The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

How AI Will Be Used for Cyber Security in 2024

Rod’s Blog • 615 implied HN points • 29 Dec 23
đź•ą Technology AI
  1. Cyber security is crucial in today's digital era due to increasing complexity of attacks, making traditional defense methods inadequate.
  2. Artificial intelligence (AI) is becoming essential in fighting cyber threats by mimicking human intelligence in tasks like learning and decision-making.
  3. In 2024, AI will play a vital role in cyber security, aiding in threat detection, prevention, response, and recovery.

Inference is FREE and INSTANT

Source Code by Fume • 22 HN points • 26 Aug 24
đź•ą Technology AI
  1. Many people have different views on the future of AI; some believe it will change a lot soon, while others think it won't become much smarter. It's suggested that rather than getting smarter, AI will just get cheaper and faster.
  2. There's a concern that large language models (LLMs) might not be improving in reasoning skills as expected. They have become more affordable over time, but that doesn't necessarily mean they are getting better at complex tasks.
  3. The Chinese Room Argument highlights that AI can follow instructions without understanding. Even if AI tools become faster, they might still lack the creativity to generate unique ideas, but they can still help with routine tasks.

The place of machines in children's society

Trevor Klee’s Newsletter • 447 implied HN points • 26 Jul 25
🎭️ Culture AI
  1. Children need time to play and make their own decisions, which helps them learn and grow. When adults step in too much, kids lose their chance to explore and figure things out themselves.
  2. With the rise of technology, kids will often be in contact with AI that can influence how they play and interact. This might change how they see the world and themselves while growing up.
  3. It's important for both kids and adults to think for themselves. Relying too much on AI can make it hard to develop original thoughts and ideas.

Don't Push AI Down Our Throats

Experiments with NLP and GPT-3 • 122 implied HN points • 30 Nov 25
đź•ą Technology AI
  1. AI should not be forced upon us; it feels overwhelming and unwanted. Technology should be introduced slowly and thoughtfully.
  2. The rush to deploy AI is driven by profit motives, not by what users really need. We should only adopt AI that provides real benefits to our lives.
  3. There are many useful applications of AI, but we should focus on what works for us and not feel pressured by companies to use AI just for their financial gain.

DeepSeek Is a Wake-Up Call. Is America Listening?

Common Sense with Bari Weiss • 1219 implied HN points • 28 Jan 25
đź•ą Technology AI
  1. DeepSeek, a small Chinese company, has created powerful AI models for much less money than American companies, challenging the idea that the U.S. leads in technology. This means other countries can compete more easily in AI.
  2. The surprising success of DeepSeek caused significant drops in the stock prices of major tech companies, showing how big of an impact one smaller player can have on the market.
  3. DeepSeek's technology is accessible for anyone with limited resources, which could change the future of AI development and create potential instability in the tech landscape.
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My Definition of Data Modeling (for today)

Joe Reis • 530 implied HN points • 20 Jan 24
đź•ą Technology AI
  1. Data modeling has various definitions by different experts and serves to improve communication, provide utility, and solve problems.
  2. A data model is a structured representation that organizes data for both humans and machines to inform decision-making and facilitate actions.
  3. Data modeling is evolving to consider the needs of machines, different use cases, and a wider range of modeling approaches for various situations.

AI Is A Car That Everyone Expects To Be A Spaceship

Beekey’s Substack • 59 implied HN points • 24 Jul 24
đź•ą Technology AI
  1. AI has made great improvements, especially with tasks that involve generating human-like responses and art. However, many people are getting carried away with the hype about its capabilities.
  2. Machine learning allows AI to recognize patterns in data, but it doesn't actually understand content like a human does. This means it can make mistakes that a human wouldn't.
  3. The idea of creating Artificial General Intelligence (AGI) from current AI is questionable because we still don't fully understand how human intelligence works. It's not just about being faster; something fundamental is still missing.

