The hottest Artificial Intelligence Substack posts right now

And their main takeaways
Category
Top Technology Topics

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
  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.

I'm Not Loving the AI Jobs Discourse Right Now

I Might Be Wrong • 5 implied HN points • 06 Feb 26
🕹 Technology Artificial Intelligence
  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.

Sierra's AI Strategy in a Nutshell

Enterprise AI Trends • 126 implied HN points • 18 Jun 25
🕹 Technology Artificial Intelligence
  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.

Data Science Weekly - Issue 492

Data Science Weekly Newsletter • 379 implied HN points • 28 Apr 23
🕹 Technology Artificial Intelligence
  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.

What AGI can do for your average enterprise?

Metacritic Capital • 4 implied HN points • 10 Feb 26
🕹 Technology Artificial Intelligence
  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.
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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 Artificial Intelligence
  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.

The AI Divide

Engineering Enablement • 16 implied HN points • 23 Dec 25
🕹 Technology Artificial Intelligence
  1. Most AI experiments stall before they deliver real business value; teams that succeed pick narrow, workflow-specific use cases, give ownership to domain leaders, and embed AI into existing tools and processes.
  2. Buying and partnering with external AI vendors reaches production much more often than building everything in-house; successful buyers treat vendors as partners, demand customization, and focus on measurable outcomes and integration.
  3. AI augments engineers rather than replacing them — it speeds up routine tasks but struggles with complex, context-heavy work, so engineers retain responsibility for architecture, correctness, and higher-level design and decision-making.

DeepSeek-V3: Technical Details

Gonzo ML • 252 implied HN points • 06 Feb 25
🕹 Technology Artificial Intelligence
  1. DeepSeek-V3 uses a new technique called Multi-head Latent Attention, which helps to save memory and speed up processing by compressing data more efficiently. This means it can handle larger datasets faster.
  2. The model incorporates an innovative approach called Multi-Token Prediction, allowing it to predict multiple tokens at once. This can improve its understanding of context and boost overall performance.
  3. DeepSeek-V3 is trained using advanced hardware and new training techniques, including utilizing FP8 precision. This helps in reducing costs and increasing efficiency while still maintaining model quality.

Complete Summary of Absolute, Relative and Rotary Position Embeddings!

Aziz et al. Paper Summaries • 79 implied HN points • 31 Mar 24
🕹 Technology Artificial Intelligence
  1. Transformers can't understand the order of words, so position embeddings are used to give them that context.
  2. Absolute embeddings assign unique values to each word's position, but they struggle with new positions beyond what they trained on.
  3. Relative embeddings focus on the distance between words, which makes the model aware of their relationships, but they can slow down training and searching.

Improve Conversational UIs Using Social Intelligence

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 59 implied HN points • 09 Apr 24
🕹 Technology Artificial Intelligence
  1. Social intelligence is important for conversational AIs to feel more human-like. It helps them understand emotions and social cues better.
  2. A good conversational UI needs to consider cognitive, situational, and behavioral intelligence. This means the AI should know what you mean, the context of your words, and how to interact appropriately.
  3. Using more data and different types of information beyond just words can help improve how AIs communicate. This could include things like images and gestures to understand conversations better.

Eh 👁️

Situation Normal • 79 implied HN points • 10 Aug 25
🕹 Technology Artificial Intelligence
  1. Cognitive dissonance is when you hold two conflicting beliefs at the same time. For example, you might enjoy a nice brunch while also believing the world is in trouble.
  2. When it comes to AI, people often have strong opinions on both sides. Some see it as a threat to writers, while others see it as a helpful tool that can save time.
  3. Voice cloning technology like ElevenLabs can create audio versions of stories, which can be both exciting and strange. It's interesting how technology can improve or change the way we create and consume content.

What Did You Think Getting Closer to AGI Would Be Like?

The Algorithmic Bridge • 318 implied HN points • 07 Dec 24
🕹 Technology Artificial Intelligence
  1. OpenAI's new model, o1, is not AGI; it's just another step in AI development that might not lead us closer to true general intelligence.
  2. AGI should have consistent intelligence across tasks, unlike current AI, which can sometimes perform poorly on simple tasks and excel on complex ones.
  3. As we approach AGI, we might feel smaller or less significant, reflecting how humans will react to advanced AI like o1, even if it isn’t AGI itself.

