The hottest Data Substack posts right now

And their main takeaways
Category
Top Literature Topics

AI as electricity, AI as magic

New World Same Humans • 31 implied HN points • 02 Feb 25
🕹 Technology AI Innovation Robotics Data Software
  1. AI is becoming more like electricity, meaning it will be everywhere and very useful for things like robots and smart devices. This will make intelligence widespread and accessible.
  2. On the other hand, AI is also like magic, creating amazing content and automating complex tasks that used to be just for humans. This aspect makes AI feel special and creative.
  3. The real money won't be in creating AI but in using it to deliver great experiences. Companies with lots of user data and reach, like Meta and Google, will likely benefit the most from this trend.

The Shift to Account-Driven GTM

MKT1 Newsletter • 4 implied HN points • 12 Feb 25
💼 Business Marketing Sales Strategy Startups Data
  1. Companies need to switch to an account-driven approach for marketing and sales. This means focusing on specific accounts instead of just waiting for leads to come in.
  2. New tools now let marketers understand their entire audience better. They can gather more data on accounts, allowing for more tailored outreach and personalized content.
  3. This shift requires teamwork across departments like marketing, sales, and customer success. Everyone has to work together to effectively target and engage with chosen accounts.

"Cache me" if you can!

System Design Classroom • 659 implied HN points • 01 Jun 24
🕹 Technology Software Systems Data Engineering Architecture
  1. The type of caching strategy you choose depends on your read and write ratios. If you read a lot, caching is very helpful, but if you write often, you need a more complex approach.
  2. Data consistency is crucial for some applications. Using methods like Write-Through helps keep data in cache and databases aligned, while other methods, like Write-Behind, prioritize speed over immediate consistency.
  3. To see if your caching is effective, you should track metrics like how many times data is successfully retrieved from the cache versus not retrieved. This will help you understand how well your caching is working.

Weekly Top Picks #93

The Algorithmic Bridge • 148 implied HN points • 07 Jan 25
🕹 Technology AI Computing Data Robotics Video
  1. ChatGPT Pro is losing money despite its high subscription cost. This shows that even popular AI tools can face financial troubles.
  2. Nvidia has introduced an expensive new AI supercomputer for individuals. This highlights the growing demand for advanced AI technology in personal computing.
  3. More artists are embracing AI-generated art, sparking discussions about creativity and technology. This signals a shift in how art is produced and appreciated.

AI Companies Have Lost the Mandate of Heaven

The Algorithmic Bridge • 339 implied HN points • 04 Dec 24
🕹 Technology AI Software Data Computing Innovation
  1. AI companies are realizing that simply making models bigger isn't enough to improve performance. They need to innovate and find better algorithms rather than rely on just scaling up.
  2. Techniques to make AI models smaller, like quantization, are proving to have their own problems. These smaller models can lose accuracy, making them less reliable.
  3. Researchers have discovered limits to both increasing and decreasing the size of AI models. They now need to find new methods that work better while balancing cost and performance.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

Artificial Intelligence... is really just "Someone Else's Intelligence"

The Lunduke Journal of Technology • 10340 implied HN points • 05 May 23
🕹 Technology Artificial Intelligence Internet Software Data Ethics
  1. When we talk about 'The Cloud', we're really just talking about internet-connected computers.
  2. Artificial Intelligence, like ChatGPT and GitHub Copilot, is essentially copying and repackaging data created by humans.
  3. As AI systems evolve, there's a risk that original human work will be devalued and intelligence may decrease.

Sora Can’t Handle the Truth

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

Weekly Top Picks #92

The Algorithmic Bridge • 201 implied HN points • 16 Dec 24
🕹 Technology AI Software Startups Innovation Data
  1. AI that can think has a lot of value and potential applications. It's exciting to see how it can change various industries.
  2. Google made significant announcements this week, showcasing its advancements in AI technology. These updates could have a big impact on users.
  3. Many startups in the AI field are becoming bold in their claims and offerings. It's important to approach these developments with a critical eye.

