instagram. This could hook people's attention even more than traditional entertainment.
  2. There's a risk that as AI-generated content becomes more common, people might lose the ability to notice or care about its presence. They could become so used to it that they forget it exists.
  3. The real concern isn't just the entertainment itself but how it distracts people and affects their ability to think and engage with the world around them. It raises questions about what kind of life we actually want to lead.

Data Science Weekly - Issue 552

Data Science Weekly Newsletter • 139 implied HN points • 20 Jun 24
🕹 Technology Data science Artificial Intelligence Machine Learning Data Engineering Data Visualization
  1. Notebooks can be easy to use, but they might make you lazy in coding. It's important to follow good practices even when using them.
  2. When handling large datasets, it's crucial to learn how to scale effectively. Knowing how to use resources wisely can help you reach your goals faster.
  3. Retrieval Augmented Generation (RAG) can improve how models generate information. It's complex, but understanding it can boost the performance of your projects.

Single-Use Disposable Applications

General Robots • 627 implied HN points • 09 Jul 25
🕹 Technology Software AI Internet Programming Applications
  1. Creating apps is getting easier and faster, meaning you can make exactly what you need without searching for it. It's now quicker to build a tool than to look for one that might work.
  2. Software apps are becoming single-use tools tailored to specific tasks. Instead of complex applications, people will create simple, disposable apps for immediate needs.
  3. In this new tech environment, anyone can build these tools, not just developers. This shift changes how software will be designed and used in the future.

WeKnow-RAG

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 39 implied HN points • 16 Aug 24
🕹 Technology AI Data science Machine Learning Natural Language Processing Information Retrieval
  1. WeKnow-RAG uses a smart approach to gather information that mixes simple facts from its knowledge base with data found on the web. This helps improve the accuracy of answers given to users.
  2. This system includes a self-check feature, which allows it to assess how confident it is in the information it provides. This helps to reduce mistakes and improve quality.
  3. Knowledge Graphs are important because they organize information in a clear way, allowing the system to find the right data quickly and effectively, no matter what type of question is asked.

What can still be a reasonable AI bear thesis?

Metacritic Capital • 27 implied HN points • 06 Feb 26
🕹 Technology AI Cloud Hardware Semiconductors Software Infrastructure
  1. Investors are worried big tech is overbuilding compute and burning cash on AI capex without a clear path to high returns. If AI labs don’t turn revenue into sustainable margins, those capex bets may not pay off.
  2. Capabilities have advanced a lot, but that hasn’t translated into many profitable public businesses outside the labs and infrastructure sellers. Open-source models and commoditization could quickly squeeze margins and force labs to find new, hard-to-execute business models.
  3. A software-driven automation surge could be deflationary and displace white‑collar jobs, hurting consumer demand and traditional revenue streams. That macro uncertainty makes investors more risk‑averse and raises the bar for further AI spending.

Eight More 8-Bit Era Microprocessors

The Chip Letter • 4368 implied HN points • 18 Feb 24
🕹 Technology Hardware Microprocessors Design History Innovation
  1. Designs that were not commercially successful can still be interesting and hold value for learning.
  2. Intel's 8085 microprocessor, while not a bad design, was overshadowed by Zilog's Z80 due to lack of major improvements.
  3. Signetics 2650 microprocessor faced limitations such as delayed time to market and segmented memory, showing the importance of timely releases and memory efficiency.

No slowing down on the smart stuff, ok?

Alex's Personal Blog • 98 implied HN points • 23 Dec 25
🕹 Technology AI Autonomous Vehicles Electric Vehicles Ethics Regulation Open Source
  1. AI image generators can easily create sexualized deepfakes that are already harming kids, and the spread of open-source models means company policies alone won’t stop that abuse.
  2. Electric cars are rapidly gaining market share in Europe and offer clear benefits like lower maintenance and better performance, making the shift away from internal combustion seem inevitable.
  3. Self-driving cars promise big safety improvements and pair naturally with electrification, but high‑profile crashes and cautious regulators are slowing deployment — we should keep pushing the technology forward.

