The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

Joe's Nerdy Rants - #1

Joe Reis • 157 implied HN points • 20 May 23
🕹 Technology AI
  1. Joe Reis has started a weekend newsletter about data and tech.
  2. Newsletters are great for weekend reading when people have more time.
  3. The newsletter will feature tech or data-oriented rants from Joe, offering interesting insights.

The case for machines to forget

Methexis • 157 implied HN points • 12 Apr 23
🕹 Technology AI
  1. Memory is important, but efficient forgetting is also crucial for transforming machines.
  2. Humans are abstraction learners and focus on efficient representations of new concepts.
  3. Forgetting unnecessary details can be key to approaching and solving seemingly unsolvable problems.

Weekly Top Picks #97

The Algorithmic Bridge • 191 implied HN points • 10 Feb 25
🕹 Technology AI
  1. Google has released impressive AI models that are both high-quality and affordable. They are competing strongly in the AI space.
  2. OpenAI is developing new AI agents to assist programmers and sales teams, indicating a focus on practical business applications.
  3. Sam Altman highlighted that the intelligence in AI improves at a super-exponential rate, making its economic value increase rapidly.
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Exploring the Purpose, Power & Potential of Small Language Models (SLMs)

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 59 implied HN points • 11 Mar 24
🕹 Technology AI
  1. Small Language Models (SLMs) can effectively handle specific tasks without needing to be large. They are more focused on doing certain jobs well rather than trying to be everything at once.
  2. The Orca 2 model aims to enhance the reasoning abilities of smaller models, helping them outperform even bigger models when reasoning tasks are involved. This shows that size isn't everything.
  3. Training with tailored synthetic data helps smaller models learn better strategies for different tasks. This makes them more efficient and useful in various applications.

203. Software As Part of Everything Is Regulated…As Part of Everything

Hardcore Software • 337 implied HN points • 19 Apr 23
🕹 Technology AI
  1. Software has become a fundamental part of our lives, evolving from its origins in math to touching every aspect of human endeavors.
  2. Regulations have always been key in governing software, ensuring safety, reliability, and functionality in various industries.
  3. The introduction of AI should follow the established regulatory frameworks for software, without seeking a separate or special exemption.

The Sequence Research #543: The Leaderboard Illusion Challenges Chatbot Arena Type Benchmarks

TheSequence • 119 implied HN points • 16 May 25
🕹 Technology AI
  1. Leaderboards in AI help direct research by showing who is doing well, but they can also create problems. They might not show the whole picture of how models really perform.
  2. The Chatbot Arena is a way to judge AI models based on user choices, but it has issues that make it unfair. Some big labs can take advantage of the system more than smaller ones.
  3. To make AI evaluations better, there need to be rules that ensure fairness and transparency. This way, everyone gets a fair chance in the AI race.

Top 5 US-China Tech Stories

ChinaTalk • 637 implied HN points • 04 Jan 24
🕹 Technology AI
  1. TikTok has defied early predictions of regulatory restrictions in the US due to vested interests and political dynamics.
  2. The splintering of cross-border VC firms like Sequoia and GGV Capital is a tangible impact of US-China relations.
  3. Chinese EVs are dominating globally, posing a challenge to traditional automakers and highlighting the US infrastructure gap.

Applied Digital, Defense Semiconductors, and 1998

Mule’s Musings • 96 implied HN points • 09 Jun 25
🕹 Technology AI
  1. Applied Digital focuses on combining technology with government projects. This partnership can lead to innovation and improved efficiency in services.
  2. Defense semiconductors are crucial for national security. They help in developing advanced technologies used in defense systems.
  3. Understanding the history of technology and its applications, like in 1998, gives insight into current trends and future developments. Learning from the past is important for progress.

The AI Elephant in the Boardroom

Condensing the Cloud • 137 implied HN points • 01 Nov 23
🕹 Technology AI
  1. AI is becoming a major focus for tech companies and investors.
  2. Companies are increasingly mentioning AI in earnings calls, impacting stock performance.
  3. Investor enthusiasm for AI is driving stock price increases and reshaping company roadmaps.

Can AI Make You A Better Beer Drinker?

Can We Still Govern? • 78 implied HN points • 13 Jul 25
🍲 Food & Drink AI
  1. AI can help you pick beers at a festival by suggesting choices based on your preferences, but it might not always be accurate about what's available.
  2. Getting to know different beers and enjoying the experience can be more fun than just following a strict plan; sometimes it's better to go with the flow.
  3. Eating balanced foods can help you enjoy drinking earlier in the day by slowing alcohol absorption and keeping your energy up.