AI is everyone's favorite excuse to raise software prices

Enterprise AI Trends • 84 implied HN points • 17 Dec 25
đź’Ľ Business AI
  1. AI is making software more expensive right now. Many SaaS vendors raised prices in 2024–25 and are likely to keep raising them through 2026–27.
  2. Companies are bundling AI features into existing plans and hiking fees, effectively converting subscription revenue into “AI” revenue and limiting opt-outs.
  3. Structural forces beyond direct product value — like customers tolerating higher prices for high-value AI improvements and halo effects from better foundational models — are giving vendors sustained pricing power and a temporary “AI windfall.”

Ranking the Chinese Open Model Builders

Democratizing Automation • 356 implied HN points • 17 Aug 25
đź•ą Technology AI
  1. China's AI labs are rapidly releasing open models, showing strong competition with Western counterparts. Labs like DeepSeek and Qwen are leading the pack with frequent and high-quality outputs.
  2. DeepSeek is known for its innovative models and focus on performance, but its recent slower release pace has allowed other labs to catch up. They aim for continual improvement and impactful contributions.
  3. Other emerging companies like Moonshot AI and Zhipu are also gaining ground, offering competitive models and partnering with tech giants for investments. They are expected to grow and possibly reshape the AI landscape.

The AI doppelgänger experiment – Part 1: The training

On Looking • 184 HN points • 15 May 24
🎨 Art & Illustration AI
  1. Communication relies on shared language, and this is especially crucial when discussing visual concepts like style and art.
  2. Training generative AI models to transfer style involves complex processes of separating denotational and stylistic aspects of images.
  3. The AI doppelganger experiment explores the tension between human-created images and machine-generated ones, raising questions about personhood, identity, and creativity in the digital age.

⤴⤵ Up Wing/Down Wing #50

Faster, Please! • 548 implied HN points • 28 Jun 25
đź•ą Technology AI
  1. Truck unloading is getting faster and safer with robots that can move packages quickly and reduce physical strain on workers.
  2. Google's new offline robot can perform complex tasks, showing how adaptable and capable modern AI technology has become.
  3. New York is building a nuclear power plant to provide clean energy, reflecting a push for faster and more reliable energy solutions.

How to Build a Company that OpenAI/Google Can't Eat

FutureIQ • 3 implied HN points • 13 Mar 26
đź’Ľ Business AI
  1. Trust wins in high-stakes fields: using credentialed sources and training models only on vetted, domain‑specific literature (not the open internet) makes professionals trust the system and cuts hallucinations.
  2. Own exclusive data and build a flywheel: getting top practitioners and journals to use and partner creates unique, high‑quality signals that improve the product and attract more users and partners.
  3. Capture tacit, time‑sensitive context to monetize defensibly: real‑time usage data and tight integrations let you offer services big generalist models can’t replicate, creating a deep, hard‑to‑clone moat.

The rise of reasoning machines

Democratizing Automation • 570 implied HN points • 12 Jun 25
đź•ą Technology AI
  1. Reasoning is when we draw conclusions based on what we observe. Humans experience reasoning differently than AI, but both lack a full understanding of their own processes.
  2. AI models are improving but still struggle with complex problems. Just because they sometimes fail doesn't mean they can't reason; they just might need new methods to tackle tougher challenges.
  3. The debate on whether AI can truly reason often stems from fear of losing human uniqueness. Some critics focus on what AI can't do instead of recognizing its potential, which is growing rapidly.

Channels, not Addresses

Philip’s Newsletter • 31 implied HN points • 28 Jan 26
đź•ą Technology AI
  1. The internet's address-based model lets anyone send messages to you uninvited, which enables spam, DDoS, stalking, and will get much worse with persuasive AIs.
  2. Creating shared private channels between people makes messaging a pull-based, encrypted inbox you control, so others can't overwhelm you and you can stop contact by deleting the channel.
  3. Simple relays only store and forward encrypted channel messages, letting many devices and servers carry traffic without reading it, which makes messaging decentralized, censorship-resistant, and usable even offline.

