The hottest Technology Substack posts right now

And their main takeaways
Category
Top Technology Topics

Using Matplotlib To Create The 50th Article Cover Mosaic Animation (#50 Part 2)

The Python Coding Stack • by Stephen Gruppetta • 119 implied HN points • 10 Feb 24
🕹 Technology Programming Animation Visualization
  1. You can use Matplotlib to create animations, like a mosaic of previous article cover images, by following a step-by-step tutorial.
  2. Before starting the animation, ensure you have images ready and the necessary libraries installed like Matplotlib, NumPy, and Pillow.
  3. You can control how images are plotted, resize images in the animation frames, and save the animation as a movie file like an mp4 or an animated GIF using libraries like Matplotlib or PillowWriter.

BLT: Byte Latent Transformer

Gonzo ML • 315 implied HN points • 23 Dec 24
🕹 Technology Artificial Intelligence Machine Learning Data processing Software Development Innovation
  1. The Byte Latent Transformer (BLT) uses patches instead of tokens, allowing it to adapt based on the complexity of the input. This means it can process simpler inputs more efficiently and allocate more resources to complex ones.
  2. BLT can accurately encode text at a byte level, overcoming issues with traditional tokenization that often lead to mistakes in understanding languages and simple tasks like counting letters.
  3. BLT architecture has shown better performance than older models, handling tasks like translation and sequence manipulation more effectively. This advancement could improve the application of language models across different languages and reduce errors.

Singh & Sins of AI 💦

Sector 6 | The Newsletter of AIM • 99 implied HN points • 13 Feb 24
🕹 Technology AI Open Source Software Data science Machine Learning
  1. The Indian AI scene is growing, with many new language models being developed based on Meta's Llama 2. This shows a collaborative spirit in the open-source community.
  2. There are specific models being made for different Indian languages like Kannada, Telugu, Odia, and Tamil. These models help in making AI more accessible to people speaking these languages.
  3. There is a strong need for India to create its own unique open-source AI model. This would allow other developers to build on it rather than relying on external sources.

The Sequence Opinion #754: Generalist vs. Specialist: Which School Will Win in Mathematical AI

TheSequence • 35 implied HN points • 13 Nov 25
🕹 Technology Artificial Intelligence Computer Science Mathematics Machine Learning Data science
  1. Generalist AI models can handle a wide range of math problems and can even score well on exams, but they struggle with creating new math concepts.
  2. Specialist AI models focus on specific math tasks and provide precise answers, but they have limits in flexibility and scope.
  3. Choosing between generalist and specialist models depends on the math task at hand, as each has its own strengths and weaknesses.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

SB 1047 with Socialist Characteristics: China’s Algorithm Registry in the LLM Era

ChinaTalk • 355 implied HN points • 14 Nov 24
🕹 Technology AI Regulations Policy Analysis Data security Global Governance
  1. China has introduced strict rules for generative AI, requiring all output to reflect socialist values. This highlights the government's focus on controlling AI content that interacts with the public.
  2. There are two separate registration processes for algorithms in China: a simpler one for regular algorithms and a more complex one for generative AI. The more complicated process involves direct testing by authorities, making it tougher for companies to launch AI products.
  3. The regulatory environment is still evolving and can be confusing for companies. Some might face delays in getting their models approved, which could lead to a preference for targeting businesses over regular consumers.

AI Companies Have Lost the Mandate of Heaven

The Algorithmic Bridge • 339 implied HN points • 04 Dec 24
🕹 Technology AI Software Data Computing Innovation
  1. AI companies are realizing that simply making models bigger isn't enough to improve performance. They need to innovate and find better algorithms rather than rely on just scaling up.
  2. Techniques to make AI models smaller, like quantization, are proving to have their own problems. These smaller models can lose accuracy, making them less reliable.
  3. Researchers have discovered limits to both increasing and decreasing the size of AI models. They now need to find new methods that work better while balancing cost and performance.