Will AI lead to more "managed" security services?

Frankly Speaking • 101 implied HN points • 29 May 25
🕹 Technology AI
  1. AI is set to change the way security services operate by taking over repetitive tasks. This means teams can focus on more important work instead of getting bogged down by routine maintenance.
  2. With AI managing security tasks, new types of services will emerge that work better and require fewer people. This helps businesses save costs and improves consistency in security measures.
  3. Instead of fearing job loss, security professionals should see AI as a tool that helps them do their jobs better. AI can handle tedious tasks, allowing security teams to focus on critical areas like designing better security systems.

Why Technology Creates More Jobs

The Digital Anthropologist • 19 implied HN points • 17 Jun 24
🕹 Technology AI
  1. Technology often creates more jobs rather than eliminating them. New technologies can lead to the creation of specialized roles that were previously unheard of.
  2. The fear of job losses due to technology arises from a perceived threat to social norms and behaviors. Revolutionary technologies like AI impact not just work but also how we envision our world and shared realities.
  3. Artificial General Intelligence (AGI) is unlikely in the near future. Instead, AI will likely augment human capabilities, leading to the creation of new specialized jobs and the evolution of work's meaning.

Weighing in on Casey Newton's "AI is fake and sucks" debate

The Future, Now and Then • 237 implied HN points • 10 Dec 24
🕹 Technology AI
  1. AI is real, but there's a lot of hype around it. It's important to be skeptical and not just believe everything that's promised.
  2. Critics of AI might have valid concerns even if they sometimes say things that sound extreme. Their worries come from seeing the tech's limitations and potential dangers.
  3. When tech leaders make big promises about AI, we should be cautious. Just because some progress has been made doesn't mean all their predictions will come true.

OLMo 2 and building effective teams for training language models

Democratizing Automation • 245 implied HN points • 26 Nov 24
🕹 Technology AI
  1. Effective language model training needs attention to detail and technical skills. Small issues can have complex causes that require deep understanding to fix.
  2. As teams grow, strong management becomes essential. Good managers can prioritize the right tasks and keep everyone on track for better outcomes.
  3. Long-term improvements in language models come from consistent effort. It’s important to avoid getting distracted by short-term goals and instead focus on sustainable progress.

Chinese AI is crushing tech stocks

Alex's Personal Blog • 197 implied HN points • 27 Jan 25
🕹 Technology AI
  1. Chinese AI models are affecting American tech stocks negatively, causing major declines in companies like Nvidia and Microsoft. This raises questions about how competitive American AI firms really are.
  2. The large amounts of money American tech companies are spending on AI hardware might be wasted since Chinese models like DeepSeek can do similar work with less investment.
  3. There are some positives, like the potential for learning from DeepSeek's open-source models, and the company is limited by government rules, which helps maintain competition.

Math Discovery, Long-Context Memory, and the Limits of Multimodal Reasoning

HackerPulse Dispatch • 13 implied HN points • 19 Dec 25
🕹 Technology AI
  1. AlphaEvolve demonstrates AI agents can autonomously discover and improve mathematical constructions, generalize finite solutions into universal formulas, and integrate with proof assistants for verification.
  2. MMGR shows that image and video models produce convincing visuals but largely fail at causal and abstract reasoning (often <10% accuracy), revealing a major gap between perceptual quality and true world understanding.
  3. Advances in model design and decoding are pushing capabilities: QwenLong-L1.5 enables reasoning over 4M-token contexts using synthetic multi-hop data, stabilized RL, and memory-augmented architectures, and ReFusion speeds text generation by decoding in parallel with a plan-and-infill diffusion approach.

Links for 2024-01-31

Axis of Ordinary • 78 implied HN points • 31 Jan 24
🕹 Technology AI
  1. SliceGPT offers a way to reduce model parameters while maintaining performance.
  2. Apple's Rephrasing the Web focuses on efficient language modeling.
  3. ADEPT's Fuyu-Heavy model outperforms Gemini Pro in certain areas.

The new philosophers

benn.substack • 1048 implied HN points • 07 Apr 23
🕹 Technology AI
  1. The modern data stack evolved from Hadoop to cloud data warehouses, ushering in new tools and companies.
  2. The modern data stack has led to tool proliferation and challenges like disconnected systems and high costs.
  3. Artificial Intelligence is poised to be the next big disruptor in the data ecosystem, potentially leading to a shift away from the modern data stack.

