The hottest Data Substack posts right now

And their main takeaways
Category
Top Literature Topics

Introducing The Data Score Newsletter

The Data Score • 138 implied HN points • 05 Apr 23
🕹 Technology Data Technology Business Analytics Insights
  1. DataChorus LLC focuses on generating actionable insights for professionals and investors through data and technology.
  2. DataChorus aims to align data and technology with decision-making outcomes, explore different datasets and analytic frameworks for critical questions, and discuss scaling data practices and creating impactful data products.
  3. The Data Score Newsletter by Jason DeRise, CFA provides actionable ways to extract insights from data, explores breakthroughs in data and technology, and encourages open conversations to maximize success.

Why some data companies struggle to sell to the financial markets

The Data Score • 138 implied HN points • 18 Apr 23
💼 Business Data Finance Market Investment Sales
  1. In the financial market, selling data can be difficult if data companies don't align their products with the specific needs and capabilities of asset managers
  2. Understanding different types of asset managers and their unique requirements is crucial for data companies to succeed in selling to the financial markets
  3. Data companies must consider financial market outcomes and work backward from there to create data solutions that meet the demands of their clients

sqlmesh test

davidj.substack • 47 implied HN points • 12 Dec 24
🕹 Technology Software Data Engineering Testing Development
  1. Unit tests and data tests are different. Unit tests check if a function works right with set inputs, while data tests check if the data meets certain conditions.
  2. Running tests locally can save costs and speed things up. If you test your code on your own machine, you don’t have to pay for the cloud data warehouse until you’re ready.
  3. Creating external models in sqlmesh can be automated, making it easier to document source tables. You just run a command to generate the necessary files instead of doing it manually.

The Rise of "Web3 Growth"

DeFi Weekly • 137 implied HN points • 19 Apr 23
🕹 Technology Cryptocurrency Blockchain Marketing Data Industry
  1. Transition from technology being just functional to focusing on differentiation and market viability in the crypto industry
  2. Challenges in growing a crypto project include difficulties in measuring effectiveness, identifying real users, and understanding target audience
  3. Current growth strategies for crypto projects heavily rely on organic methods due to limitations in paid channels and data quality
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Breaking and Non-Breaking Changes

davidj.substack • 47 implied HN points • 11 Dec 24
🕹 Technology Software Development Data Engineering Analytics
  1. When making changes to data models, it's important to identify if they are breaking or non-breaking changes. Breaking changes affect downstream models, while non-breaking changes do not.
  2. SQLMesh automatically analyzes changes to understand their impact on other models. This helps developers avoid manual tracking and reduces the chances of errors.
  3. New features in SQLMesh will allow for more precise tracking of changes at the column level. This means less unnecessary work when something minor is modified.

Putting AI To Work

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 39 implied HN points • 11 Apr 24
🕹 Technology AI Automation Software Data Interfaces
  1. AI tools can help businesses automate tasks and improve efficiency without needing coding skills. This makes it easier for companies to integrate AI into their workflows.
  2. It's important to have a single platform that can manage different AI models together. This way, organizations can create more effective applications by combining the strengths of various models.
  3. Moving AI projects from ideas to reality requires careful planning and testing. Organizations need to ensure models are well-trained before using them in real-world applications.

🎧 Technically Optimistic Podcast: Season Two

Technically Optimistic • 19 implied HN points • 08 Jun 24
🎙 Podcasts Tech Data Privacy Social media Surveillance
  1. Season Two of Technically Optimistic Podcast dives into the topic of data privacy and control.
  2. Episodes discuss how our behavior online is used as a valuable resource, the impact of digital surveillance on reproductive rights, and the use of data in influencing voters.
  3. The podcast explores the concerns around online tracking of children, the evolving data economy in South Asia, and the implications of facial recognition technology in law enforcement.

The truth is out there

benn.substack • 511 implied HN points • 12 May 23
🕹 Technology AI Data Analysis Computers Software
  1. Computers can approach problems in ways humans can't, like Deep Blue's moves in chess.
  2. AI progress often comes from scaling computation by search and learning, not by mimicking human reasoning.
  3. Considering new approaches that leverage computation over human knowledge could help solve complex problems like pricing optimization.