PostHog vs. The Industry

Alex's Personal Blog • 131 implied HN points • 17 Jun 25
🕹 Technology Startups Software Funding Innovation Analytics
  1. PostHog is a startup doing things differently in the software world, like offering mostly free and open-source tools for product development. They focus on customer-friendly policies instead of typical sales tactics.
  2. There’s increasing investment in defense and AI startups, showing a trend towards innovation in these sectors. Companies like Helsing and xAI are raising significant funds to grow their projects.
  3. High costs for coding tools are becoming more common, as shown by Anysphere's price increase for its AI coding service. Developers might need to adjust to spending more to access advanced technology.

Last Week in AI #248: ChatGPT's 1st birthday, Amazon's new AI chatbot Q, the energy cost of generative AI, Sam Altman makes statement after return, and more!

Last Week in AI • 178 implied HN points • 04 Dec 23
🕹 Technology AI Chatbots Leadership Changes AI Applications
  1. ChatGPT has made a significant impact in the past year with its interactive and conversational dialogue capabilities
  2. Amazon's new AI chatbot Q for companies has faced reliability issues, including hallucinations and data exposure during its public preview
  3. Generative AI, like image generation, consumes significant energy, equivalent to charging a smartphone, prompting a need to consider the environmental impact of AI technologies

State of AI: February 2026 newsletter

Guide to AI • 4 implied HN points • 09 Feb 26
🕹 Technology AI Research Policy Infrastructure Semiconductors Security Funding
  1. Agentic AI is triggering a massive market repricing as autonomous agents and rapidly advancing frontier models threaten the long-term recurring revenue that justified high SaaS valuations, wiping hundreds of billions from software stocks. Investors are racing to re-evaluate how to underwrite tech companies in a world where core workflows can be rebuilt AI-first.
  2. Geopolitics and infrastructure constraints are reshaping the AI landscape: governments are clashing with labs over military use and export controls, states are limiting data center builds, and China is aggressively scaling talent and commercial AI, all of which will affect where training clusters and supply chains can be built. These policy and resource shifts will influence competition, investment, and national strategy in AI.
  3. Rapid agent proliferation has produced both theatrical emergent behavior and serious security problems: viral agent networks blurred the line between human and AI activity, while open-source agents exposed widespread vulnerabilities, leaked credentials, and growing shadow-IT risks for enterprises. The combination of autonomy, data access, and external actions makes agent security a top priority.

BI is not ready for AI

HyperArc • 3 HN points • 06 Sep 24
🕹 Technology AI Data science Machine Learning Business Intelligence Software Development
  1. Business Intelligence (BI) needs both good models and great data to be effective with AI. Without quality data, AI can't really show its true power.
  2. Many BI tools only focus on successful outcomes, like specific metrics, while ignoring the complete journey of discovery. This limited data can lead to missing important insights.
  3. To improve AI's effectiveness in BI, we should include a wider range of experiences and exploration paths, not just successful queries. This fuller picture can help create better AI training sets.

Security by design is hard

Frankly Speaking • 355 implied HN points • 10 Nov 24
🕹 Technology Cybersecurity Product Design Software Development Startups Tech Trends
  1. Security by design is a good idea but hard to implement. Most companies prioritize speed over security, treating security as an afterthought.
  2. Many existing cybersecurity solutions focus on adding security measures after a product is built instead of integrating it from the start.
  3. Tools like Pangea help address security issues early in product development, making it easier for developers to implement security as they build.

I'm Not Loving the AI Jobs Discourse Right Now

I Might Be Wrong • 5 implied HN points • 06 Feb 26
🕹 Technology Artificial Intelligence Automation Workforce Ethics Misinformation Public Discourse
  1. The public conversation about AI and jobs is poor quality and often full of fear-mongering and bad faith arguments.
  2. There are three distinct AI risks — alignment, misinformation, and job displacement — and they deserve different levels of concern: alignment is very worrying, misinformation is less novel, and the jobs debate is the most overheated.
  3. Treating labor as a cost is a normal business perspective, and criticizing companies for that misses that paychecks are a real benefit for workers and that firms respond to economic incentives.

