The hottest Artificial Intelligence Substack posts right now

And their main takeaways
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Top Technology Topics

BREAKING: Politician Gives Good Speech

Common Sense with Bari Weiss • 361 implied HN points • 12 Feb 25
🇺🇸 U.S. Politics Artificial Intelligence
  1. Vice President J.D. Vance gave a strong speech at the AI Action Summit in Paris, which surprised many people who don't expect politicians to speak well.
  2. He warned about the dangers of overregulating artificial intelligence, highlighting the importance of keeping it free from strict rules.
  3. This speech stood out because it's rare to hear a politician articulate their thoughts clearly and effectively on such a complex topic.

Why the US military should plan for human-level AI

Faster, Please! • 365 implied HN points • 14 Feb 25
🇺🇸 U.S. Politics Artificial Intelligence
  1. The US military needs to prepare for the future of AI, especially if it reaches human-level intelligence. This preparation is crucial because AI could change how wars are fought.
  2. Unlike nuclear fission, which clearly showed its potential for destructive power, the military uses of AI are still not very clear. It's harder to see what AI can really do for military purposes right now.
  3. There are calls for a major effort, similar to the Manhattan Project, to stay ahead in AI development, particularly to prevent adversaries like China from gaining an advantage. However, the exact military benefits of advanced AI are still uncertain.

AI ❤️ Humans?

Technically Optimistic • 39 implied HN points • 14 Jun 24
🕹 Technology Artificial Intelligence
  1. It's important to have a human in the loop when deploying AI systems to validate responses and ensure ethical considerations.
  2. The decision to deploy AI should consider when it is better than humans, addressing bias, and maintaining a focus on humanity.
  3. While AI can bring solutions and efficiencies, it's crucial to remember that every data point represents a person, emphasizing the importance of human-centric AI development.

Data Science Weekly - Issue 515

Data Science Weekly Newsletter • 299 implied HN points • 06 Oct 23
🕹 Technology Artificial Intelligence
  1. There's a lot happening in data science right now. The team is considering adding a second newsletter each week to cover more exciting content.
  2. High-performing data scientists have specific traits that set them apart from others. Companies are researching these traits to help improve their teams.
  3. Art institutions can greatly benefit from data and analytics. Collaborating with leaders can help them use data to improve their operations and strategies.

A Great Interruption Begins

From The Future • 294 implied HN points • 17 Jul 23
🕹 Technology Artificial Intelligence
  1. A new era called The Great Interruption seems to be approaching, freeing us from the constant distractions and reclaiming our attention
  2. Information and attention have always been intertwined, impacting humanity's growth and evolution
  3. Interest Grids could be the future of organizing our attention, helping us navigate a world inundated with information and distractions
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In artificial intelligence the world is always what we want it to be and it is so before we act.

World Game • 7 implied HN points • 27 Jan 26
🕹 Technology Artificial Intelligence
  1. AI functions as an external world-builder rather than just mimicking human thought, creating virtual realities that can stand in for the physical world.
  2. Digitally-native activities like software development and online commerce are easiest to automate, while tasks tied to historical contingency or embodied human contexts, such as law or healthcare, will be much harder to reproduce.
  3. Building these metaverse-like worlds will be a long, fragile process full of setbacks, attacks, and competition, and it risks producing polished, wish-fulfilling fictions that distance us from a shared reality.

Data Science Weekly - Issue 512

Data Science Weekly Newsletter • 299 implied HN points • 14 Sep 23
🕹 Technology Artificial Intelligence
  1. Nvidia has been a leader in AI technology, but its dominance might not last. Changes in the market and technology could shift the competitive landscape soon.
  2. For those who know R and want to learn Python, there are resources available to help make the transition easier. These resources provide advice and tips catered to R users.
  3. Reinforcement Learning with Human Feedback (RLHF) is an important part of training large language models. It's essential for improving how these models understand and respond to human preferences.

