The hottest Data Substack posts right now

And their main takeaways
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Top Literature Topics

IT-Harvest Launches AI Assistants for Industry Research

The Security Industry • 8 implied HN points • 15 Jan 25
🕹 Technology Data
  1. IT-Harvest has launched AI assistants called HarvestIQ.ai, which help users research companies and products in the cybersecurity field. These assistants are designed to make finding information easier and faster.
  2. The HarvestIQ Assistants feature chat interfaces that allow users to ask questions about cybersecurity vendors and products, providing detailed responses and insights. This is especially helpful for professionals needing quick access to relevant data during discussions.
  3. The tools are cost-effective compared to traditional research methods and integrate advanced technologies to assist users in selecting the best cybersecurity solutions for their needs.

On the Behavior of OpenAPI's oneOf

The API Changelog • 3 implied HN points • 04 Jul 25
🕹 Technology Data
  1. OpenAPI's `oneOf` feature is useful for defining complex data types in an API. It allows data to match one schema from a list, but not more than one at the same time.
  2. To avoid confusion when validating data against multiple schemas, make sure the schemas are distinct. Adding specific properties can help ensure data validates correctly against the intended schema.
  3. Using a `discriminator` property can make validation simpler by clearly indicating which schema to use. This helps the API understand the data type better and reduces errors.

Are Only 20% of Devs Happy? | Stack Overflow’s Erin Yepis

Dev Interrupted • 9 implied HN points • 19 Nov 24
🕹 Technology Data
  1. Only about 20% of developers say they are happy in their jobs. This suggests many people in the field are feeling dissatisfied.
  2. Factors like low pay, workplace culture, and issues with technical debt are major reasons behind this unhappiness. It's important to look at these issues to help improve developer satisfaction.
  3. A new project called Flock aims to address problems with the popular Flutter toolkit. The creators want to make a community-driven platform that fixes bugs and speeds up development.
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About Cybersyn, the Company

Magis • 36 implied HN points • 13 Apr 23
💼 Business Data
  1. Cybersyn, a startup, recently raised a Series A funding round.
  2. The company focuses on data, finance, economics, and DaaS.
  3. Common questions about Cybersyn include what the company does, the data it uses, and who is involved.

API Preview and Signal Stats

Dataplane.org Newsletter • 19 implied HN points • 07 Mar 22
🕹 Technology Data
  1. The API Preview allows users to search data with a subset of current data and provides documentation for various queries and returns.
  2. The Signal Statistics page offers graphical insight into daily event summaries, aiding both the organization and the community.
  3. The commentary on UA and RU signals highlights the organization's operational status in these regions amidst recent events, emphasizing the importance of monitoring and preparedness.

RAG RAG on the Wall.

potentialmind • 1 HN point • 17 May 24
🕹 Technology Data
  1. Building successful AI apps involves utilizing AI systems with additional functionalities like retrieval capabilities to support RAG.
  2. To enhance RAG, the 'Small-to-Big' pattern is used, decoupling text chunks for retrieval and synthesis, leading to more precise results.
  3. Two basic patterns for implementing RAG are 'Large Chunks' and 'Small Chunks', each with trade-offs in synthesis quality and recall specificity.

Introducing The Data Exchange

Gradient Flow • 79 implied HN points • 14 Nov 19
🎙 Podcasts Data
  1. The Data Exchange is a new independent podcast focusing on data, machine learning, and AI
  2. The podcast aims to build a community to help people make better decisions
  3. To support The Data Exchange, listeners are encouraged to subscribe and share with friends

An analysis of Berkson's Paradox

Of Aurochs and Angels • 1 HN point • 14 May 24
🔬 Science Data
  1. In statistics, a collider can affect the relationship between variables, leading to false impressions. For example, controlling for a collider can change the true effect of one variable on another.
  2. Berkson's Paradox shows how relationships between variables can change when selecting samples based on certain traits, leading to counterintuitive results.
  3. The impact of weighting test scores in selection processes can alter the relationship between test scores and outcomes. Higher weighting can sometimes lead to negative correlations, despite the underlying positive relationship.

The Connected

coreygarvey • 59 implied HN points • 01 Jul 20
🏥 Health & Wellness Data
  1. Healthcare will be greatly impacted by devices and data in the future.
  2. The upcoming advancements will reshape our understanding of our bodies.
  3. These changes will influence various aspects of life, from healthcare to parenting.

Comments to the White House on Federal Data

The Good Science Project • 26 implied HN points • 13 Sep 23
🇺🇸 U.S. Politics Data
  1. The White House should make federal data more accessible in a machine-readable format.
  2. NIH and NSF need to be more open in allowing external researchers access to critical data on agency operations.
  3. There is a need to update scientific funding agencies like NIH and NSF to enable external researchers to access data more easily.