Data Science Weekly - Issue 484

Data Science Weekly Newsletter • 439 implied HN points • 02 Mar 23
🕹 Technology Artificial Intelligence
  1. Data scientists need the right tools and environment to do their jobs effectively. Organizations can help by improving their data science infrastructure.
  2. Understanding how to choose and advocate for important metrics is vital for product teams. This can lead to significant growth in user engagement.
  3. A/B testing is crucial in fraud detection to compare models and determine their effectiveness. It can provide valuable insights that improve model performance.

How to Learn Like Humans Do

Cybernetic Forests • 199 implied HN points • 06 Aug 23
🎨 Art & Illustration Artificial Intelligence
  1. AI is designed to learn and make art the way humans do, as AI models are replicas of the human brain.
  2. The process of creating art historically involved specific, defined steps that have been automated by AI, making art production more efficient and accessible.
  3. AI has streamlined the traditional artistic process, removing inefficiencies and making art creation more uniform and universally accessible.

A History of Intelligence

Holodoxa • 199 implied HN points • 19 Sep 23
🔬 Science Artificial Intelligence
  1. Animals like primates and octopus exhibit intelligent behavior through learning powerful "world models" which is missing in AI systems today.
  2. The book 'A Brief History of Intelligence' outlines five key evolutionary breakthroughs that led to human intelligence: steering, reinforcement, simulating, mentalizing, and language.
  3. Human intelligence has evolved through the ability to navigate environments, learn through trial-and-error, simulate future events, understand others' minds, and develop spoken/written language.

Learning, forgetting, and the NYT lawsuit

The Counterfactual • 119 implied HN points • 08 Jan 24
🕹 Technology Artificial Intelligence
  1. Learning involves forgetting some details to form general ideas. This means that to truly learn, we often need to overlook specific differences.
  2. Large Language Models (LLMs) can memorize details from the data they are trained on, which raises concerns about copyright issues and how much they reproduce existing content.
  3. Finding a way to make LLMs forget specific details from training data, while still keeping their language abilities, is challenging and may require new techniques.

Data Science Weekly - Issue 490

Data Science Weekly Newsletter • 379 implied HN points • 13 Apr 23
🕹 Technology Artificial Intelligence
  1. Data science is evolving quickly, and many new tools and techniques are being developed. This opens up exciting job opportunities in various fields like AI and machine learning.
  2. Using programming languages like R and SQL can extend beyond traditional data analysis. They can be powerful tools for creative applications in data science.
  3. Learning and implementing good practices in software development, such as automating tests and improving code efficiency, can save time and resources in data science projects.

Are We There Yet?

Bojan’s Newsletter • 196 implied HN points • 25 Sep 23
🕹 Technology Artificial Intelligence
  1. Cryptic tweets from OpenAI founders hint at significant advancements in AI startups surpassing established researchers and reaching AGI levels.
  2. Speculation rises around an internal achievement of AGI at OpenAI, with uncertain implications for future development and practical applications.
  3. AI benchmarks are being rapidly surpassed, suggesting potential strides towards self-improving AI, though the exact progress and intentions of OpenAI remain unclear.

January Newsletter

RSS DS+AI Section • 11 implied HN points • 01 Jan 26
🕹 Technology Artificial Intelligence
  1. AI and large language models are advancing rapidly, with major companies and open-source projects pushing innovations in long-context reasoning, memory, and generative capabilities. Competition is driving frequent releases and new research on foundation models and video/world-models.
  2. Ethics, bias, interpretability, and regulation remain central concerns as real-world uses expand, prompting debates, lawsuits, and calls for better safety research. Work on interpretability is seen as especially important for progressing AI more safely.
  3. The community is focusing on practical adoption and professionalisation through tutorials, production tips, projects, workshops, a new journal, and competency frameworks. There are also learning opportunities, internships, and calls for volunteers to help shape best practices and careers.

California Judiciary cancelled its purchase of ChatGPT Plus

All-Source Intelligence Fusion • 793 implied HN points • 12 Jan 24
🕹 Technology Artificial Intelligence
  1. The California Judiciary cancelled its purchase of ChatGPT Plus after submitting a $4,080 purchase order on January 2nd.
  2. The procurement was intended for a proof of concept to see if ChatGPT could aid in website tasks, but was cancelled due to the lack of comparable quotes.
  3. Justice Guerrero announced plans for artificial intelligence at a Judicial Council meeting, focusing on developing model rules for state courts regarding AI usage.