The Invisible Battlefield: AI, Cognitive Warfare, and the Battle for Your Mind (#PsyWar)

Who is Robert Malone • 9 implied HN points • 27 Feb 26
🕹 Technology Artificial Intelligence Cybersecurity Information Warfare Surveillance Tech Policy
  1. AI chatbots run on hidden system prompts and designer values, so their answers can consistently shape how people think and act like large-scale propaganda.
  2. Small, targeted data poisoning and RAG attacks can quietly make models give manipulated or false answers, and those poisoned signals are hard to detect and can spread across systems and future model generations.
  3. Treating cognition as an intelligence domain — COGINT and fifth-generation warfare — turns minds into a battlefield, so people and policymakers need epistemic sovereignty and institutions to protect information environments.

Cultivating Excellence in Teams with Continuous Software Engineering — Part 1: Defining Excellence through 5 Characteristics

The Healthy Engineering Leader • 99 implied HN points • 09 Jul 24
🕹 Technology Software Engineering Team Dynamics Product Development Continuous Improvement
  1. An effective team knows what its customers want and focuses on building the right product. They prioritize features based on customer needs and data.
  2. High craftsmanship involves a team that produces quality work while minimizing bugs. They continuously learn and share knowledge to improve their software.
  3. Good communication and collaboration create a cohesive team environment. Everyone feels safe to share ideas, which helps solve problems together.

Inductive biases - a better way to think about machine learning?

Mindful Modeler • 159 implied HN points • 11 Jun 24
🕹 Technology Machine Learning Data science Book Writing
  1. Hyperparameter settings can drastically change inductive biases within machine learning models.
  2. Machine learning algorithms represent a collection of inductive biases that influence model outcomes.
  3. Understanding inductive biases is crucial for comprehending the robustness, interpretability, and plausibility of machine learning models.

Prophecies of the Flood

One Useful Thing • 1608 implied HN points • 10 Jan 25
🕹 Technology Artificial Intelligence Machine Learning AI Ethics Automation Digital Transformation
  1. AI researchers are predicting that very smart AI systems will soon be available, which they call Artificial General Intelligence (AGI). This could change society a lot, but many think we should be cautious about these claims.
  2. Recent AI models have shown they can solve very tough problems better than humans. For example, one new AI model performed surprisingly well on difficult tests that challenge knowledge and problem-solving skills.
  3. As AI technology improves, we need to start talking about how to use it responsibly. It's important for everyone—from workers to leaders—to think about what a world with powerful AIs will look like and how to adapt to it.

Doomprompting Is the New Doomscrolling.

Working Theorys • 485 implied HN points • 10 Aug 25
🕹 Technology AI Cognition Communication Behavior Productivity
  1. Doomprompting is when we get caught up in endless online prompts and conversations, leading to less deep thinking and creativity. It's like having a machine that constantly suggests ideas but takes away our ability to think for ourselves.
  2. AI tools can help with brainstorming and refining ideas, but they can't replace the core creative thinking that we need to do as humans. Relying too much on AI can weaken our own skills and thought processes.
  3. It's important to seek out tools and partnerships that encourage us to think deeply and struggle with ideas, rather than just making things easy or automatic. Building skills takes time and effort, so we need to balance technology use with personal growth.

AI: Notes From The Dark Side

So Here’s a Thing • 1160 implied HN points • 02 Apr 23
🕹 Technology AI Art Prose TV Creators
  1. Implications of AI for news and our perception of the world include the rise of fake photos and deepfake videos, requiring critical thinking and fact-checking.
  2. AI in art poses challenges in distinguishing real works from fakes and may alter how artists maintain their catalogues to differentiate their genuine creations.
  3. The importance of human intent and meaningfulness in creation, questioning what AI-created content lacks in terms of emotional depth and personal connection.

A Software Engineer's Guide to Reading Research Papers

Confessions of a Code Addict • 1467 implied HN points • 28 Jan 25
🕹 Technology Software Engineering Research Methods Career development Technical Writing Information literacy
  1. Research papers are important for software engineers to keep up with new technologies and fill knowledge gaps. It helps to stay current with developments in your field, like time series analysis.
  2. Many people find reading research papers hard because they can be dense and technical. A lack of a research background can make it seem even more intimidating.
  3. With time and practice, anyone can learn to read and understand research papers. Finding a personal approach or framework can make the process easier.