These 7 Software Engineering Skills Give You an Unfair Advantage

Brain Bytes • 119 implied HN points • 17 Jan 24
🕹 Technology Software Engineering Cybersecurity Automation Version Control Cloud Computing
  1. Thinking like a hacker helps in identifying and fixing security flaws before they are exploited, crucial in today's cybersecurity landscape.
  2. Understanding different devices through cross-platform critical thinking gives a competitive edge and promotes reusability of business logic.
  3. Scripting and automation for repetitive tasks enhances productivity by ensuring consistency, accuracy, and freeing up time for more complex work.

🤖⚡ Does AI use too much energy? A Quick Q&A with … policy analyst James Broughel

Faster, Please! • 822 implied HN points • 03 Feb 24
🕹 Technology AI Energy Policy Renewables Tech industry
  1. Critics think AI consumes a significant amount of energy, comparable to whole countries.
  2. There's a risk of AI's energy consumption becoming a political issue, akin to past debates around cryptocurrency.
  3. Leading tech companies are working to use renewable energy sources to power AI, reducing potential worries about its energy usage.

Inventions I Like To See

David Friedman’s Substack • 125 implied HN points • 23 Jun 25
🕹 Technology Gadgets Innovations Design Engineering Problem Solving
  1. Ziplock bags with built-in reseals help keep flatbreads fresh after opening. It's a smart design that solves a common problem.
  2. Shower designs that allow users to adjust water temperature safely make for a more comfortable experience. Simple solutions like combined tub and shower setups are very effective.
  3. New kitchen gadgets, like edgeless can openers and color-changing plastic eggs, show how inventiveness can improve everyday tasks. They add convenience and safety while cooking.

The latest open artifacts (#6): Reasoning models, China's lead in open-source, and a growing multimodal space

Democratizing Automation • 261 implied HN points • 27 Jan 25
🕹 Technology AI Models Open Source Datasets Reasoning Geopolitics
  1. Chinese AI labs are now leading the way in open-source models, surpassing their American counterparts. This shift could have significant impacts on global technology and geopolitics.
  2. A variety of new AI models and datasets are emerging, particularly focused on reasoning and long-context capabilities. These innovations are making it easier to tackle complex tasks in coding and math.
  3. Companies like IBM and Microsoft are quietly making strides with their AI models, showing that many players in the market are developing competitive technology that might not get as much attention.

OOP in Python: Why is object-oriented programming so important?

Mostly Python • 1257 implied HN points • 06 Jul 23
🕹 Technology Programming
  1. Object-oriented programming (OOP) is important because it stores information and actions in one place.
  2. OOP is powerful for getting work done efficiently, as shown by the ease of creating and working with objects in Python.
  3. Even if you don't write classes often, understanding OOP in Python can make you a better programmer since everything in Python is an object.

Seattle Data Guy In 2024

SeattleDataGuy’s Newsletter • 871 implied HN points • 26 Dec 23
🕹 Technology Data Analysis Consulting Content creation Community Building
  1. Seattle Data Guy's work in 2023 involved filming videos, virtual conferences, and writing articles and newsletters.
  2. Client trends in 2023 showed shifts towards greenfield projects, solution design, marketing, and education.
  3. Popular articles in 2023 covered topics like data modeling, breaking out of tutorial hell, and essential templates for data analytics.

On messing around

Sunday Letters • 79 implied HN points • 10 Mar 24
🕹 Technology Innovation Discovery Exploration Mindset Science
  1. Being a 'happy mutant' means being curious and passionate about your interests, even if others don't understand them. It's about exploring what fascinates you without needing to justify it.
  2. Mistakes and experiments are crucial for innovation and discovery. Sometimes the best inventions come from unexpected errors or just playing around with ideas.
  3. Having a growth mindset helps you embrace exploration. Following your instincts and interests can lead to amazing discoveries you never planned for.