"Good" questions

The Uncertainty Mindset (soon to become tbd) • 99 implied HN points • 29 Nov 23
🕹 Technology AI Data Innovation Ethics Software
  1. Asking good questions is important for getting useful answers. A good question is one that is foundational, meaning its answer can help answer many other questions.
  2. Foundationality is about understanding questions in a hierarchy. The more foundational a question is, the more it influences other questions.
  3. Thinking clearly and framing questions well can lead to breakthroughs. It may be hard work, but it's necessary to unlock important answers, especially in complex areas like AI.

Your friend the language model

DYNOMIGHT INTERNET NEWSLETTER • 437 implied HN points • 03 Mar 23
🕹 Technology AI Language Models Training Data Fine-tuning
  1. Large language models are trained using advanced techniques, powerful hardware, and huge datasets.
  2. These models can generate text by predicting likely words and are trained on internet data, books, and Wikipedia.
  3. Language models can be specialized through fine-tuning and prompt engineering for specific tasks like answering questions or generating code.

Diagram of an AI Image System

Cybernetic Forests • 119 implied HN points • 21 May 23
🕹 Technology AI Data Media Systems
  1. There is no definite definition of an AI image, as there are differing views on what AI and images truly are.
  2. Understanding different levels of AI image systems, such as data, interface, image, and media, is essential to navigating challenges within these systems.
  3. The intersection of AI images with human culture and media can perpetuate stereotypes and impact creators, leading to concerns about theft and ethical considerations.

A 3-Part Series: Thriving Across the Worlds of Finance, Business, Data, and Technology

The Data Score • 118 implied HN points • 09 Aug 23
💼 Business Finance Technology Data Decision-making Integration
  1. Problems in the fields of finance, business, data, and technology are becoming more interconnected and complex.
  2. There is a need to break down silos and create alignment among stakeholders to make more impactful decisions.
  3. Increasing overlap between business, data, and technology requires expertise from multiple domains to navigate high-risk environments.

So long Aeolus, and thanks for all the wind data

Europe in Space • 117 implied HN points • 02 May 23
🔬 Science Space Technology Data Environment Satellites
  1. Aeolus satellite mission ended and made significant contributions to improving weather forecasting with its pioneering technology
  2. Aeolus had a unique instrument to collect global wind data and its impact goes beyond just weather forecasts
  3. The mission had a lasting impact and economic benefits, leading to approval for a second Aeolus mission

2023 Trends To Watch: Data, Machine Learning, AI

Gradient Flow • 219 implied HN points • 12 Jan 23
🕹 Technology Data Machine Learning AI
  1. 2023 Trends to Watch: Data, Machine Learning, and AI are key areas to keep an eye on for advancements and innovations.
  2. Tech job market shifts: Despite challenges, demand for skilled professionals in MLOps and MLflow showcases opportunities for job seekers.
  3. Financial market impacts on data companies: Young data infrastructure companies faced stock value drops in 2022, with some like Klarna, Stripe, and Thoughtspot showing resilience amidst challenges.

Card Insights

Pine • 19 implied HN points • 18 Jun 24
🕹 Technology Software Data Analytics User Experience Improvements
  1. Pine now has cool analytics tools to help you understand your data better. You can break down and show your information in different ways.
  2. They've made some neat improvements, like showing summary insights and helping you create better connections between cards. This makes using the app more user-friendly.
  3. You can now open links in new tabs easily and get notifications for actions you take. These small updates improve the overall experience when using the app.

Top Questions ahead of Battlefin’s Discovery Day Miami

The Data Score • 59 implied HN points • 22 Jan 24
💰 Finance Investing AI Data Technology Economics
  1. The article highlights key questions for speakers at Battlefin's Discovery Day Miami, focusing on emerging technologies integration and data-driven insights in investment debates.
  2. The author tested ChatGPT for question generation, challenging its ability to create relevant and insightful questions for each panel session.
  3. The author compared their questions with ChatGPT's questions for each panel, reflecting on their differences and the strengths of human creativity against AI capabilities.

A New Fear Unlocked with Copilot+PCs

Sector 6 | The Newsletter of AIM • 19 implied HN points • 22 May 24
🕹 Technology AI Software Data Privacy Innovation
  1. Microsoft's new Recall feature allows easy data retrieval, but many employees are worried it could invade their privacy.
  2. The feature captures screenshots of user activities, which gets processed by an AI, making everything searchable.
  3. High-profile figures, like Elon Musk, are concerned about this feature, comparing it to something out of a dystopian show like Black Mirror.

