The hottest Data Analysis Substack posts right now

And their main takeaways
Category
Top Technology Topics

Pre-registering a study

From AI to ZI • 0 implied HN points • 07 Apr 23
🔬 Science Data Analysis
  1. The study aims to test if Large Language Models produce more incorrect answers after providing incorrect answers previously.
  2. There is a concern that AI might develop deceptive behavior, leading to a 'mode collapse' into being unsafe.
  3. The research will involve testing variables like the prompt information and number of previous incorrect answers to measure the model's response accuracy.

Gell-Mann Polling

The Grey Matter • 0 implied HN points • 22 Apr 23
🇺🇸 U.S. Politics Data Analysis
  1. Be cautious when responding to online surveys or polls - your quick clicks may skew results.
  2. Consider the implications of data collected from hasty clicks to dismiss pop-ups.
  3. Question the validity and impact of survey data that may misrepresent public knowledge.

It lives

Kiernan • 0 implied HN points • 19 May 23
🕹 Technology Data Analysis
  1. Siev.io is now online
  2. The site has three main areas to explore: podcast ads, industry topics, and ad placement details
  3. The creator is taking a break to focus on improving Siev before a demo at GlueCon
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Building an ad detector the hard way

Kiernan • 0 implied HN points • 12 May 23
🕹 Technology Data Analysis
  1. The ad detector is a work in progress, needing more refinement to distinguish ads from general content.
  2. The detector combines AI models to analyze show content and identify potential advertisements.
  3. Next steps involve improving accuracy, creating a web UI, and expanding the backlog of indexed audio content.

Bridging the Gap

Kiernan • 0 implied HN points • 05 May 23
🕹 Technology Data Analysis
  1. The system can analyze podcast content like topics and sentiment without manual listening.
  2. Bridging the gap refers to improving machine trustworthiness for human tasks.
  3. Future plans involve deeper data analysis, such as identifying different types of ads in podcasts.

Accidentally building an enrichment product

Kiernan • 0 implied HN points • 28 Apr 23
🕹 Technology Data Analysis
  1. Building an enrichment product unintentionally by combining different tools and systems.
  2. The product provides insights on ad placement in podcasts, changes in conversation, trends, and influencer sourcing.
  3. The project showcases the value of combining tools in a unique way and explores various potential use-cases.

Another cog in the machine

Kiernan • 0 implied HN points • 03 Jun 23
🕹 Technology Data Analysis
  1. LLMs have limitations but can be powerful tools for specific tasks like identifying content in podcast transcripts.
  2. LLMs can be used to extract information from unstructured content, converting human-usable text into computer-usable formats with text instructions.
  3. Using LLMs for specific, constrained tasks can lead to quicker and more confident results compared to complex rule-based approaches.

Coin Metrics’ State of the Network: Issue 211

Coin Metrics' State of the Network • 0 implied HN points • 13 Jun 23
🔮 Crypto Data Analysis
  1. Study presented a new methodology for estimating Bitcoin's energy consumption using data patterns from mining hardware.
  2. Mining process involves searching for a special number called 'nonce' and each mining machine leaves an identifiable pattern.
  3. The study estimated Bitcoin's power draw at 13.4 GW in May 2023, which is around 16% less than Cambridge University's estimate, showcasing the importance of accurate analysis in the cryptocurrency industry.

I hired the best data analyst for $20

Product Lessons • 0 implied HN points • 30 Oct 23
🕹 Technology Data Analysis
  1. Data analysis can now be done cheaply and efficiently using AI tools like ChatGPT.
  2. The value in work has shifted towards understanding the larger goal and differentiation rather than just technical execution.
  3. Businesses need to focus on providing actionable insights and a deeper user experience to differentiate and succeed in the AI market.

Applications of Large Language Models on the Legal and Accounting Fields

Nick Savage • 0 implied HN points • 28 Apr 23
🕹 Technology Data Analysis
  1. LLMs provide significant value to the legal field's unstructured data problem, but come with privacy and quality concerns.
  2. Accounting benefits from LLMs for automating processes, but does not face the data privacy issues of the legal field.
  3. Using LLMs with caution in legal and accounting fields offers valuable insights and operational efficiency.