Clouded Judgement 1.3.25 - Domain Specific Models

Clouded Judgement • 7 implied HN points • 03 Jan 25
🕹 Technology Data
  1. In 2025, we will see a lot of special AI models that focus on specific areas of knowledge, like health or engineering. These models will learn from specialized and private data to perform better than general AI models.
  2. These domain-specific models will help industries that need deep understanding and accuracy, solving complex problems that generalized AI can struggle with. This means they can deliver the right answers when it matters most.
  3. As businesses create their own tailored AI models, the enterprise AI market will grow significantly. This will change how companies operate and improve efficiency in many fields.

Remix is better than GraphQL

Andrew's Substack • 13 HN points • 30 Jun 24
🕹 Technology Data
  1. Remix and GraphQL serve different purposes - Remix is for full-stack app development while GraphQL is for building APIs
  2. Both Remix and GraphQL offer benefits like type-safety and efficient data fetching
  3. Remix loaders provide specific data loading endpoints, offering straightforward authorization and reducing opportunities for bad inputs

How Programming Intelligence Changes the Role of AI

The API Changelog • 3 implied HN points • 11 Jun 25
🕹 Technology Data
  1. AI systems, especially large language models, are often unpredictable and work like black boxes, which can be a big problem in important fields like medicine or finance.
  2. To make AI more controllable, we can set limits on what it can do and ensure it asks for our approval before taking actions, giving us more confidence in its decisions.
  3. Making AI systems programmable means we understand what they do better, helping us regain control and turn AI into a tool that supports our goals instead of taking charge.

The Value of Stability in Scientific Funding, and Why We Need Better Data

The Good Science Project • 18 implied HN points • 17 Feb 24
🔬 Science Data
  1. Scientific funding instability negatively impacts researchers' ability to plan and conduct research effectively, leading to swings in funding and unnecessary time spent on grant proposals.
  2. Improved data tracking is crucial to understanding the impact of funding gaps on researchers' employment outcomes, highlighting the need for long-term empirical studies in science policy.
  3. Addressing funding stability issues and utilizing detailed longitudinal data can help prevent obstacles in scientific progress and support the longevity of researchers' careers.

Ion Proton - FPGAs!

ASeq Newsletter • 7 implied HN points • 10 Dec 24
🕹 Technology Data
  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.

Trends to Watch in 2021 and Best Books of 2020

Gradient Flow • 39 implied HN points • 31 Dec 20
🕹 Technology Data
  1. The post highlights key AI and data trends for 2021, with a focus on managing data-focused teams and upcoming trends to watch out for.
  2. A selection of recommended books from 2020 covers a wide range of topics, from data analytics and machine learning to history, biography, security, and big tech.
  3. The author provides a glimpse into personal experiences in 2019, like visiting the longest zipline in the world, and sends well wishes for 2021.

Don't Read, Listen

Magis • 27 implied HN points • 15 May 23
💼 Business Data
  1. The post discusses an interview on the Alternative Data Podcast about Cybersyn and Coatue.
  2. The interview reflects on topics like culture at Cybersyn, alternative data adoption in asset classes, and opportunities in the public sector.
  3. The post suggests subscribing to the author's writing to stay informed.

Lies and Gaslighting Over the Military Health Data - Calling Out Steve Kirsch and Robert Malone

Rounding the Earth Newsletter • 16 implied HN points • 26 Jan 24
🏥 Health Politics Data
  1. Steve Kirsch may have lied or been incompetent about the DMED database, causing gaslighting and isolation.
  2. Robert Malone also appeared to hallucinate about the DMED data, leading to blocked communication and potential gaslighting.
  3. A comprehensive report on the DMED data for Congress was not completed due to external interference, causing stress and exhaustion.

Growth Is Up. So What's Up With the Economy?

Gideon's Substack • 19 implied HN points • 26 Oct 23
💼 Business Data
  1. The American economy is performing exceptionally well post-pandemic, surpassing other developed countries.
  2. There is a notable disconnect between people's perceptions of the economy and the actual economic data, leading to various theories and concerns.
  3. Factors such as the pandemic hangover, inflation, wage discrepancies, and fiscal uncertainties contribute to the complex economic landscape, influencing consumer sentiment and political outcomes.

Clouded Judgement 10.18.24

Clouded Judgement • 7 implied HN points • 18 Oct 24
🕹 Technology Data
  1. Enterprise software has always relied on systems that store data, but the real value comes from how people use that data in workflows. It's not just about the data, but how it's managed and processed.
  2. AI is set to change this by taking over the data entry tasks that humans typically do. This means less focus on user interfaces and more on how efficiently AI can handle and process data automatically.
  3. With this shift to AI-driven systems, we will see new ways of building applications that prioritize smart databases. This could make traditional systems less important and create a need for new tools to manage complex workflows.

