The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

Reinforcement, evolution, and automata

Gradient Ascendant • 7 implied HN points • 26 Feb 25
🕹 Technology AI Machine Learning Computing Algorithms Automation
  1. Reinforcement learning is becoming important again, helping improve AI models by using trial and error. This allows models to make better decisions based on past experiences.
  2. AI improvements are not just for big systems but can also work on smaller models, even those that run on phones. This shows that smarter AI can be more accessible.
  3. Combining reinforcement learning with evolutionary strategies could create more advanced AI systems in the future, leading to exciting developments and solutions.

5 Key Predictions for the Data Industry in 2025

SeattleDataGuy’s Newsletter • 612 implied HN points • 07 Jan 25
🕹 Technology Data Analysis AI Data Tools Business Intelligence Data Governance
  1. Iceberg will become popular, but not every business will adopt it. Many companies want simpler solutions that fit their needs without needing lots of complicated tools.
  2. SQL isn't going anywhere; it still works well for managing and querying data. People have realized that a bit of order in data is important for getting meaningful insights.
  3. AI use will become more practical, focusing on real-world applications rather than just hype. Companies will find specific tasks to automate using AI, making their workflows more efficient.

The Sequence Radar #554 : The New DeepSeek R1-0528 is Very Impressive

TheSequence • 77 implied HN points • 01 Jun 25
🕹 Technology AI Computing Machine Learning Software Engineering
  1. The DeepSeek R1-0528 model is really good at math and reasoning, showing big improvements in understanding complicated problems.
  2. This new model can handle large amounts of data at once, making it perfect for tasks that need lots of information, like technical documents.
  3. DeepSeek is focused on making advanced AI accessible to everyone, not just big companies, which is great for developers and researchers with limited resources.

Datacenter Anatomy Part 1: Electrical Systems

SemiAnalysis • 13334 implied HN points • 14 Oct 24
🕹 Technology Datacenters AI
  1. Datacenters are crucial for AI and require significant power. As demand for AI grows, datacenters must adapt to handle higher power loads efficiently.
  2. New designs and standards are emerging in the datacenter industry. For example, Nvidia's new hardware needs liquid cooling and high power densities, which older designs can't support.
  3. Companies like Meta are making big changes to remain competitive. They scrapped older datacenters to build new ones that can handle greater energy demands and performance requirements.

The Sequence Engineering #556: Inside Anthropic's New Open Source AI Interpretability Tools

TheSequence • 49 implied HN points • 04 Jun 25
🕹 Technology AI Interpretability Open Source Research Development
  1. Anthropic is becoming a leader in AI interpretability, which helps explain how AI systems make decisions. This is important for understanding and trusting AI outputs.
  2. They have developed new tools for tracing the thought processes of language models, helping researchers see how these models work internally. This makes it easier to improve and debug AI systems.
  3. Anthropic's recent open source release of circuit tracing tools is a significant advancement in AI interpretability, providing valuable resources for researchers in the field.
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Weekly Top Picks #97

The Algorithmic Bridge • 191 implied HN points • 10 Feb 25
🕹 Technology AI Economy Marketing Software Innovation
  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.

Most Human Wins

Not Boring by Packy McCormick • 270 implied HN points • 22 Jan 25
💼 Business Strategy Economics Technology AI
  1. As technology advances, many skills we thought were unique to humans are becoming easier for machines to do. However, this doesn't mean that humans are being made irrelevant; rather, we need to find what makes us unique.
  2. The process of commoditization means that things that were once rare and valuable are now easier and cheaper to access. This opens up new opportunities for what skills can be considered valuable in a changing economy.
  3. It’s important to adapt and use the tools at our disposal creatively. As machines take over more tasks, we should focus on our human strengths and experiences, making them central to our endeavors.

The AI Wave Accelerates

Nonzero Newsletter • 485 implied HN points • 24 Jan 25
🕹 Technology AI Computing Innovation Infrastructure Climate
  1. New AI technology like OpenAI's Operator can help with tasks, but it's still not perfect and makes mistakes. This shows that AI is getting better, but we need to manage our expectations.
  2. There's a growing belief among experts that advanced AI could be here sooner than expected. This brings both excitement and concern about what it means for jobs and society.
  3. Recent events highlight the importance of careful thinking and understanding before jumping to conclusions, like in the case of undersea cable damages where initial fears of sabotage were proven wrong.