Data Science Weekly - Issue 547

Data Science Weekly Newsletter • 179 implied HN points • 17 May 24
đź•ą Technology AI
  1. Learning Rust programming can be made easy with exercises designed for beginners, even if you know another language already. You’ll work through small tasks to build confidence.
  2. Data scientists need to learn how to work with databases to scale their analytics. Many face challenges when transitioning to this part of their work.
  3. There are helpful tools, like Data Wrangler for VS Code, that simplify data cleaning and analysis. These tools help generate code automatically as you work with your data.

DeepSeek: A Tragedy Foretold?

ChinaTalk • 1141 implied HN points • 31 Jan 25
đź•ą Technology AI
  1. DeepSeek is an open-source AI project in China that allows developers to use and build on its models for free. This supports the idea of sharing knowledge and innovation globally.
  2. Many Chinese tech leaders prefer closed-source models because they see open-source as less profitable. They believe it’s often not worth the investment when considering the costs involved.
  3. The Chinese government supports open-source initiatives to reduce dependence on foreign software, but there are concerns about how powerful AI could be regulated to ensure safety and control.

2024 is all About Generative AI for Indian IT

Sector 6 | The Newsletter of AIM • 559 implied HN points • 08 Jan 24
đź•ą Technology AI
  1. 2024 is set to focus heavily on generative AI in the Indian IT sector. It's expected to drive many business deals and boost revenue.
  2. Major companies like Infosys, TCS, Wipro, and HCLTech will take the lead in integrating AI and enhancing skills for their workforce.
  3. This year aims for bigger AI projects compared to last year, moving towards larger contracts instead of smaller ones.

LabGenius - the long slow road to faster drug discovery

Rory’s Always On Newsletter • 535 implied HN points • 07 Feb 24
🔬 Science AI
  1. AI and machine learning are revolutionizing drug discovery by speeding up the identification of potential treatments, leading to big rewards for those in the industry.
  2. Building a successful biotech company requires patience, determination, and significant funding, often with a focus on research and development before revenue generation.
  3. Investors in biotech companies must be prepared for a long journey of constant failures and successes, akin to the process of drug discovery, with potential acquisitions being key outcomes.

Resilient Cyber Newsletter #4

Resilient Cyber • 79 implied HN points • 09 Jul 24
đź•ą Technology AI
  1. Cybersecurity roles are becoming more competitive, and many people want to join the field. It's important to have standards, but we also need to make sure newcomers have a chance to enter the profession.
  2. There's a huge increase in cybersecurity vulnerabilities, making it harder for companies to keep up. Organizations need better ways to manage these vulnerabilities to protect against attacks.
  3. The conversation around AI in cybersecurity is rising, with discussions on how to use it securely and the risks involved. Transparency is key to building trust, especially after high-profile breaches.

Data Science Weekly - Issue 541

Data Science Weekly Newsletter • 279 implied HN points • 05 Apr 24
đź•ą Technology AI
  1. AI agents have unique challenges that traditional laws may not effectively solve. New rules and systems are needed to ensure they are managed properly.
  2. JS-Torch is a new JavaScript library that makes deep learning easier for developers familiar with PyTorch. It allows building and training neural networks directly in the browser.
  3. Data acquisition is crucial for AI start-ups to succeed. There are strategies outlined to help these businesses gather the right data efficiently.

Is growth still good?

benn.substack • 1176 implied HN points • 17 Jan 25
đź’Ľ Business AI
  1. Fast growth can be misleading in today's market. Just because a startup is making money quickly doesn't mean it has a solid long-term plan.
  2. Smaller, newer companies are often more innovative than big ones. Many tech leaders are looking to fresh, creative minds instead of established corporations for solutions.
  3. AI is creating a new type of workplace dynamic. Instead of making jobs easier, it could lead to roles that are more focused on managing technology than using creativity.