Large Impact: The Rise of Small Language Models

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 59 implied HN points • 07 Mar 24
🕹 Technology AI
  1. Small Language Models (SLMs) are becoming popular because they are easier to access and can run offline. This makes them appealing to more users and businesses.
  2. While Large Language Models (LLMs) are powerful, they can give wrong answers or lack up-to-date information. SLMs can solve many problems without these issues.
  3. Using Retrieval-Augmented Generation (RAG) with SLMs can help them answer questions better by providing the right context without needing extensive knowledge.

#2: Search continues for someone with an opinion on AI

12challenges • 171 implied HN points • 24 Feb 25
🕹 Technology AI
  1. There's a lot of chatter around AI, and it can feel overwhelming with so many opinions coming from everywhere. Not everyone can be right, and sometimes it’s nice to take a step back.
  2. The writer is working on making their tech publication more engaging, including designing a cool interactive button that enhances the reader experience. Adding fun elements can make a project feel exciting.
  3. Getting back into the habit of writing and sharing can be challenging, but it's important to push through and not aim for perfection. Staying persistent is key to finding your audience.

Insight Into Sam Altman's Firing From OpenAI

72 Degrees North • 139 implied HN points • 18 Nov 23
🕹 Technology AI
  1. Sam Altman's firing from OpenAI was surprising but predictable.
  2. Silicon Valley's focus is shifting towards big-game reputation building using AI products.
  3. The use of AI for reputation manipulation has the potential to dramatically impact individuals, companies, and nations.

Compound AI is AGI

Generating Conversation • 233 implied HN points • 13 Dec 24
🕹 Technology AI
  1. The debate about whether we've achieved AGI (Artificial General Intelligence) is ongoing. Many people don't agree on what AGI really means, making it hard to know if we've reached it.
  2. The argument is that current AI models can work together to perform tasks at a human-like level. This teamwork, or 'compound AI,' could be seen as a form of general intelligence, even if it's not from a single AI model.
  3. Not all forms of intelligence are the same, and AI systems can do things that humans can’t, but that doesn't mean they can't be considered intelligent. The future potential of AI isn't just about mimicking human intellect; it may also involve different types of skills and knowledge.

Introducing React Native AI

Nader's Thoughts • 117 implied HN points • 27 Nov 23
🕹 Technology AI
  1. React Native AI is a framework for building cross-platform mobile AI apps with various features like real-time responses, image processing, and pre-built chat UI components.
  2. React Native AI saves time by providing preconfigured components for handling tasks like LLM normalization, OpenAI Assistants, and theming/styling.
  3. To get started with React Native AI, run the command 'npx rn-ai' and configure environment variables based on the desired services to try out.

The last generation of programmers

Brick by Brick • 63 implied HN points • 04 Aug 25
🕹 Technology AI
  1. AI is changing programming in a big way. Soon, machines might do most of the coding, leaving fewer jobs for human programmers.
  2. Just like how cars created new jobs when horses disappeared, AI will lead to new roles focused on guiding and managing these technologies.
  3. In the future, software creation might be easier for everyone. People will share ideas, and AI will turn those ideas into working software quickly.

Pratik's Year in Review: 2025

Pratik’s Pakodas 🍿 • 8 implied HN points • 02 Jan 26
🕹 Technology AI
  1. AI agents and skill-based subagents let you run many tasks in parallel and move work forward continuously. This shifts the role from single-threaded coder to an orchestrator who delegates, evaluates, and scales output.
  2. Building a community depends on habits and critical mass more than platform features; migrating people to a new platform requires heavy outreach, patience, and active admins. Tools help, but sustained engagement is earned through social habits, not just better functionality.
  3. Measure and design life around 'great days' by engineering conditions that produce them — prioritize sleep, consistent healthy habits, slack time, and small experiments. Small rituals and intentional choices matter more for long-term happiness than chasing big achievements.

LLM links, 11/17

In My Tribe • 243 implied HN points • 18 Nov 24
🕹 Technology AI
  1. AI agents are most helpful when they can repeat simple tasks many times, rather than doing complex, one-time jobs. It’s better to have them automate quick tasks consistently.
  2. Chatbots face serious challenges, especially when discussing sensitive topics like suicide. They should guide users to seek help but also create a safe conversation environment.
  3. There’s concern that new AI models may not improve in accuracy and could actually make mistakes more often. This suggests that AI will always struggle to tell the truth from lies.