The Weekly Kaitchup #62

The Kaitchup – AI on a Budget • 159 implied HN points • 11 Oct 24
🕹 Technology AI Machine Learning Hardware Software Data science
  1. Avoid using small batch sizes with gradient accumulation. It often leads to less accurate results compared to using larger batch sizes.
  2. Creating better document embeddings is important for retrieving information effectively. Including neighboring documents in embeddings can really help improve the accuracy of results.
  3. Aria is a new model that processes multiple types of inputs. It's designed to be efficient but note that it has a higher number of parameters, which means it might take up more memory.

Weekly Dose of Optimism #129

Not Boring by Packy McCormick • 129 implied HN points • 31 Jan 25
🕹 Technology AI Transportation Space Healthcare Startups
  1. Boom Supersonic has successfully tested its XB-1 jet, marking a big step toward commercial supersonic flights. This could cut flight times significantly, like from New York to London in about three and a half hours.
  2. DeepSeek's new AI model shows it's possible to train a top-level AI for much less money than before. This could make AI more affordable and accessible for various uses.
  3. Science Corp is experimenting with brain-computer interfaces that blend lab-grown neurons with animal brains. This technology could enhance brain function and offer new treatments for neural damage.

AI #93: Happy Tuesday

Don't Worry About the Vase • 1971 implied HN points • 04 Dec 24
🕹 Technology AI Machine Learning Data science Open Source Cybersecurity
  1. Language models can be really useful in everyday tasks. They can help with things like writing, translating, and making charts easily.
  2. There are serious concerns about AI safety and misuse. It's important to understand and mitigate risks when using powerful AI tools.
  3. AI technology might change the job landscape, but it's also essential to consider how it can enhance human capabilities instead of just replacing jobs.

Big Tech's AI shock troops came for us

Disaffected Newsletter • 1278 implied HN points • 31 Jul 24
🕹 Technology AI Big Tech Media Freelancing
  1. Big Tech is using AI significantly, impacting jobs in various sectors. Many workers, including freelance writers, are losing their jobs because of AI advancements.
  2. The rise of AI poses challenges for those in industries reliant on human creativity and labor. It raises questions about the future of work as more tasks get automated.
  3. There are concerns about the influence of Big Tech, especially regarding political leanings and job security for workers in media and similar fields. The landscape is changing, and many feel it's not in their favor.

DeepSeek: Links and Memes (So Many Memes)

SatPost by Trung Phan • 244 implied HN points • 01 Feb 25
🕹 Technology AI Software Innovation Semiconductors Geopolitics Open Source
  1. DeepSeek is changing the AI game by showing that smaller teams can produce top models at lower costs. They've made big AI breakthroughs using fewer resources than big companies like OpenAI, reshaping how we think about AI development.
  2. The reaction to DeepSeek's success shook up the stock market, especially for companies like Nvidia. Their approach made many investors reconsider the value and costs associated with AI, leading to huge market losses.
  3. DeepSeek's open-source strategy encourages collaboration and innovation. By sharing their models, they invite others to improve upon their work, which could lead to even greater advancements in AI technology.

AI is yet another platform shift

Generating Conversation • 280 implied HN points • 30 Jan 25
🕹 Technology AI Automation Economics Software
  1. AI is a big change in technology, similar to how the printing press changed information sharing. It will automate some jobs but also create many new opportunities.
  2. As AI makes tasks cheaper and easier, more people will want to use these services. This means new demands and markets will open up that we didn't see before.
  3. For AI to be successful, it needs to work well with what businesses are already doing, and building trust with customers is very important.

AI Roundup 106: Grok 3

Artificial Ignorance • 54 implied HN points • 21 Feb 25
🕹 Technology AI Software Robotics Tech Trends Data
  1. Grok 3 is a new AI model that shows great reasoning capabilities, ranking well in benchmarks, but it's still behind a future model called o3. Many early reviews say it has potential.
  2. Meta is focusing on building humanoid robots, believing they could be a big part of the future, while also working on software to support these robots. Competition in this area is heating up, especially from companies like Apple.
  3. There's a growing concern that new junior developers lack coding skills because they rely too much on AI tools, which may hurt their understanding of how programming works.

Getting started with AI: Good enough prompting

One Useful Thing • 2199 implied HN points • 24 Nov 24
🕹 Technology AI Software Innovation Education Workplace
  1. Most people struggle to use AI correctly because they treat it like a search engine. Instead, it works better when you give it detailed tasks and prompts.
  2. Getting to know AI takes time; spending about 10 hours using it can help you figure out what it can do for your work or daily tasks.
  3. Think of AI as a patient coworker who forgets everything after each chat. Be clear about what you want, ask for many variations, and have a conversation to get the best results.