Designing Usable Toggle Switches: Applying UX Research Insights

UX Psychology • 198 implied HN points • 20 Oct 23
🕹 Technology UX Design User Experience Research Design principles
  1. Toggle switches in user interfaces should provide immediate visual feedback when clicked to show the state change.
  2. Clear and familiar labels like 'On/Off' are crucial for toggle switches to avoid confusion. Avoid using unfamiliar terms or questions as labels.
  3. Use color effectively with 'On' typically in green or blue and position it on the right side. Negative or ambiguous toggle text should be avoided.

AI-generated slop is already clogging the arteries of the web

Simon Owens's Media Newsletter • 823 implied HN points • 19 Jan 24
🕹 Technology AI Tech Platforms Content creation Digital Media Media industry
  1. Many worry about AI-generated content replicating and stealing audiences, but the impact on publishers is still largely hypothetical.
  2. AI is already degrading the user experience of the web, causing harm and making content resources useless.
  3. Platforms like Amazon, Google News, and ad tech are flooded with AI-generated content, harming users and eroding trust in the information served.

Sierra's AI Strategy in a Nutshell

Enterprise AI Trends • 126 implied HN points • 18 Jun 25
🕹 Technology Artificial Intelligence Startups Enterprise Software Business strategy Risk management
  1. Sierra is an AI agent platform focused on building customer-facing AI interactions. It aims to take over all customer communications for businesses, starting with support.
  2. The success of Sierra could influence how other AI startups are viewed, especially those targeting the enterprise market. If Sierra struggles, it might signal challenges for similar companies.
  3. Sierra has a solid foundation with experienced founders and strong funding, but it faces risks like change management and vendor lock-in when companies consider using its services.

Results from poll #3 (and updates)

The Counterfactual • 59 implied HN points • 11 Apr 24
🕹 Technology AI LLMs Research Education Cognition
  1. Tokenization won the recent poll, so there will be an in-depth explainer about it soon. This will help people understand how tokenization works in large language models.
  2. The visual reasoning task was a close second, so it might come up in the next poll for more ideas. This shows there is interest in how models think visually.
  3. There are updates about recent publications and discussions on related topics in AI and psychology. These will be shared in upcoming posts, expanding on interesting research topics.

Data Science Weekly - Issue 492

Data Science Weekly Newsletter • 379 implied HN points • 28 Apr 23
🕹 Technology Data science Machine Learning Artificial Intelligence Data Visualization Software Engineering
  1. There is a new Slack community for paid subscribers focused on learning new tools and techniques in data science and career growth. It's a good place for support and sharing information.
  2. A/B testing is important for experiments and there are recommended resources to help design and run successful tests. Proper planning and communication are key to making A/B testing effective.
  3. Large Language Models (LLMs) are becoming more useful, and several resources are available for learning how to work with them. Understanding how they operate can help create valuable applications.

LLMs and World Models, Part 1

AI: A Guide for Thinking Humans • 247 implied HN points • 13 Feb 25
🕹 Technology AI Machine Learning Neural Networks Natural Language Processing Computational Models
  1. In the past, AI systems often used shortcuts to solve problems rather than truly understanding concepts. This led to unreliable performance in different situations.
  2. Today’s large language models are debated to either have learned complex world models or just rely on memorizing and retrieving data from their training. There’s no clear agreement on how they think.
  3. A 'world model' helps systems understand and predict real-world behaviors. Different types of models exist, with some capable of capturing causal relationships, but it's unclear how well AI systems can do this.

What AGI can do for your average enterprise?