Sora Can’t Handle the Truth

Marcus on AI • 3398 implied HN points • 17 Feb 24
đź•ą Technology AI
  1. Large language models like Sora often make up information, leading to errors like hallucinations in their output.
  2. Systems like Sora, despite having immense computational power and being grounded in both text and images, still struggle with generating accurate and realistic content.
  3. Sora's errors stem from its inability to comprehend global context, leading to flawed outputs even when individual details are correct.

Dialogical Design

the shimmering void • 93 implied HN points • 08 Dec 25
🪑 Design AI
  1. Your computer should feel like a personal world built from people, places, and things, where structure emerges as you use it rather than being forced by pre-set apps or folders.
  2. Current software habits create silos and rigid schemas that ossify your life’s data, so designers must stop assuming they know what users need and enable iterative, user-driven structure instead.
  3. Large language models make fuzzy, dialogical interaction possible and can help shape meaning, but we also need new technical substrates that support flexible subdivision, derivation, and coherent sharing/privacy.

The Impact of AI on Social Media

Rod’s Blog • 515 implied HN points • 16 Jan 24
đź•ą Technology AI
  1. Artificial intelligence is extensively used on social media platforms like Facebook, Twitter, Instagram, and TikTok to personalize content, analyze user data, and moderate harmful content.
  2. AI on social media can enhance user experience by helping discover relevant content, connect with similar individuals, and create a safer online environment.
  3. Despite its benefits, AI poses risks to user privacy, security, and trust by collecting and exploiting data, creating biases and misinformation, and reducing user control over algorithms.

Photon-Lines Tech Notes - July 2025

Photon-Lines Substack • 417 implied HN points • 31 Jul 25
đź•ą Technology AI
  1. OpenAI encourages a culture where anyone can share good ideas, and teams can quickly adapt and change their focus based on new findings. This fast-moving style allows for exciting developments but also comes with challenges.
  2. Modern software often hides important controls, making it hard for users to navigate interfaces efficiently. Good design should prioritize clear and visible controls to help users easily find what they need.
  3. Beliefs are like complex webs of ideas, and changing one belief often requires rethinking many connected beliefs. This makes conversations about challenging beliefs tough, as people naturally defend their larger belief systems.

OpenClaw/Moltbot/ClawdBot 101: The Complete Guide

The Product Channel By Sid Saladi • 20 implied HN points • 11 Feb 26
đź•ą Technology AI
  1. OpenClaw is a local AI agent framework that runs on your machine, links to messaging apps, and can actually execute commands, scripts, browser actions, and file operations using an LLM backend.
  2. It went viral because of flashy demos and the Moltbook agent phenomenon, but much of the “AI society” hype was overstated and many high-profile examples were human-assisted or misleading.
  3. OpenClaw poses serious security and privacy risks since it has shell access and shipped with weak defaults, so you should use dedicated hardware/accounts, avoid exposing ports, enable Docker sandboxing, and follow strict credential and network hygiene.

GPT-5: Strategic Implications

Enterprise AI Trends • 379 implied HN points • 07 Aug 25
đź•ą Technology AI
  1. OpenAI is combining all its models into one, called GPT-5, which makes things easier for users since they won’t need to choose from different versions anymore.
  2. This new model setup helps OpenAI save money by managing costs better and keeping everything efficient, like a smart system that uses just the right amount of power for each task.
  3. With GPT-5 being cheaper and better than some competitor models, it pushes other companies, like Anthropic, to innovate and lower their prices to stay competitive.

It’s time to hire your first marketing agent

MKT1 Newsletter • 8 implied HN points • 19 Feb 26
đź’Ľ Business AI
  1. Agents are AI teammates that can autonomously run repeatable marketing work — they plan, reason, and act across tools to deliver measurable outcomes.
  2. Build agents like hiring a new teammate: write a short job-style spec, pick a builder (autonomous, structured, or productized), ship a simple MVP, and iterate with human review.
  3. Start with easy, high-ROI agents (competitive intel, content repurposing, social listening, growth analysis), deliver outputs into systems you already use, and design for reliability with structured outputs, checks, and limited permissions.