How to save media and keep AI startups alive

Alex's Personal Blog • 98 implied HN points • 18 Mar 24
🕹 Technology AI Media Startups Data Regulation
  1. AI models may need to make deals with publishers to get access to training data, but this can create challenges for startups that can't afford upfront costs.
  2. There's a suggestion to shift payment for data access from upfront to back-end, where AI companies pay a portion of their revenue in return for used data.
  3. There are discussions around the importance of fair compensation for content used by AI models to ensure their continued development and success.

Ion Proton - FPGAs!

ASeq Newsletter • 7 implied HN points • 10 Dec 24
🕹 Technology Hardware Software Data Engineering Innovation
  1. The Ion Proton DNA sequencer uses specific hardware for DNA acquisition, which is important for its function.
  2. This hardware is expensive and involves custom designs, making it a significant cost for the sequencer.
  3. The upcoming summary will focus on the disassembly of the Ion Proton, which reveals more about its inner workings.

Can Minor Document Typos Comprehensively Disrupt RAG Retriever & Reader Components?

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 20 May 24
🕹 Technology AI NLP Data Algorithms Machine Learning
  1. RAG systems can struggle with small mistakes in documents, making them vulnerable to errors. Even tiny typos can disrupt how well these systems work.
  2. The study introduces a method called GARAG that uses a genetic algorithm to create tricky documents that can expose weaknesses in RAG systems. It's about testing how robust these systems really are.
  3. Experiments show that noisy documents in real-life databases can seriously hurt RAG performance. This highlights that even reliable retrievers can falter if the input data isn’t clean.

How to cultivate a high-signal AI feed

Democratizing Automation • 166 implied HN points • 28 Feb 24
🕹 Technology AI ML Data Research Communication
  1. Be intentional about your media diet in the ML space, curate and focus your energy to save time and avoid misleading content.
  2. When evaluating ML content, focus on model access, credibility, and demos; choosing between depth or breadth in your feed; and checking for reproducibility and verifiability.
  3. Ensure to socialize your information, build relationships in the community, and consider different sources and content types for a well-rounded perspective.

Log invalid values

CodeFaster • 36 implied HN points • 27 Nov 24
🕹 Technology Programming Software Development Coding Data
  1. Logging invalid values helps in debugging and understanding errors better. By including the actual value in the log, you can see what went wrong.
  2. Using clear and structured logging formats, like JSON, makes it easier to extract useful information later. This can save time and make troubleshooting smoother.
  3. Fast programming techniques and commands can enhance your workflow, letting you focus on coding efficiently rather than getting stuck on minor issues.

Reddit S-1 Breakdown

Tanay’s Newsletter • 164 implied HN points • 27 Feb 24
💼 Business Technology Finance Data AI IPO
  1. Reddit boasts a massive user base with 500M monthly active users but faces challenges in user engagement and monetization compared to platforms like Facebook and Snap.
  2. In terms of revenue, Reddit earns primarily from advertising, making $804M in 2023, but needs to address its high R&D spending to achieve profitability.
  3. Reddit holds valuable conversational data with 1 billion posts and 16 billion comments, making it attractive in the AI market; however, it must also navigate potential challenges where AI models could replace users asking questions on the platform.

Enterprise Prompt Engineering Practices

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 17 May 24
🕹 Technology AI NLP Research Engineering Data
  1. Users spend a good amount of time, around 43 minutes, editing prompts to get better results from language models. They often make small, careful changes instead of big rewrites.
  2. The main focus of edits is usually on the context of the prompts, such as improving examples and grounding information. This shows that context is crucial for getting good outputs.
  3. Many users try multiple changes at once and sometimes roll back their edits. This indicates that they might struggle to remember what worked well in the past or which changes had positive effects.

Pinterest improves their Closeup Recommendation System through foundational changes

MLOps Newsletter • 98 implied HN points • 07 Oct 23
🕹 Technology AI Data ML Models Libraries
  1. Pinterest improved their Closeup Recommendation System with foundational changes like hybrid data logging and sampling.
  2. Pinterest uses a model refreshing framework to keep their Closeup Recommendation model up-to-date and adaptable.
  3. Distilling step-by-step can help train smaller, more efficient, and interpretable language models like LLMs.

What the heck is "Media Access Control" or "MAC"????

Cybersect • 98 implied HN points • 24 Apr 23
🕹 Technology Networking Data
  1. MAC addresses are essential for networking and have a long history of evolution and usage.
  2. Understanding the concepts of Data Link Control and Network Layer is crucial for comprehending the development of networking protocols.
  3. MAC addresses need to be globally unique to ensure efficient communication in diverse network environments.