The Sequence Opinion #774: Everything You Need to Know About Audio AI Frontier Models

TheSequence • 28 implied HN points • 18 Dec 25
🕹 Technology Artificial Intelligence
  1. Audio is a major next frontier in AI, with models now able to hear, understand, and generate speech, music, and environmental sounds at near-human levels.
  2. Audio is fundamentally different from text and images because it's a continuous, high-frequency time-series that requires modeling very long sequences and both short-term details (like phonemes or notes) and long-term structure (like phrases or whole melodies).
  3. Development is happening across open-source and commercial players, and a central debate is whether to build general multimodal systems that include audio or to focus on specialized audio models tuned for sound-specific challenges.

Sora What

Don't Worry About the Vase • 1075 implied HN points • 22 Feb 24
🕹 Technology Artificial Intelligence
  1. OpenAI's new video generation model Sora is technically impressive, achieved through massive compute and attention to detail.
  2. The practical applications of Sora for creating watchable content seem limited for now, especially in terms of generating specific results as opposed to general outputs.
  3. The future of AI-generated video content may revolutionize industries like advertising and media, but the gap between generating open-ended content and specific results is a significant challenge to overcome.

Inside AI

John Ball inside AI • 39 implied HN points • 12 Jun 24
🕹 Technology Artificial Intelligence
  1. AGI might not come from current machine learning methods. Instead, understanding how human brains work could be the key to achieving it.
  2. The theory behind brain functions can help solve AI challenges. Learning from how brains process information could lead us to better AI solutions.
  3. Language is crucial for interacting with AI. Building a trustworthy AI community focused on language can improve how we communicate and use technology.

The Sequence AI of the Week #773: The Week Google Turned Gemini Into an Agent Runtime

TheSequence • 28 implied HN points • 17 Dec 25
🕹 Technology Artificial Intelligence
  1. Google moved from just releasing models to shipping an agent runtime that coordinates and runs agents, making Gemini a platform for agent workflows.
  2. The Interactions API (Beta) and the Gemini Deep Research Agent (Preview) were released together, signaling a deliberate architectural pivot and providing both the runtime and a managed agent that uses it.
  3. Real agent systems are stateful, tool-heavy, and long-running, so most engineering effort goes into planners, tool routing, memory, retries, auditing, and UIs — the LLM call itself is the smallest piece.

What A Horse Can Tell Us About Machine Learning

Mindful Modeler • 279 implied HN points • 10 Oct 23
🕹 Technology Artificial Intelligence
  1. Animals like horses and machines can appear clever by relying on cues and shortcuts, rather than true understanding.
  2. When designing or evaluating machine learning models, watch out for 'Clever Hans Predictors' that rely on spurious correlations.
  3. To spot potential Clever Hans Predictors, look for unexpectedly good model performance, apply causal thinking, examine data closely, and use interpretation methods to investigate model behavior.

A Closer Look Into Databricks's Photon Engine

VuTrinh. • 79 implied HN points • 13 Apr 24
🕹 Technology Artificial Intelligence
  1. Photon engine uses columnar data layout to manage memory efficiently, allowing it to process data in batches. This helps in speeding up data operations.
  2. It supports adaptive execution, which means the engine can change how it processes data based on the input. This can significantly improve performance, especially when data has many NULLs or inactive rows.
  3. Photon integrates with Databricks runtime and Spark SQL, allowing it to enhance existing workloads without completely replacing the old system, making transitions smoother.

OpenAI's Reinforcement Finetuning and RL for the masses

Democratizing Automation • 427 implied HN points • 11 Dec 24
🕹 Technology Artificial Intelligence
  1. Reinforcement Finetuning (RFT) allows developers to fine-tune AI models using their own data, improving performance with just a few training samples. This can help the models learn to give correct answers more effectively.
  2. RFT aims to solve the stability issues that have limited the use of reinforcement learning in AI. With a reliable API, users can now train models without the fear of them crashing or behaving unpredictively.
  3. This new method could change how AI models are trained, making it easier for anyone to use reinforcement learning techniques, not just experts. This means more engineers will need to become familiar with these concepts in their work.