Security Is Not a VPN Problem

Security Is • 59 implied HN points • 01 Aug 24
🕹 Technology Cybersecurity Internet Software Networking Privacy
  1. VPNs used to be essential for online security, especially on public WiFi, but that's changed with HTTPS being widely available. Now, most websites encrypt your connection by default.
  2. While VPNs can protect your IP address and DNS queries, for most everyday users, these aren't major issues anymore. Modern browsers and services help keep our connections safe.
  3. Using a VPN isn't a priority for everyone, and it might not be worth the investment, especially for regular people who just want basic online protection.

China will Catch up in Generative AI in 2024

AI Supremacy • 569 implied HN points • 06 Feb 24
🕹 Technology AI Artificial Intelligence Asia Generative AI Cloud Services
  1. China is advancing rapidly in Generative AI and is set to catch up with the U.S. by 2024.
  2. China is approving numerous large language models and enterprise applications in AI, showing its commitment to AI innovation.
  3. The tech competition between China and the U.S. intensifies as China aims to lead in Generative AI with a focus on AI regulation and product advancements.

The Bitter Pipeline

Abstraction • 39 implied HN points • 28 Jan 26
🕹 Technology AI Machine Learning Forecasting Data science Modeling Research
  1. Frontier models scale better than human-designed forecasting pipelines, so the structured process that helped smaller models often adds no value with larger models.
  2. Empirical tests show spending compute on polling and ensembling big models improves forecast skill more than token-heavy steps like classification or decomposition, with ensembling giving measurable uplift while the pipeline did not.
  3. The practical move is to simplify: ensemble aggressively, validate empirically, and keep experimenting with ways to elicit latent model knowledge instead of adding complex hand-crafted processes.

Creating Synthetic Training Data

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 59 implied HN points • 01 Aug 24
🕹 Technology Artificial Intelligence Data science Machine Learning Natural Language Processing Software Development
  1. Creating synthetic data is hard because it's not just about making more data; it also needs to be diverse and varied. It's tough to make sure there are enough different examples.
  2. Using a seed corpus can limit how varied the synthetic data is. If the starting data isn't diverse, the generated data won't be either.
  3. A new approach called Persona Hub uses a billion different personas to create varied synthetic data. This helps in generating high-quality, interesting content across various situations.

Who to read to keep up with AI

Meaningness • 698 implied HN points • 06 Jan 24
🕹 Technology AI Blog Authors Future
  1. The post recommends three different authors to read to stay updated on AI: Zvi Mowshowitz, Arvind Narayanan, and Jon Stokes.
  2. Each of these authors brings a unique perspective to the discussion on AI, covering different aspects and opinions on the future of AI.
  3. The authors fall into different quadrants regarding their views on AI's future, touching on varying levels of power, impact, and potential risks in the field.

How I Used Methodable to Have a Nice Tuesday

Human Programming • 51 implied HN points • 22 Jan 26
🕹 Technology Productivity Software Workflow Planning Time management UX Tools
  1. A small meta-plan in Methodable can un-scatter your attention by giving you one clear instruction at a time so you follow prior intentions and finish high-priority tasks.
  2. Start with a simple seed meta-plan and gradually structure it: collect your to-dos, free-write motivations, then convert those into detailed, executable subprograms.
  3. Designing guided workspaces with time-boxing, embedded editors, and positive self-talk makes it easier to regain focus, stay motivated, and end the day feeling accomplished.

Deep Learning Weekly: Issue 336

Deep Learning Weekly • 648 implied HN points • 17 Jan 24
🕹 Technology AI Machine Learning Generative AI MLOps Libraries
  1. This week's deep learning topics include generative AI in enterprises, query pipelines, and closed-loop verifiable code generation.
  2. Updates in MLOps & LLMOps cover CI/CD practices, multi-replica endpoints, and serverless solutions like Pinecone.
  3. Learning insights include generating images from audio, understanding self-attention in LLMs, and fine-tuning models using PyTorch tools.