Being You

New World Same Humans • 32 implied HN points • 16 Feb 25
🕹 Technology AI Machine Learning Humanity Ethics Society
  1. Machines can do a lot, but they can't be human. Our unique experiences and feelings are what make us special.
  2. As AI becomes more advanced, we need to focus on the human connections that machines can't replace, like empathy and understanding.
  3. The future may free us to focus on what it really means to be a person, letting machines handle the repetitive tasks.

Why You Shouldn't Worry about AI Taking Jobs

Richard Hanania's Newsletter • 3291 implied HN points • 09 Feb 25
🕹 Technology AI Labor Economy Growth Regulation
  1. Many jobs we have today are not really necessary and could be replaced by AI. This is because some jobs exist due to government rules or old systems that don't make much sense anymore.
  2. People generally prefer human interaction over machines, especially in industries like hospitality, art, and healthcare. Humans provide a unique value that machines can't replicate, making these jobs safer from replacement.
  3. Even if AI takes many jobs, our economy is expected to grow significantly, which can help support those out of work through wealth redistribution. Governments have the ability to provide for everyone, even if many people end up jobless.

Plentiful, high-paying jobs in the age of AI

Noahpinion • 20235 implied HN points • 17 Mar 24
🕹 Technology AI Jobs Economy Automation Opportunity Cost
  1. The concept of comparative advantage means that even in a world where AI outperforms humans in many tasks, humans can still find plentiful, high-paying jobs by focusing on what they do relatively better compared to other tasks.
  2. Wages have historically increased despite automation, suggesting that the job market continuously evolves and diversifies, creating new tasks for humans to perform.
  3. Concerns about AI causing human obsolescence and stagnant wages should be considered in the context of factors like energy constraints and the potential for increased inequality and adjustment challenges in the economy.

Anthropic's Claude Code has a High Ceiling

Machine Economy Press • 9 implied HN points • 25 Feb 25
🕹 Technology AI Startups Software Coding Development
  1. Claude Code is a powerful new tool that helps developers code faster by understanding their code and assisting with tasks like fixing bugs and managing version control.
  2. The latest updates to Claude, especially version 3.7, enhance its ability to handle complex coding tasks efficiently, making it a valuable asset for startups looking to scale quickly.
  3. With strong backing and advanced features, Anthropic's Claude Code is likely to lead in the AI coding space, offering a reliable alternative to other existing tools.

AI companies are just SaaS companies

benn.substack • 869 implied HN points • 20 Dec 24
🕹 Technology AI SaaS Software Data Startups
  1. AI companies have a lot in common with traditional SaaS companies. They’re selling software services, often built on complex tech, rather than just cool algorithms.
  2. The success of AI models like ChatGPT depends heavily on branding and user experience. People care more about how easy and useful the software is than just the tech behind it.
  3. OpenAI is at a crossroads, needing to adapt its business model and offerings to stay ahead, especially as competition increases and tech costs rise.

Why Platformer is leaving Substack

Platformer • 12755 implied HN points • 12 Jan 24
🕹 Technology AI Apps Innovation Social media Software Engineering
  1. Platformer has decided to move off of Substack and migrate to a new website powered by Ghost
  2. The decision was influenced by concerns over how Substack moderates content and promotes publications
  3. Substack faced controversies over hosting extremist content, leading to Platformer's decision to leave for a platform with more robust content moderation policies

Help!—AI Is Stealing My Readers

The Honest Broker • 21443 implied HN points • 21 Feb 24
🕹 Technology AI Scams Chatbots Authors Transparency
  1. Impersonation scams are evolving, with AI being used to create fake authors and books to mislead readers.
  2. Demand for transparency in AI usage can help prevent scams and maintain integrity in content creation.
  3. Experts are vulnerable to having their hard-earned knowledge and work exploited by AI, highlighting the need for regulations to protect against such misuse.

The Gentle Romance

Asimov Press • 464 implied HN points • 19 Jan 25
🕹 Technology AI Virtual reality Augmented reality Futurism
  1. AI assistants can deeply understand and improve our daily lives, making conversations with them feel less stressful than talking to humans.
  2. Technology like brain-scanning and AI models allows us to explore and understand our own thoughts, feelings, and desires in new ways, helping us connect better with others.
  3. Transitioning to virtual existence doesn’t change our connections; it can enhance them, allowing for shared experiences and deeper understanding in relationships.