The Black Spatula Project: Day Five

Am I Stronger Yet? • 125 implied HN points • 24 Dec 24
🕹 Technology AI Science Research Community Data
  1. A new community project is using AI to find errors in scientific papers. It's already made great progress in just a few days.
  2. Identifying and fixing errors in scientific research could help improve the quality of published papers. There are discussions on how best to implement this technology.
  3. The project faces challenges, like figuring out who will use the error-checking tool and how to manage costs associated with scanning many papers.

Has Google gone too woke? Why even the biggest models still struggle with guardrails

Marcus on AI • 2608 implied HN points • 21 Feb 24
🕹 Technology AI Ethics Data Bias Machine Learning
  1. Google's large models struggle with implementing proper guardrails, despite ongoing investments and cultural criticisms.
  2. Issues like presenting fictional characters as historical figures, lacking cultural and historical accuracy, persist with AI systems like Gemini.
  3. Current AI lacks the ability to understand and balance cultural sensitivity with historical accuracy, showing the need for more nuanced and intelligent systems in the future.

From Theory to Practice: Inductive Biases in Machine Learning

Mindful Modeler • 639 implied HN points • 23 Apr 24
🕹 Technology Machine Learning Algorithms Data Bias Modeling
  1. Different machine learning models exhibit varying behaviors when extrapolating features, influenced by their inductive biases.
  2. Inductive biases in machine learning influence the learning algorithm's direction, excluding certain functions or preferring specific forms.
  3. Understanding inductive biases can lead to more creative and data-friendly modeling practices in machine learning.

sqlmesh init -t dbt

davidj.substack • 179 implied HN points • 02 Dec 24
🕹 Technology Software Data Engineering Development Analytics
  1. SQLMesh recently announced that it is backwards compatible with dbt projects. This means teams can gradually switch to SQLMesh without having to do a big migration all at once.
  2. Using SQLMesh can help improve the clarity of data workflows and avoid broken DAGs during development. It offers features that make managing complex data stacks easier.
  3. Migrating to SQLMesh is possible even for those who aren't very tech-savvy. The process can be simple and done in an afternoon, making it accessible for teams to test and implement.

Weekly Dose of Optimism #125

Not Boring by Packy McCormick • 92 implied HN points • 20 Dec 24
🕹 Technology Energy AI Sustainability Data Innovation
  1. Commonwealth Fusion is making big strides toward clean energy with plans for the world's first commercial fusion power plant in Virginia, which could be operational by the early 2030s.
  2. Off-grid solar microgrids could greatly help power AI data centers quickly and affordably, making use of solar energy, especially in sunny regions like the U.S. Southwest.
  3. A new method called HORNET combines atomic force microscopy and AI to map RNA structures. This could improve our understanding of RNA and lead to better treatments for diseases.

sqlmesh janitor

davidj.substack • 119 implied HN points • 13 Dec 24
🕹 Technology Software Data Engineering Cloud Development
  1. Sqlmesh offers various command-line interface commands that help manage and maintain your data projects effectively. For example, the `clean` command helps fix any issues that might arise during execution.
  2. The new tool has unique features that improve development, like automatic data contract handling and optimized incremental models, making it easier to work with large datasets without unnecessary costs.
  3. Competition in the data transformation space is healthy. It pushes tools like dbt and sqlmesh to improve, ultimately benefiting users by providing better features and experiences.

10 AI stories that shaped 2024

Artificial Ignorance • 100 implied HN points • 27 Dec 24
🕹 Technology AI Innovation Data Regulation Infrastructure Trends
  1. AI is now a part of everyday life, making things easier and more efficient. It's moving from being a fun tool to a necessary part of our routines.
  2. Big companies are investing huge amounts of money in AI technology and infrastructure. They're building data centers and buying powerful computer chips to support AI's growth.
  3. New AI models are getting smarter and better at reasoning. These advancements allow AI to solve complex problems in ways we haven't seen before.