Data Science Weekly - Issue 520

Data Science Weekly Newsletter • 239 implied HN points • 10 Nov 23
🕹 Technology Artificial Intelligence
  1. Data scientists share interesting links and news weekly about AI, machine learning, and data visualization. It's a great way to stay updated on trends and tools in the field.
  2. Learning about the basics of deep learning and mathematical foundations is important for anyone starting in machine learning. Understanding key concepts helps you tackle complex problems more effectively.
  3. There are many job opportunities in data science and related fields. Keeping an eye on openings can lead to exciting career advancements and collaborations.

Artificial Intelligences in the Guanzi and the Han Feizi

Daoist Methodologies • 275 implied HN points • 20 Mar 23
🕹 Technology Artificial Intelligence
  1. Confucians and Daoists have different approaches to learning: acquiring proven vs. eliminating disproven methods.
  2. Learning can occur without a brain: different entities like dogs, rivers, and markets learn without understanding.
  3. Systems can learn independently without human input, like in the case of artificial intelligence drawing from socio-political systems described in ancient texts.

Genre Grapevine on Machine Learning’s Problem with Bad Stories and Bad Intentions

Genre Grapevine • 176 implied HN points • 29 Dec 23
🎨 Art & Illustration Artificial Intelligence
  1. Bad stories can inspire writers to improve their own writing by learning from the mistakes of others.
  2. Artists and writers have pushed back against AI dominance by engaging in strikes and filing lawsuits to protect their work from being used without permission.
  3. Machine learning programs face challenges in creating truly innovative and original art, as they often get stuck in a cycle of reproducing popular styles and lacking true imagination.

GroupBy #34: Hybrid Transactional/Analytical Storage, From Predictive to Generative – How Michelangelo Accelerates Uber’s AI Journey

VuTrinh. • 59 implied HN points • 07 May 24
🕹 Technology Artificial Intelligence
  1. Hybrid transactional/analytical storage combines different types of data processing. This helps companies like Uber manage their data more efficiently.
  2. The shift from predictive to generative AI is changing how companies use machine learning. Uber's Michelangelo platform shows how this new approach can improve AI applications.
  3. Data reliability and observability are important for businesses as their data grows. Companies need tools to quickly find and fix data issues to keep their operations running smoothly.

The ICML 2025 Outstanding Papers

Gonzo ML • 126 implied HN points • 28 Jul 25
🕹 Technology Artificial Intelligence
  1. The recent ICML 2025 Outstanding Papers show a huge amount of important research in machine learning, but many people feel overwhelmed and can't read everything in-depth.
  2. It's okay to admit that you can't keep up with all the new papers. Using AI tools can help manage the load and ensure you're still getting the important insights you need.
  3. Some of the papers focus on practical issues, like improving predictions and making AI more collaborative, which are vital for real-world applications.

AI - An Enablement Shift

Software Snack Bites • 10 implied HN points • 16 Jan 26
🕹 Technology Artificial Intelligence
  1. AI is an enablement shift, not a slow paradigm change — it's making people more capable right now because it’s easy to adopt and useful across skill levels.
  2. We’re still very early: most users treat AI as a simple answer engine, and that’s just the tip of the iceberg for self-teaching, new creators, and deeper technical work to come.
  3. Don’t dismiss the momentum — value and spending can grow quickly along an S-curve, and monetization paths like ads, commerce, and healthcare are only beginning to emerge.

Tools for thought: the first 300,000 years

Subconscious • 1660 implied HN points • 10 Jun 23
🕹 Technology Artificial Intelligence
  1. 300,000 years ago, humanity started leaving messages in rocks and clay, allowing thoughts to outlive individuals.
  2. Throughout history, humans have continuously discovered new tools for thinking, such as language, art, and technology.
  3. The shared brain of humanity has evolved over time, with increasing collaboration and technological advancements, setting the stage for thinking together to address global challenges.

Roadmap: Defense Tech

Next Big Teng • 137 implied HN points • 29 Jan 24
🕹 Technology Artificial Intelligence
  1. Defense tech landscape is evolving, and startups are now collaborating with the DOD.
  2. Government contracts are key for defense tech startups, offering revenue and validation.
  3. Innovation in AI/ML, data infrastructure, cybersecurity, vertical solutions, and autonomous systems are driving the defense technology industry.