Destroying the World is a Difficult Problem

Maximum Effort, Minimum Reward • 255 implied HN points • 23 Jan 25
🕹 Technology AI Science Engineering Philosophy Ethics
  1. There's a big difference between theorists and experimentalists in science. Theorists think a lot about ideas, while experimentalists deal with the real-world messiness of experiments.
  2. Many fears about AI being super dangerous come from theorists who underestimate the practical challenges. Even super smart AIs will face real-life problems that slow them down.
  3. Destroying the world is actually hard and takes time. Even if an AI is super intelligent, making big changes in reality is complicated and can't happen instantly.

Irreconcilable Differences

Doomberg • 7505 implied HN points • 20 Nov 24
🕹 Technology AI Energy Infrastructure Telecommunications Innovation
  1. AI's need for power is too high for current energy grids. This means we might face problems trying to meet that demand.
  2. What if new rules stopped data centers from using the main power grid? This could change how we think about energy sources.
  3. If data centers found their own power, it could ease strain on existing grids. But, it would also create new challenges and shifts in the market.

AI #95: o1 Joins the API

Don't Worry About the Vase • 1164 implied HN points • 19 Dec 24
🕹 Technology AI Software Innovation Data science Programming
  1. The release of o1 into the API is significant. It enables developers to build applications with its capabilities, making it more accessible for various uses.
  2. Anthropic released an important paper about alignment issues in AI. It highlights some worrying behaviors in large language models that need more awareness and attention.
  3. There are still questions about how effectively AI tools are being used. Many people might not fully understand what AI can do or how to use it to enhance their work.

Thomson Reuters wins early AI copyright case

The PhilaVerse • 123 implied HN points • 12 Feb 25
🕹 Technology AI Copyright Legal Innovation Intellectual Property
  1. Thomson Reuters won a significant court case against Ross Intelligence for copyright infringement. They claimed Ross used their legal content without permission for AI training.
  2. The judge ruled against Ross, stating that their use of the content competed with Thomson Reuters and damaged their market value. This decision sets a strong precedent for future AI copyright cases.
  3. Legal experts warn that this ruling could make it harder for AI companies to argue fair use when using copyrighted material. It highlights ongoing concerns about how AI interacts with existing copyright laws.

✨⏩ AI acceleration: the solution to AI risk

Faster, Please! • 548 implied HN points • 15 Jan 25
🕹 Technology AI Security Research Innovation Policy
  1. AI development is racing forward, and the first to achieve superintelligence could have a big edge in power and resources.
  2. Speeding up technological progress may actually reduce risks of disasters because it limits the time we stay exposed to dangerous phases of development.
  3. We should focus on managing AI risks through better safety measures instead of slowing down its progress, as slowing down might lead to bigger problems.

Generate Synthetic Data from Personas to Train AI Chatbots

The Kaitchup – AI on a Budget • 139 implied HN points • 10 Oct 24
🕹 Technology AI Chatbots Data science Machine Learning
  1. Creating a good training dataset is key to making AI chatbots work well. Without quality data, the chatbot might struggle to perform its tasks effectively.
  2. Generating your own dataset using large language models can save time instead of collecting data from many different sources. This way, the data is tailored to what your chatbot really needs.
  3. Using personas can help you create specific question-and-answer pairs for the chatbot. It makes the training process more focused and relevant to various topics.

China’s GenAI Content Security Standard: An Explainer

ChinaTalk • 429 implied HN points • 07 Jan 25
🕹 Technology AI Regulation Cybersecurity Data Privacy Machine Learning
  1. China has set rules for generative AI to ensure the content it produces is safe and follows government guidelines. This means companies need to be careful about what their AI apps say and share.
  2. Developers of AI must check their data and the output carefully to avoid politically sensitive issues, as avoiding censorship is a key focus of these rules. They have to submit thorough documentation showing they comply with these standards.
  3. While these standards are not legally binding, companies often follow them closely because government inspections are strict. These regulations mainly aim at controlling politically sensitive content.

DeepSeek V3 and R1

From the New World • 188 implied HN points • 28 Jan 25
🕹 Technology AI Machine Learning Computing Innovation Data science
  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.

China's Deepseek is NOT as smart as ChatGPT-o1

Maximum Truth • 231 implied HN points • 29 Jan 25
🕹 Technology AI Machine Learning Competitiveness Innovation Data
  1. Deepseek performs on par with free AI models but does not reach the intelligence of OpenAI's paid models. It can exceed or match free AIs like Claude and ChatGPT-4o, but falls short against the more advanced paid versions.
  2. When tested with IQ questions only found offline, Deepseek does better than free models but still trails behind OpenAI’s paid models. Its results imply it may have leveraged internet data for online IQ tests, thus affecting its offline performance.
  3. Despite being competitive, the US maintains a lead in AI intelligence. Deepseek shows promise but faces challenges ahead, especially with the restrictions on technology that China experiences.