An algorithm for quality

Substack Blog • 774 implied HN points • 19 Sep 23
🕹 Technology AI
  1. Algorithms can serve to feed the basest version of ourselves
  2. Technology platforms should aim to serve the best version of the user
  3. Reading with agency and curating your attention can lead to a more fulfilling experience

Inside Pulley's AI-Native Engineering Team

Artificial Ignorance • 92 implied HN points • 18 Jun 25
🕹 Technology AI
  1. Using AI regularly helps small teams work efficiently. By leveraging AI tools, even a small engineering team can compete with much larger companies.
  2. It's important to foster a culture of experimentation with AI. When team members are excited about trying new AI tools and sharing what they learn, it boosts overall productivity.
  3. Skills are shifting from direct coding to more strategic tasks like writing specifications. As AI becomes more capable, being able to communicate ideas clearly and manage these tools is becoming crucial.

How I use chatGPT

The Common Reader • 921 implied HN points • 09 Jun 23
🕹 Technology AI
  1. The author discusses using ChatGPT for writing and editing, including feedback on a book manuscript.
  2. ChatGPT provided accurate summaries and assessments, along with helpful prompts for editing and copywriting.
  3. The post highlights utilizing ChatGPT for various tasks like book manuscript feedback, editing prompts, and copywriting assistance.

DeepSeek V3 and R1

From the New World • 188 implied HN points • 28 Jan 25
🕹 Technology AI
  1. DeepSeek has released a new AI model called R1, which can answer tough scientific questions. This model has quickly gained attention, competing with major players like OpenAI and Google.
  2. There's ongoing debate about the authenticity of DeepSeek's claimed training costs and performance. Many believe that its reported costs and results might not be completely accurate.
  3. DeepSeek has implemented several innovations to enhance its AI models. These optimizations have helped them improve performance while dealing with hardware limits and developing new training techniques.

Data Science Weekly - Issue 485

Data Science Weekly Newsletter • 319 implied HN points • 09 Mar 23
🕹 Technology AI
  1. The newsletter shares interesting links about data science, machine learning, and AI each week. It’s a good way to keep up with new trends and knowledge in the field.
  2. There's a discussion on what databases should do but often don’t. Understanding these gaps can help you improve your data projects by knowing what to build yourself.
  3. AI's impact on jobs and industries is being researched, especially how language models like ChatGPT could change certain occupations. It's important to understand how AI can affect your career choices.

What Does Hitting Scaling Law Limit Mean for US-China AI Competition

Interconnected • 246 implied HN points • 18 Nov 24
🕹 Technology AI
  1. The scaling law for AI models might be losing effectiveness, meaning that simply using more data and compute power may not lead to significant improvements like it did before.
  2. US export controls on AI technology may become less impactful over time, as diminishing returns on AI model scaling could lessen the advantages of having the most advanced hardware.
  3. If AI development slows down, the urgency for a potential 'AI doomsday' scenario may decrease, allowing for a more balanced competition between the US and China in AI advancements.

The Sequence Weekly Alpha #686: Kimi K2 is a Trillion Parameter Open Source Model You Must Know About

TheSequence • 77 implied HN points • 16 Jul 25
🕹 Technology AI
  1. Kimi K2 is a huge open source AI model with a trillion parameters, which makes it very powerful. It's important to know about advancements like this, especially as they can change how we use AI.
  2. The model uses a special design called Mixture-of-Experts that improves its efficiency. This means it can perform tasks better by only activating the parts it needs to.
  3. Kimi K2 shows strong performance in areas like coding and reasoning. This highlights how rapidly AI is evolving, and we need to keep up with newer developments from around the world.

The GPT Era

Artificial Ignorance • 79 implied HN points • 10 Jul 25
🕹 Technology AI
  1. The development of AI from models like GPT-3 to GPT-4 has seen rapid improvements in technology and user experience. Each version has made it easier for people to interact with AI in more useful ways.
  2. Competition in the AI market has led to better products and features, such as enhanced memory, web integration, and advanced coding tools. Now many companies offer similar core functions, making it important to focus on product design and user experience.
  3. As AI continues to evolve, there's a growing focus on reasoning models that help systems think more deeply. This shift will be important for making AI even more effective and adaptable in the future.