Human Intelligence, Inc.

Teaching computers how to talk • 136 implied HN points • 10 Dec 24
🕹 Technology AI Computing Data Innovation Big Tech
  1. AI might seem really smart, but it actually just takes a lot of human knowledge and packages it together. It uses data from people who created it, rather than being original itself.
  2. Even though AI can do impressive things, it's not actually intelligent in the way humans are. It often makes mistakes and doesn't understand its own actions.
  3. When we use AI tools, we should remember the hard work of many people behind the scenes who helped create the knowledge that built these technologies.

Import AI 370: 213 AI safety challenges; everything becomes a game; Tesla's big cluster

Import AI • 439 implied HN points • 29 Apr 24
🕹 Technology AI Data Security Research Systems
  1. Chinese researchers introduced MMT-Bench, a benchmark for assessing visual reasoning in language models with diverse tasks and scenarios.
  2. Researchers developed a system to turn 2D photos into 3D gameworlds, showing AI's capability to transform real-world imagery into interactive experiences.
  3. A consortium of researchers addressed 213 AI safety challenges across 18 areas, emphasizing the urgent need for solutions to ensure the reliability and safety of language models.

🌻 E45: PDL - New Language for Prompting

Musings on AI • 184 implied HN points • 05 Nov 24
🕹 Technology AI Software Development Innovation Data
  1. Prompt engineering is important because the way a prompt is worded can change the AI's response. Finding the right technique can improve the effectiveness of AI applications.
  2. The Prompt Declaration Language (PDL) is a new tool designed to simplify working with AI. It allows programmers to easily create applications like chatbots using a straightforward, data-oriented approach.
  3. Recent advancements in AI include new architectures that enhance performance in specific tasks, like financial analysis. These innovations are making AI applications more powerful and useful for real-world problems.

Weekly Top Picks #89

The Algorithmic Bridge • 159 implied HN points • 25 Nov 24
🕹 Technology AI Software Innovation Data Research
  1. The report discusses the current state of Generative AI in businesses for 2024, highlighting its growth and use.
  2. Large language models (LLMs) mainly focus on approximate retrieval rather than deep reasoning, which affects their performance.
  3. Recent studies indicate that people often prefer AI-generated art and poetry over works created by humans.

You can't build a moat with AI

The AI Frontier • 459 implied HN points • 11 Apr 24
🕹 Technology AI Data Software Engineering Startups
  1. You can't really set yourself apart with just AI models because they're becoming similar across different companies. What matters more is the unique data you use to feed those models.
  2. Even if your prompts seem special, they won't give you a long-term advantage. Competitors can quickly figure out how to improve their prompts, making them less valuable for differentiation.
  3. To succeed in building AI applications, focus on understanding and using your customers' data effectively. Good data engineering can really make a difference in how well your application performs.

GraphRAG: Design Patterns, Challenges, Recommendations

Gradient Flow • 259 implied HN points • 30 May 24
🕹 Technology AI Data Graphs Challenges
  1. GraphRAG enhances traditional RAG by incorporating knowledge graphs, improving content retrieval and answer generation for complex queries.
  2. GraphRAG offers various architectures like knowledge graph with semantic clustering, knowledge graph and vector database integration, and knowledge graph-based query augmentation for different applications.
  3. Building a comprehensive knowledge graph comes with challenges like domain understanding, data quality, and evolving data sources, requiring significant resources and expert knowledge.

Odds and Ends #43: An awesome drone trial in central London, legalised e-scooters at last, and National Data Library progress

Odds and Ends of History • 536 implied HN points • 18 Nov 24
🕹 Technology Innovation Transportation Data Drones
  1. There's a new drone trial happening in central London, showing cool innovations in technology. These drones could change how we think about delivery and transportation.
  2. E-scooters are now legal, making it easier for people to get around the city. This is a positive step towards eco-friendly transport options.
  3. Progress is being made on the National Data Library, which could improve access to important information for everyone. This can help with research and data sharing in various fields.