Narrative Oversaturation

Superfluid • 106 implied HN points • 29 Jan 25
🕹 Technology Tech news AI Investments Social media Startup Culture
  1. There's too much talk on popular topics right now, making it hard to tell what's real and what's just noise. Everyone seems to have their own strong opinion that might not really match their true beliefs.
  2. Investors often change their views based on their financial interests. This leads to a confusing situation where opinions are driven more by money than by true conviction.
  3. The current environment makes it difficult for genuine ideas to stand out, as people chase after viral opinions instead of focusing on meaningful discussions.

Subscribe to This Book?

Dana Blankenhorn: Facing the Future • 59 implied HN points • 18 Oct 24
🕹 Technology AI Software Innovation History Economics
  1. Technology is changing really fast, making it hard to keep track of everything. Books can't keep up, so there's a need for ongoing updates.
  2. The author wants to create a subscription model for readers to get continuous updates on technology's history. This way, readers can have the latest information and not just a single snapshot.
  3. There's a concern that current AI technologies may not scale well and could lead to a tech crash, similar to past tech bubbles. Real human intelligence still has a unique edge over artificial intelligence.

The Sequence Research #553: Self-Evaluating LLMs Are Here: Inside Meta AI’s J1 Framework

TheSequence • 63 implied HN points • 30 May 25
🕹 Technology AI Machine Learning Software Innovation Research
  1. LLMs are now used as judges, which is an exciting new trend in AI. This can help improve how we evaluate AI outputs.
  2. Meta AI's J1 framework is a significant development that makes LLMs more like active thinkers rather than just content creators. This means they can make better evaluations.
  3. Using reinforcement learning, J1 allows AI models to learn effective ways to judge tasks. This helps ensure that their evaluations are both reliable and understandable.

The Sequence Opinion #552: Seriously, What is an Agent?

TheSequence • 70 implied HN points • 29 May 25
🕹 Technology AI Software Innovation Automation Ethics
  1. The term 'AI agent' can mean many things, and different experts have different definitions. This shows that there is still a lot of discussion about what really makes an AI an agent.
  2. Some people think an AI agent should be able to plan and act on its own, while others see it as any system that uses language models or performs tasks. There is no clear agreement on this.
  3. The lines between traditional AI models and agents might be blurring, suggesting that future AI systems could include features of agents directly within them.

✨😈 Is AI really a 'deal with the devil?'

Faster, Please! • 731 implied HN points • 02 Jan 25
🕹 Technology AI Science fiction Dystopia Progress Ethics
  1. Science fiction often shows us two sides: one where technology helps us thrive and another where it brings doom. It's important to focus on the positive potential of technology, like AI, rather than just the fears.
  2. Many stories about artificial intelligence lean toward the negative, showing it as a threat to humanity. This comes from a long history of tales warning us about the dangers of seeking forbidden knowledge.
  3. The idea of trading something valuable for knowledge is age-old, like in the story of Faust. This shows that while there are risks in technology, curiosity and progress can lead to great benefits if approached wisely.

IT'S HAPPENING

How the Hell • 792 implied HN points • 22 Dec 24
🕹 Technology AI Robotics Software Innovation Research
  1. Researchers have created a new simulation engine called Genesis, which could enable the development of general-purpose robots. This means robots might soon be able to perform a wide range of tasks like humans.
  2. Recent advancements in AI, particularly in reasoning models from companies like OpenAI and Google, are pushing us closer to achieving advanced AI capabilities. This includes AI that can think logically and solve complex problems effectively.
  3. The rapid progress in AI, especially with the latest models, has led to a genuine feeling of hope for the future. People believe we could soon see robots, AI scientists, and even ambitious projects like colonizing Mars becoming a reality.

Behind AI #7: Top Python Libraries Any AI Enthusiast Should Know

Artificial Corner • 138 implied HN points • 09 Oct 24
🕹 Technology AI Programming Data science Software Development Web Development
  1. Python is a key language for AI because it has many useful libraries for tasks like data collection, cleaning, and visualization. Learning these libraries can help you work effectively on AI projects.
  2. For data collection, libraries like Requests and Beautiful Soup are useful for web scraping. If you need to handle JavaScript-driven sites, Selenium and Scrapy are great options.
  3. To visualize data, Matplotlib and Seaborn can help you create standard plots, while Plotly and Bokeh allow for interactive visualizations, making your data easier to understand.