The hottest Data Substack posts right now

And their main takeaways
Category
Top Literature Topics
Expand Mapping with Mike Morrow 0 implied HN points 13 Nov 24
  1. Recommendation engines can work in two main ways: using features like genre or through user behavior to suggest content. This means they can recommend similar items based on what you liked or what others liked when they liked the same thing.
  2. A good way to find new movies is by looking at the work of the same director or producer. This can help you discover different films outside your usual tastes.
  3. Using a network diagram can help visualize connections between different movies or content. This manual method can feel more personal and help avoid getting stuck in a 'filter bubble' of recommendations.
Database Engineering by Sort 0 implied HN points 02 Dec 24
  1. There's a new organization dashboard that helps track important issues and change requests effectively. It makes it easier to see what needs action right away.
  2. The Sort website has been updated to showcase how their workflows operate. This should help users understand the product better.
  3. Several new blog posts detail various functionalities of Sort, including APIs and integrations, providing users with useful insights and tools.
Nano Thoughts 0 implied HN points 11 Dec 24
  1. Building a strong foundation before specialized learning is important. Just like in karate, having basic skills helps in mastering advanced techniques later.
  2. Large datasets without labels are crucial for training AI in systems biology. These datasets can help uncover hidden patterns in biology, similar to how language models learn from vast amounts of text.
  3. Advanced AI can make healthcare more personalized and efficient. With better AI models, diagnoses may be quicker, and treatments could be more suited to each person's needs.
Alex's Personal Blog 0 implied HN points 20 Dec 24
  1. OpenAI's new model, o3, shows significant improvements in programming tasks and exam scores. It indicates that AI is advancing fast and can tackle challenging problems.
  2. Inflation rates are slightly lower than expected, which might affect consumer spending and interest rates. However, the markets seem to recover despite this uncertainty.
  3. Elon Musk is building ties with various right-wing political groups in Europe. His support for these parties suggests a trend toward anti-immigration and nationalistic policies.
Database Engineering by Sort 0 implied HN points 06 Jan 25
  1. The new Data Explorer is designed to be user-friendly and looks similar to a spreadsheet, making it easier to manage data. You can filter rows and propose changes quickly with just a few clicks.
  2. A feature called 'Describe Changes' allows users to detail updates to data in simple language, like changing a customer’s address. The improvements also make it easier to view these described changes.
  3. The founders encourage user feedback and suggestions for future updates, highlighting their commitment to improving the platform.
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Guide to AI 0 implied HN points 29 Dec 24
  1. Data acquisition is crucial for AI startups. It's important to know different methods like using synthetic data and scraping from various sources.
  2. Strong storytelling helps tech companies succeed. Good story-telling is needed to explain technology and attract support.
  3. AI's energy needs are growing, making nuclear energy a potential solution. However, the speed of building new infrastructure to support it must improve.
Database Engineering by Sort 0 implied HN points 21 Jan 25
  1. Sort is a database tool that helps operations teams manage their data better. It keeps everyone on the same page with up-to-date information.
  2. With Sort, teams can quickly track changes and resolve issues together, reducing confusion and improving teamwork.
  3. Using Sort can lead to faster decisions, fewer mistakes, and overall better efficiency in operations management.
My Makerspace 0 implied HN points 02 Feb 25
  1. Using PostgreSQL 10 from amazon-linux-extras can save you a lot of hassle. It's simple and works well in AWS Lambda.
  2. Newer versions of PostgreSQL can cause issues, so it's often better to stick with stable, older versions.
  3. Make sure to set up your VPC correctly to connect to Aurora. Also, always use environment variables for your database credentials.
Expand Mapping with Mike Morrow 0 implied HN points 12 Feb 25
  1. Many people are trying to use LLMs, but often they aren't sure what problems to solve. It's important to find the right match between the tool and the issue.
  2. LLMs can be really useful for tasks like translation, helping people find information, and working with data. These are some of the best ways to use them.
  3. Successful LLM applications will focus on these core uses. It's all about using the technology for what it does best.
Phoenix Substack 0 implied HN points 25 Feb 25
  1. FortuneGPT mixes tarot reading with AI to predict your future based on your data and habits. It's like having a digital fortune teller who uses real information to give you insights.
  2. The app learns from each reading, becoming better at understanding your worries over time. It can adjust its advice based on your mood and past decisions.
  3. FortuneGPT offers a free version and multiple paid plans that upsell deeper insights and predictions. It's designed to keep users engaged and curious, almost like a subscription service for mystical insights.
More Than Moore 0 implied HN points 24 Feb 25
  1. AMD expects their AI business to grow to over $10 billion a year. This shows they are really focusing on artificial intelligence as a big part of their future.
  2. They are planning to create an AI Developer Cloud, which will help developers access tools for building AI applications. This could make it easier for more people to work on AI projects.
  3. AMD believes that training AI models will be the main focus in 2025. This means they are shifting gears from just inference tasks to actually training the models needed for AI.
philsiarri 0 implied HN points 15 Jun 25
  1. Libraries are releasing old books in the public domain to help train AI models. This includes tons of books from many languages, going back to the 15th century.
  2. Using these public texts helps avoid legal problems tech companies face when they use copyrighted material. It also can improve the quality and reliability of AI.
  3. The dataset from Harvard is available for anyone to use on the Hugging Face platform. This gives researchers and developers a valuable resource for their AI projects.