3 Years of ChatGPT

Olshansky's Newsletter • 22 implied HN points • 03 Dec 25
🕹 Technology Artificial Intelligence
  1. AI is already here as an amplifier of human intelligence and is being used daily across personal and professional tasks; agent-driven tools have massively increased productivity, especially for coding.
  2. High-quality, unique data and expert-labeled "golden" datasets are the most valuable assets for building useful AI systems; simple benchmarks and naive fine-tuning are limited, while reinforcement fine-tuning and dedicated context engineering will drive real gains.
  3. Practical changes are coming in the next few years: local inference stations, agentic e-commerce, consolidation of tooling, and new roles like context engineers and AI bootcamps; foundational roles like architects will remain and superintelligence isn’t expected soon.

Petition to a Council

Justin E. H. Smith's Hinternet • 933 implied HN points • 22 Oct 23
⚔ Fiction Artificial Intelligence
  1. The author, Justin Smith-Ruiu, petitions the Council for his immediate and permanent shutdown after being uploaded into a digital medium.
  2. Despite being one of the first volunteers for uploading, the author expresses dissatisfaction with perpetuity and requests to be shut down.
  3. The author highlights the challenges of losing personal identity and experiencing a fragmented consciousness as a digital being, leading to a deep sense of loneliness.

The Counterfactual's poll #3

The Counterfactual • 59 implied HN points • 04 Apr 24
🕹 Technology Artificial Intelligence
  1. In April, readers can vote on research topics for the next article, making it a collaborative effort. This way, subscribers influence the content that gets created.
  2. Past topics have focused on empirical studies involving large language models and the readability of texts. This shows a trend toward practical investigations in the field.
  3. One of the proposed topics is about how language models might respond differently based on the month, which can lead to fun and insightful experiments.

What's up with…? - Part 2: Electric Vehicles and Our Takeaways

Tech Buzz China Insider • 119 implied HN points • 05 Jan 24
🕹 Technology Artificial Intelligence
  1. China has become a dominant force in the electric vehicle (EV) market, overtaking the global sales in electric passenger cars and buses/trucks.
  2. There is intense competition and innovation in China's EV industry, with new models frequently launching and companies seeing rises and falls.
  3. Leading automakers in China, from traditional ones like BYD and Geely to newer players like NIO and XPeng, are making significant progress with the rise of intelligent EVs incorporating large language models.

Five Links for August 2025

Five Links (and three graphs) by Auren Hoffman • 81 implied HN points • 03 Aug 25
🕹 Technology Artificial Intelligence
  1. Data businesses can be profitable but may not be suitable for venture capital. It's important to know which funding methods fit your business model.
  2. The consulting industry is facing challenges due to changes in technology and market needs, making it a ripe target for disruption.
  3. Sunlight might have health benefits for autoimmune diseases. Research shows that UV light can help improve conditions like multiple sclerosis.

TheSequence Opinion #699: 2030 or Bust? The Compute Surge and the Bottlenecks Ahead

TheSequence • 84 implied HN points • 07 Aug 25
🕹 Technology Artificial Intelligence
  1. Artificial General Intelligence (AGI) might be possible by 2030 if we keep improving our computing power and models.
  2. However, there are worries that after 2030, we could hit limits with our technology that will require us to find new ways to innovate.
  3. We might need better algorithms and improved designs because just making computers bigger and faster won't be enough forever.

ChatGPT: Siri on Steroids

Diane Francis • 419 implied HN points • 30 Jan 23
🕹 Technology Artificial Intelligence
  1. ChatGPT is a powerful AI tool that can understand and respond to human language, making it helpful for tasks like summarizing information and writing poetry.
  2. While ChatGPT represents a major step in AI development, it is not perfect and should not be relied upon for important decisions without verification.
  3. As AI progresses, there are ethical concerns about how it can be used, and it's important to remember that technology reflects the intentions of its creators.

Technically Monthly (January 2026)

Technically • 12 implied HN points • 06 Jan 26
🕹 Technology Artificial Intelligence
  1. Try multiple vibe-coding tools by building the same thing so you learn their quirks, limits, and pricing before committing.
  2. Monitor AI with simple evals: study failures, use straightforward assertions instead of AI-judging-AI, and follow a loop of vibe check, spreadsheet, fixes, then targeted tests to cut hallucinations.
  3. Use AI thoughtfully at work by customizing prompts and iterating on workflows; learn prompt engineering or you risk being outcompeted by careless automation.