My Story with Snowflake

Magis • 18 implied HN points • 04 Oct 23
🎙 Podcasts Data
  1. The user participated in Snowflake's Data Cloud podcast.
  2. They discussed topics like Snowflake, Coatue, and Cybersyn.
  3. The conversation also covered AI-related subjects.

The Shift to Account-Driven GTM

MKT1 Newsletter • 4 implied HN points • 12 Feb 25
💼 Business 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.

How do you compete with the everything company?

Entry Level Investing • 16 implied HN points • 09 Nov 23
🕹 Technology Data
  1. OpenAI is a strong competitor in AI, but they are not infallible across all business lines.
  2. To compete with OpenAI, focus on deep vertical specialization, proprietary data moats, and cloud agnostic solutions.
  3. Consider prioritizing enterprise needs, leveraging open source communities, and recognizing the challenges of being an 'everything company.'

The End of Software, Long Live Software

Chaos Engineering • 5 implied HN points • 04 Dec 24
🕹 Technology Data
  1. AI Agents are changing how we think about software. They are smart programs that can do tasks for us, but we still need humans to help out to make sure everything runs smoothly.
  2. Using AI to create software can make things cheaper, but it also makes the software more complex. As we rely on AI, we need to ensure we can trust it to work reliably.
  3. Data is super important for AI to work well. We need to collect good quality data to train these AI Agents so they can do their jobs effectively and produce accurate results.

Intelligence in the World

New World Same Humans • 15 implied HN points • 12 Nov 23
🕹 Technology Data
  1. Intelligence is becoming infrastructural, like a new form of energy, powering the world in the Exponential Age.
  2. In the Exponential Age, intelligence is becoming superabundant, available everywhere, like never before in history.
  3. Intelligence in the new world is seen as a new form of energy that does useful work in the digital-physical field, driving a variety of technologies.

Projects of fake coherence

Internal exile • 21 implied HN points • 19 May 23
🕹 Technology Data
  1. Generative AI is used to deskill workers and remove their leverage over their bosses.
  2. Automation is driven by the demands of capitalism to deskill and discipline workers.
  3. Capital functions as an 'artificial intelligence' that emerges from economic power concentration.

Clouded Judgement 1.24.25 - The Year of Enterprise AI

Clouded Judgement • 4 implied HN points • 24 Jan 25
🕹 Technology Data
  1. AI in businesses faces a big challenge called the 'last mile' problem, which means it struggles to give accurate answers for specific business needs. This is especially important when customers are involved.
  2. To make AI better for businesses, combining general AI models with specific company data helps create more reliable results. This approach can improve things like compliance checks and sales forecasts.
  3. The speed of improvement in AI technology is impressive, and future models might overcome current limitations. This could allow businesses to answer a wider range of questions more accurately.

When few do great harm

Patterns in Humanity • 3 HN points • 23 Apr 23
🇺🇸 U.S. Politics Data
  1. A small number of people often commit a large fraction of crimes, known as power laws in criminal behavior.
  2. Most crimes are committed by repeat offenders, leading to more victims than offenders.
  3. The impact of crime extends beyond direct victims, with financial costs and societal harm being significant.

The Belamy | OpenAI Triton, SingleStore & Stack Overflow

Sector 6 | The Newsletter of AIM • 19 implied HN points • 08 Aug 21
🕹 Technology Data
  1. OpenAI has released a new programming language called Triton that allows users without CUDA experience to write GPU code effectively. This makes it easier for more people to work with high-performance computing.
  2. Triton offers an alternative to existing technologies like NVIDIA CUDA, which has been the standard for GPU programming. It's important to understand the differences to choose the right tool for specific needs.
  3. The advancements in programming languages like Triton show how AI and technology are evolving, making powerful tools more accessible to developers and researchers. This opens up new possibilities for innovation.

20241124

Curious futures (KGhosh) • 4 implied HN points • 24 Nov 24
🕹 Technology Data
  1. Leonardo da Vinci was very curious and used his knowledge from different fields to understand the world better. He wasn't just a jack-of-all-trades but saw how art and science worked together.
  2. The development of AI is changing how we interact with technology. There are concerns about deep fakes and the need for tools that can verify if something is real or made by AI.
  3. Understanding the risks in our world, such as those identified by the EU, is important for preparing for the future. These risks can affect everyone, so awareness is key.

How to train your GPT 🤖

Year 2049 • 11 implied HN points • 17 Nov 23
🕹 Technology Data
  1. OpenAI introduced custom GPTs, allowing users to publish and monetize their own versions on the ChatGPT platform.
  2. When building a custom GPT, focus on giving it a clear action-based identity to avoid it drifting from its purpose.
  3. Simplify the knowledge transfer process, write helpful conversation starters, and gracefully handle questions your GPT may not have answers to.