Data Exfiltration from Slack AI via indirect prompt injection

PromptArmor Blog • 604 HN points • 20 Aug 24
🕹 Technology Artificial Intelligence
  1. There is a serious vulnerability in Slack AI that lets attackers access confidential information from private channels without needing direct access. This means sensitive data can be stolen just by manipulating how Slack AI processes requests.
  2. The risk increases with the recent Slack update that allows AI to access files shared within the platform. This could mean that harmful files uploaded by users can also be exploited to extract confidential information.
  3. Both data theft and phishing attacks can happen through crafted messages in public channels. This makes it crucial for users to be careful about what they share, because attackers can trick the AI into sharing sensitive details.

Deepseek: From Hedge Fund to Frontier Model Maker

ChinaTalk • 400 implied HN points • 09 Dec 24
🕹 Technology Artificial Intelligence
  1. High-Flyer, a hedge fund, is making big moves by venturing into AI research through a new company called DeepSeek. They want to create human-level AI instead of just copying existing models.
  2. Their success in the AI field comes from a unique hiring process that focuses on curious and passionate individuals rather than experience. This helps foster innovation within the company.
  3. Despite the high costs of running AI research, High-Flyer believes in funding their projects through a mix of their own resources and philanthropy. They prioritize long-term research over quick financial returns.

For Pete's sake, learn what a machine is.

Top Carbon Chauvinist • 19 implied HN points • 17 Jul 24
🕹 Technology Artificial Intelligence
  1. A machine is made up of parts that do work by handling loads, like electricity or mechanics. It does not actually understand or think about what it does.
  2. When programming a machine, like a catapult, you're just adjusting physical elements, not teaching it to know or understand concepts like 'rock' or 'lever'.
  3. Living things are not machines because they aren't made of manufactured parts. They grow and evolve in ways that machines cannot.

Operation Liberate Programmer

Rethinking Software • 399 implied HN points • 05 Dec 24
🕹 Technology Artificial Intelligence
  1. Scrum and its new version, Extreme Agile, focus too much on speed without considering the quality of work. This prioritization can lead to worsening job conditions for programmers.
  2. Programmers have the option to explore freelancing or starting their own businesses, especially with AI tools making it easier. This could provide more freedom and control over their work.
  3. Instead of waiting for companies to change, programmers should take action to create their own opportunities, sharing their experiences and insights to help others along the way.

Mondays with the Machine: Thinking Out Loud About the Current "AI" Boom-Bubble

Brad DeLong's Grasping Reality • 169 implied HN points • 02 Jun 25
🕹 Technology Artificial Intelligence
  1. New technologies like AI often cause panic as people worry about their impact, similar to how calculators were once banned in schools. Over time, we learn to use these tools responsibly.
  2. AI chatbots can seem human-like, but they are actually complex tools for finding information. Instead of treating them like people, we should learn how to use them effectively for our needs.
  3. While AI can generate a lot of ideas quickly, it lacks the depth and truthfulness that history provides. History gives us valuable lessons, but AI can still help spark new thoughts and start conversations.

How LibreOffice and Markdown Can Become The Future of AI Productivity

Experiments with NLP and GPT-3 • 7 implied HN points • 05 Feb 26
🕹 Technology Artificial Intelligence
  1. Native Markdown support makes documents much easier for AI to read and process because Markdown preserves structure without hidden formatting noise.
  2. Treating spreadsheets and presentations as web-first formats (JSON, HTML, JavaScript) lets AI generate live, interactive data views and dynamic, responsive slides instead of static files.
  3. Focusing on open standards, interoperability, and reliability builds the infrastructure that actually makes AI useful, instead of chasing flashy but brittle agent features.

Joe's Nerdy Rants #9

Joe Reis • 255 implied HN points • 15 Jul 23
🕹 Technology Artificial Intelligence
  1. Data modeling in the industry is often ignored or undervalued.
  2. There is a trend towards 'query-driven modeling' or 'just-in-time modeling.'
  3. The question is raised about the importance of data modeling and its impact on businesses.