Metacritic Capital • 4 implied HN points • 10 Feb 26
🕹 Technology Artificial Intelligence Enterprise Software Automation Regulation
  1. Large companies already run as software-driven hive minds, so AGI will mostly make legacy systems work better instead of radically changing operations for firms like airlines.
  2. LLMs will automate a lot of knowledge work and reduce the need for human coordination, letting individuals oversee many more tasks, but competitors will have access to the same gains so margins won’t necessarily leap upward.
  3. The net effect is far more software and fewer people organizing production, pushing humans toward creative, adversarial, sales, and care roles, while the biggest transformative gains may come in fields like biology rather than mature industries.

How I've been using ChatGPT

The Counterfactual • 219 implied HN points • 25 Jul 23
🕹 Technology AI Tools Research Methods Programming Information Retrieval
  1. ChatGPT can help you learn about new topics by suggesting useful resources and references. This can speed up your research by providing relevant information without the hassle of searching through many documents.
  2. Using ChatGPT for recommendations can be helpful, but it shouldn't replace getting suggestions from friends or experts. It can fill in gaps when you don't have access to personal recommendations.
  3. ChatGPT acts as a good reading companion by answering specific questions while you read. This helps you understand the material better and encourages you to ask questions about what you’re learning.

LLM Disruption in Chatbot Development Frameworks

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 05 Jul 24
🕹 Technology AI Chatbots Natural Language Programming Development
  1. Large Language Models (LLMs) make chatbots act more like humans, making it easier for developers to create smart bots.
  2. Using LLMs reduces the need for complex programming rules, allowing for quicker chatbot setup for different uses.
  3. Despite the benefits, there are still challenges, like keeping chatbots stable and predictable as they become more advanced.

UX Roundup: UX Unicorns | Captcha Must Die | Flow in UX | Dark Design | Avatar Animation

Jakob Nielsen on UX • 114 implied HN points • 07 Jul 25
🕹 Technology User Experience Artificial Intelligence Design principles Human-computer interaction
  1. There are now many 'UX unicorns' – people skilled in various areas of user experience. They are common and help create better products by juggling different tasks like design and coding.
  2. Captchas are a big hassle for users, wasting their time and creating frustration. They don't really work anymore due to advances in AI, so we need better solutions.
  3. When users are in a state of 'flow,' they are more productive and happy. Good design helps achieve this by making tasks easy and seamless, so users don't get distracted.

Revolutionizing IoT Beyond Earth | Challenges & Innovations in Satellite-Enabled IoT

Space Ambition • 259 implied HN points • 23 Jun 23
🕹 Technology Space Technology IOT Startups Innovation
  1. Satellite technology is changing how we connect and communicate, especially in remote places. Smaller, cheaper satellites help devices send and receive information directly from space.
  2. Using satellites for IoT can improve many areas like farming, disaster response, and environmental monitoring. These systems can gather essential data from hard-to-reach locations and help address big challenges.
  3. While satellite IoT offers great opportunities, it also faces hurdles. Issues like regulations, energy needs, and ensuring data security will be important as this technology grows.

Missionaries vs. Mercenaries

Teaching computers how to talk • 110 implied HN points • 10 Jul 25
🕹 Technology AI Innovation Investment Startups Corporate strategy
  1. OpenAI has a huge ambition to grow like Meta, needing to hit a target of $125 billion in revenue by 2029. This is a really tough goal and they have to compete aggressively.
  2. Sam Altman believes that teams driven by passion and purpose (missionaries) will outperform those just focused on making money (mercenaries). He wants to create an inspiring work culture at OpenAI.
  3. OpenAI has taken on a lot of investment, which means they need to deliver high returns quickly. This pushes them to make bold moves in the AI market.

Some interesting new robots just announced!

Robots & Startups • 79 implied HN points • 09 Mar 24
🕹 Technology Robotics AI Startup News Events Ethics
  1. AI learning starting with text may be going backwards for language development, particularly for speech and social interaction.
  2. Human-robot interactions often differ from our collective fantasies, with instances of people mistreating robots in public like playing 'kick the robot dog' or interfering with autonomous cars.
  3. Robots posing as scooters in public encounters negative behaviors due to lack of proper treatment and consideration towards the technology.