Open Thread 317

Astral Codex Ten • 2340 implied HN points • 26 Feb 24
🕹 Technology Social media AI Data
  1. Some users who were supposed to be unbanned were not truly unbanned, leading to a need for them to reach out to get it fixed.
  2. Substack acknowledges issues with page and comment loading speed, with plans to improve that in the future.
  3. GPT-6's training might require only 0.1% of the world's computers, according to Ben Todd's findings, a significant discrepancy from previous estimations.

Flows Are So Back

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 39 implied HN points • 22 Aug 24
🕹 Technology AI Data Development Software User Interface
  1. Graphs help show complicated data in a simple way. By using nodes and edges, you can easily see how everything connects.
  2. No-code tools let anyone, even those without programming skills, create complex workflows. This makes development quicker and more accessible for everyone.
  3. There's a growing need for tools that can organize and connect different AI flows. This would help everything work better together and solve problems more effectively.

A reduction in complexity is a reduction in humanity

Alberto Cairo's The Art of Insight • 279 implied HN points • 10 May 24
🎭️ Culture History Art Design Data Humanity
  1. Reducing complexity in data visualization can lead to oversimplifying important human stories. It's essential to remember that simplification can erase important details that affect people's lives.
  2. The history of data visualization is linked to darker aspects of society, like slavery and eugenics. Recognizing this helps us understand the impact of our tools and the stories we choose to tell.
  3. Visualization can be a powerful tool to reveal new insights when used correctly. By learning from the past, we can aim to avoid repeating mistakes and address inequalities.

TT Chapter: Fat-Tailed Distributions

Software Design: Tidy First? • 154 implied HN points • 04 Nov 24
🕹 Technology Software Design Development Data Engineering
  1. Fat-tailed distributions show that extreme events can happen more often than we expect. This is important for planning in various fields.
  2. When designing software, it's good to focus on creating simple models first. This can help make complex concepts easier to understand.
  3. Being an empirical designer means you rely on real-world data and observations to guide your design decisions. This approach can lead to better results.

LangGraph Agents By LangChain

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 39 implied HN points • 19 Aug 24
🕹 Technology AI Data Software Programming Engineering
  1. Graph-based representations are becoming popular in AI, making it easier to visualize application flows and manage data relationships. This helps in understanding complex connections between data points.
  2. There are two ways to create graph representations: one is using code to create a visual flow, and the other is using a graphical user interface (GUI) to build the flow directly. This dual approach caters to different needs and levels of user expertise.
  3. Graph data structures allow for both firm control over applications and the flexibility needed for agent-based systems. This is useful for tasks where interactions and decisions must adapt based on inputs or user approvals.

Stop begging for JSON

Artificial Ignorance • 88 implied HN points • 12 Dec 24
🕹 Technology AI Software Development Engineering Data
  1. Using AI tools has gotten better with structured outputs, which ensures that AI responses follow a specific format. This means developers can rely more on AI results.
  2. OpenAI introduced features like JSON mode and Structured Outputs, making it easier for developers to get the correct data structure from the AI. This reduces errors and makes integration smoother.
  3. Even with improvements, some challenges like inconsistent names and types in data still exist. Developers need to be aware and manage these issues when using AI.

Mistral Small 3, Open Music Foundation Models, Qwen2.5-Max and VL, FUZZ, Open-R1, Hailuo Director mode, Tülu 3 405B, Postman AI Agent Builder, Goose, LlamaReport, open-source operator, Codev, and more

AI Brews • 17 implied HN points • 31 Jan 25
🕹 Technology AI Software Innovation Digital Tools Data
  1. Mistral Small 3 is a new AI model that is fast and efficient, making it a strong competitor against larger models like Llama 3.3.
  2. Tülu 3 405B is an open-source model that follows an open training approach and has shown great performance on key benchmarks.
  3. There are new tools and apps for music generation and automation, making it easier to create songs and automate tasks through simple conversations.

Are AI Agentic Workflows the Future of Automation?