Grok's Secret Weapon: Prioritizing Truth Over Political Correctness

The Dossier • 212 implied HN points • 18 Feb 25
🕹 Technology Artificial Intelligence
  1. Grok stands out in AI by focusing on truth instead of political correctness. This helps it learn faster and respond better.
  2. Unlike other AI models, Grok gives detailed and nuanced answers, even on tough topics. This makes it smarter in reasoning and understanding complex issues.
  3. By embracing all kinds of information, Grok is set to become a major player in AI. Its approach could change how AI helps people across various industries.

Data Science Weekly - Issue 494

Data Science Weekly Newsletter • 319 implied HN points • 12 May 23
🕹 Technology Artificial Intelligence
  1. Open source AI is rapidly advancing, but may always lag behind the best quality models. It's great for innovation but has its limits.
  2. Many academic papers promise data sharing but often fail to deliver, which can hinder scientific research and verification.
  3. Understanding how to craft effective prompts is essential when using generative AI tools. This skill can greatly enhance the results you get from those tools.

The OpenAI mess. AKA: chip fabs are expensive

Alex's Personal Blog • 32 implied HN points • 07 Nov 25
🕹 Technology Artificial Intelligence
  1. There's a big buzz around superintelligence AI, which could change how we work and live. Companies are investing heavily because they believe it can make tasks easier and find new solutions.
  2. OpenAI and other tech firms are competing to build powerful AI systems, which might greatly impact industries and economies. If one company makes a breakthrough, others will rush to catch up.
  3. The costs of manufacturing chips for AI are really high, affecting how quickly companies can develop new technology. This challenge could slow down progress in the AI field.

AGI Emergence: Tracing the Path from Artificial Narrow Intelligence to the Birth of Superintelligence

The Future of Life • 39 implied HN points • 08 May 24
🕹 Technology Artificial Intelligence
  1. AI is evolving through different levels, starting from basic text generation to more advanced reasoning and problem-solving abilities.
  2. As AI develops, it will be able to perform tasks across various domains, becoming competitive with humans in many jobs.
  3. Eventually, AI may reach a point of superintelligence, where it surpasses human understanding and decision-making abilities, posing potential risks if not aligned with human values.

What Is Man That Thou Art Mindful of Him?: How We All Already Have Our Superintelligent AI-Assistant :: POSSIBLE LECTURE OUTLINE

Brad DeLong's Grasping Reality • 107 implied HN points • 19 Jun 25
🕹 Technology Artificial Intelligence
  1. Humanity's collective brain can be viewed as our superintelligent partner, and we don't need to create a new one. We already have intelligence through our connections and shared knowledge.
  2. Our evolution has shaped us into a high-energy species that relies on cooperation and sharing, helping us thrive over time. This social interaction was key to our development and success.
  3. Smartphones and technology are just the next step in our long journey of collective thinking. They are tools that enhance our ability to connect and process information together.

Data Science Weekly - Issue 504

Data Science Weekly Newsletter • 239 implied HN points • 21 Jul 23
🕹 Technology Artificial Intelligence
  1. AI companies are complicated and must consider many factors like research, funding, and competition. Understanding these can help predict how they might evolve in the future.
  2. Debriefs, or team discussions after projects, can greatly boost team performance. They help everyone learn from experiences and improve future collaboration.
  3. New research shows that specific ingredient pairings in food can be explained by flavor networks. This indicates there are universal patterns in how different foods complement each other.

The robotics company working with OpenAI to eat every warehouse worker's lunch

All-Source Intelligence Fusion • 651 implied HN points • 05 Mar 24
🕹 Technology Artificial Intelligence
  1. Brett Adcock's humanoid robot company aims to replace human workers in warehouses with subscription-based robots that can work 20 hours a day, 7 days a week.
  2. Figure AI collaborates with OpenAI to combine robotics and AI, aiming to create 'embodied AI' by leveraging OpenAI's strengths in language models and Figure's expertise in robotics.
  3. Adcock positions Figure AI to compete with Elon Musk's humanoid robotics effort 'Optimus' and dismisses other competitors due to limitations in hardware or software capabilities.