Data Science Weekly - Issue 510

Data Science Weekly Newsletter • 279 implied HN points • 31 Aug 23
🕹 Technology Artificial Intelligence
  1. Autonomous drones can now race at human champion levels using deep reinforcement learning. This shows how advanced technology can mimic skilled human behavior in competitive sports.
  2. Google is rapidly developing its AI capabilities and plans to surpass GPT-4 by a significant margin soon. This could lead to more powerful AI tools for various applications.
  3. Reinforced Self-Training (ReST) is a new method for improving language models by aligning their outputs with human preferences. It offers better translation quality and can be done efficiently with less data.

Humans—and GPT-4—are predictably irrational

The Counterfactual • 219 implied HN points • 07 Nov 23
🕹 Technology Artificial Intelligence
  1. Humans often make decisions based on emotions and biases, rather than pure logic. This means they're not always rational, which is important to understand.
  2. Large language models like GPT-4 can show similar irrational behaviors. They can make mistakes in judgment much like humans do, which gives insight into how we think.
  3. The way people attribute beliefs to others can change based on the situation. When faced with strong pressures, people are less likely to jump to conclusions about someone's beliefs.

Engineering Management in the Age of Agents

Leading Developers • 100 implied HN points • 12 Aug 25
🕹 Technology Artificial Intelligence
  1. Engineering managers play a crucial role in bridging the gap between technical and business sides. They need to understand what customers want and how the business works to effectively communicate and create roadmaps.
  2. Good communication is key for engineering managers, especially when mentoring new engineers. Clear expectations and understanding of the desired outcomes can help prevent misunderstandings and improve the coding process.
  3. People skills are essential in engineering management. As AI tools become more common, being able to manage relationships and navigate challenges with team members will remain an important advantage.

"AI Won't Take Your Job, a Person Using AI Will"—Yes, You Using AI Will Replace You Not Using It

The Algorithmic Bridge • 392 implied HN points • 11 Dec 24
🕹 Technology Artificial Intelligence
  1. Embracing AI tools is essential. If you don't use them, someone who does will likely take your place.
  2. Technology is becoming a part of our lives whether we like it or not. You might not notice it, but AI is already in everyday tools that can help you do better.
  3. It's common to resist new tech because we feel comfortable, but eventually, we adapt. Just like we moved from pencils to keyboards, we will embrace AI too.

Robotics startups vs other startups

Robots & Startups • 119 implied HN points • 11 Feb 24
🕹 Technology Artificial Intelligence
  1. The number of venture-backed U.S. startups has significantly increased over the years, with a particularly notable growth in robotics startups.
  2. Compared to all startups, robotics startups have seen a much larger growth percentage, showcasing the significant expansion of the robotics industry.
  3. OpenAI's achievement of reaching $2B in revenue marks it as the fastest growing startup ever, demonstrating the potential for success in the robotics field.

Augmented Coding: Coached by the Genie

Software Design: Tidy First? • 154 implied HN points • 11 Jun 25
🕹 Technology Artificial Intelligence
  1. Improvement is great, but when improvements lead to even more rapid progress, that’s revolutionary. We should strive for advancements that keep building on each other.
  2. There are limits to how much we can improve, influenced by natural laws. This means while we can grow, there will also be things that slow us down.
  3. Having support or guidance, like a 'genie', can help us make better progress. It’s helpful to have tools or mentors that guide us in our journey.

Captain's log: the irreducible weirdness of prompting AIs

One Useful Thing • 902 implied HN points • 04 Mar 24
🕹 Technology Artificial Intelligence
  1. Stop trying to use incantations: There is no single magic word that works all the time with AIs. Promising rewards or being polite may help occasionally, but not always.
  2. There are prompting techniques that work consistently: Techniques like adding context to prompts, providing a few examples, and using Chain of Thought can help in crafting better prompts for AIs.
  3. Prompting matters significantly: The way you prompt AIs can have a huge impact on the outcomes. Good prompts can turn a difficult task into an easy one for AI.