The API Changelog • 10 implied HN points • 30 Jan 25
🕹 Technology AI Automation APIs Workflows Data
  1. AI agentic workflows can adapt and make decisions like humans, allowing them to handle unexpected situations in real-time. This makes them more effective than traditional automation, which often breaks down with changes.
  2. Using APIs is essential for AI agentic workflows because they enable access to live data and help connect different services. This makes workflows smarter and more responsive to current events.
  3. Switching to agentic workflows can reduce the maintenance costs of automation and doesn't require deep technical knowledge, making it easier for more people to implement.

OpenAI Acquired Rockset

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 59 implied HN points • 31 Jul 24
🕹 Technology AI Data Analytics Infrastructure Applications
  1. OpenAI bought Rockset to make their data retrieval system better, which helps in using AI more effectively.
  2. The acquisition shows that LLMs are being seen more like a tool, and the focus is shifting to building useful applications using these technologies.
  3. Rockset's technology will help OpenAI work better with developers and make it easier to access and use real-time data for AI products.

It's time to build

benn.substack • 1278 implied HN points • 19 Jan 24
🕹 Technology Data AI Software Startups Analytics
  1. The modern data stack ecosystem is shifting as interest in generative AI takes over.
  2. The hype surrounding data tools can lead to rapid product development but also instability and distraction.
  3. Startups can find success by focusing on rebuilding existing ideas in a more deliberate and stable manner.

How AI startups are building moats - by paying for them

Enterprise AI Trends • 443 implied HN points • 19 Jul 24
💼 Business Startups Mergers Data Technology Finance
  1. AI startups need to spend a lot of money to build strong defenses, like buying data and companies, instead of just focusing on AI features.
  2. Having unique data is more valuable for AI startups than having great technology or user experience.
  3. Established companies have a big advantage because they already own important data. New AI startups may struggle to compete without something really special.

TAO - Meta's Scalable architecture powering world's largest social graph

Engineering At Scale • 120 implied HN points • 09 Nov 24
🕹 Technology Software Architecture Data Systems Engineering
  1. Meta created TAO to handle the huge amount of data and user interactions on its platform. This system helps generate personalized content for over 2 billion users very quickly.
  2. TAO uses a layered architecture that includes caching and data storage to improve performance. This design helps distribute the load and maintain fast responses even when many users are active.
  3. TAO prioritizes high availability over strict data consistency. This means it can sometimes show slightly out-of-date information, but it still works well for users, especially during busy times.

Issue #7 - The Business Strategy, Where The Data Journey Starts

The Data Ecosystem • 179 implied HN points • 26 May 24
💼 Business Strategy Data Leadership Analytics Performance
  1. A business strategy is the game plan for a company to reach its goals. It involves having a clear vision, mission, and set of goals to guide the organization.
  2. Good business strategies have defined components that everyone in the company knows. This helps avoid confusion and keeps everyone focused on the same objectives.
  3. Data plays a crucial role in shaping modern business strategies. Companies need to integrate data and analytics into their plans to make informed decisions and stay competitive.

Race, Homicide, & Data

Peter Boghossian • 1041 implied HN points • 02 May 23
🇺🇸 U.S. Politics Race Data
  1. The news media and public figures can create inaccurate narratives that influence perceptions.
  2. Educating people about accurate data is crucial to addressing social issues like crime and policing.
  3. Examining and fact-checking data can reveal insights that challenge popular movements and ideologies.

OpenAI Enhanced Their API With Robust Structured Output Capabilities

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 39 implied HN points • 12 Aug 24
🕹 Technology AI API Data Development NLP
  1. OpenAI has improved its API to ensure that outputs always match a set JSON format. This helps developers know exactly what kind of data they will get back.
  2. The previous method of generating JSON outputs was inconsistent, making it hard to use in real-world applications. Now, there's a more reliable way to create structured outputs.
  3. Developers can now use features like Function Calling and a new response format to make their apps interact better with AI, ensuring clearer communication between systems.