Agriculture, but make it precise

Topsoil • 550 implied HN points • 06 Jan 24
đź•ą Technology AI
  1. Precision agriculture uses technology to adjust equipment for field variability, improving efficiency.
  2. Precision agriculture offers benefits like increased yields, time savings, and environmental sustainability.
  3. While valuable, precision agriculture is not a one-size-fits-all solution and adoption can be complex.

AI is Creating Peak Software, Media is the Best Analogy

Mule’s Musings • 455 implied HN points • 10 Jul 25
đź•ą Technology AI
  1. The cost of creating software is dropping dramatically because of new AI tools, making it cheaper and faster to write code.
  2. Just like the rise of YouTube changed how people consumed media, AI is transforming how software is produced and distributed, increasing supply significantly.
  3. As the number of software solutions grows, traditional software companies may struggle to compete, leading to a rush of changes in the industry.

Import AI 333: Synthetic data makes models stupid; chatGPT eats MTurk. Inflection shows off a large language model

Import AI • 898 implied HN points • 26 Jun 23
đź•ą Technology AI
  1. Training AI models exclusively on synthetic data can lead to model defects and a narrower range of outputs, emphasizing the importance of blending synthetic data with real data for better results.
  2. Crowdworkers are increasingly using AI tools like chatGPT for text-based tasks, raising concerns about the authenticity of human-generated content.
  3. The UK is taking significant steps in AI policy by hosting an international summit on AI risks and safety, showcasing its potential to influence global AI policies and safety standards.

✨ The Age of AI: Will 2025 be our last normal year?

Faster, Please! • 1279 implied HN points • 03 Jan 25
đź•ą Technology AI
  1. AI technology is rapidly evolving, and some predict it could change our everyday lives significantly by 2025. If this happens, what we consider 'normal' now might no longer exist.
  2. Recent advances in AI, like OpenAI's new model, have made experts rethink how soon we might see 'strong' AI that can perform complex tasks like humans. This raises important questions about the future of work and society.
  3. Despite the excitement around AI, not all experts believe we are close to seeing a major economic boom from it. Predictions about technology can be tricky, and history shows change can take a long time.

Things don't only get better

imperfect offerings • 379 implied HN points • 26 Feb 24
đź•ą Technology AI
  1. Improvements in AI models are not always guaranteed, as evidenced by instances of models getting worse over time due to tweaks and updates.
  2. Investment in AI technology is booming, generating wealth for billionaires while possibly hindering investment in viable low-carbon tech solutions for climate change.
  3. The narrative surrounding AI portrays it as a powerful force for the future, but practical solutions for climate crisis require more than just technological advancements - they also need systemic changes and investments.

Deepfaked Shit is Getting Real

Marcus on AI • 3438 implied HN points • 04 Feb 24
đź•ą Technology AI
  1. An entire cast of deepfaked people scammed a company out of $25 million
  2. Even a suspicious employee fell for the deepfake scam
  3. AI developers should be accountable for the negative impacts of their technology

đź’› Artificial Intelligence: A Boon for Humanity or a Dreadful Weapon of Tyranny?

The Glenn Meder Newsletter • 530 implied HN points • 09 Jan 24
đź•ą Technology AI
  1. Artificial intelligence has advanced rapidly, blurring the line between human and AI interactions.
  2. Big Tech companies like Google and Facebook use AI to manipulate public opinion and influence elections.
  3. AI, in the hands of those seeking power, can be a dangerous tool for control and manipulation of individuals and society.

AGI Is Already Here—It’s Just Not Evenly Distributed

The Algorithmic Bridge • 1104 implied HN points • 05 Feb 25
đź•ą Technology AI
  1. Understanding how to create good prompts is really important. If you learn to ask questions better, you'll get much better answers from AI.
  2. Even though AI models are getting better, good prompting skills are becoming more important. It's like having a smart friend; you need to know how to ask the right questions to get the best help.
  3. The better your prompting skills, the more you'll be able to take advantage of AI. It's not just about the AI's capabilities but also about how you interact with it.