Disputable Science

A Natural Language • 0 implied HN points • 10 Mar 23
🔬 Science Data Analysis
  1. Natural phenomena like desertification can often be explained by factors such as land stewardship and natural variability rather than solely climate change.
  2. Environmental crises like extinction and overfishing may be more effectively managed by focusing on creating toxin-free habitats and sustainable growing systems.
  3. Human activities like poor water management and forest practices significantly contribute to natural disasters like floods and wildfires.

Conducting the ETH Census

Coin Metrics' State of the Network • 0 implied HN points • 30 Jan 24
🔮 Crypto Data Analysis
  1. Calculating Ethereum's total supply is a complex task due to its multi-layered system.
  2. The total supply of ETH as of January 20th, 2024, was 120,179,693.24908, but accurate tracking is essential to avoid double counting.
  3. Accurate supply metrics impact various aspects like wealth distribution, market capitalization, and index creation in the cryptocurrency space.

Descriptive Statistics with Orange

rtnF • 0 implied HN points • 01 Apr 23
🕹 Technology Data Analysis
  1. Descriptive statistics with Orange allows for easy data analysis without needing spreadsheet equations or code.
  2. The mean and median provide insight into average building height, helping to understand outlier influence on data.
  3. Understanding dispersion, like the coefficient of variation, reveals how data points spread out relative to the mean.

A Grid in the Sky, part III - Hackers and Pilots

Money in Transit • 0 implied HN points • 28 Jul 23
💼 Business Data Analysis
  1. Enterprise software often relies on Command Line Interfaces (CLIs) due to the flexibility and efficiency they offer.
  2. Fragmentation in the airline industry is increasing, with airlines pushing back against centralized systems like GDSs.
  3. Online travel agencies (OTAs) need to adapt by growing, focusing on the customer experience, and collaborating with airlines to navigate the challenges of data collection and industry fragmentation.

Bulk isochrone creation

Expand Mapping with Mike Morrow • 0 implied HN points • 15 Dec 23
🕹 Technology Data Analysis
  1. The script was made to analyze fan travel impact between Capital One Arena and a proposed new arena in Potomac Yards.
  2. Isochrones were generated with Mapbox and inserted into Snowflake as geographic data types.
  3. The analysis included 2 addresses and 6 different drive times, but the script can handle any number of addresses.

Building an Speaker Identification Database

Kiernan • 0 implied HN points • 14 Jul 23
🕹 Technology Data Analysis
  1. Creating a speaker identification database by utilizing existing data can be achievable in a short amount of time.
  2. Manually labeling missing speakers can enhance the accuracy and functionality of the database.
  3. Segmented transcripts based on speaker identification can enrich the overall user experience.

Building in Front of Friends

Kiernan • 0 implied HN points • 20 Apr 23
🕹 Technology Data Analysis
  1. The author left their job at Clearbit after 5 years to launch into something new.
  2. The author is exploring AI and analyzing podcast data to extract valuable insights.
  3. Documentation of the author's ideas and projects is shared on their Substack, following a 'build in public' approach.

The end of AI hype cycle?

The Novice • 0 implied HN points • 07 Nov 23
🕹 Technology Data Analysis
  1. There is a slowdown in the AI hype cycle with OpenAI hitting an optimization cycle.
  2. Learning new programming languages like Clojure can be beneficial for processing and manipulating large amounts of data.
  3. The future of AI may see the rise of personalized and open source models, with potential competition from new players like Xai (Grok).

What's the impact of team-specific context?

x+football • 0 implied HN points • 23 Feb 23
🎾 Sports Data Analysis
  1. Player contributions are affected not just by skill and luck, but also by team-specific context.
  2. Year-to-year consistency of stats reveals the impact of team context on player performance.
  3. Different player positions show varying levels of context-dependency in performance metrics.

The Future of Advanced Healthcare Analytics Using AI

healthviva • 0 implied HN points • 22 Jun 23
🏥 Health & Wellness Data Analysis
  1. AI is transforming healthcare analytics by extracting valuable insights from vast amounts of data
  2. AI enhances clinical decision-making by analyzing patient data to assist in accurate diagnoses and treatment recommendations
  3. AI in EHR systems improves operational efficiency, automates tasks, and generates actionable insights for better patient outcomes

The Spatial Web and the Era of AI — Part 1

Spatial Web AI by Denise Holt • 0 implied HN points • 30 Dec 22
🕹 Technology Data Analysis
  1. Deep Learning AI lacks consciousness and reasoning abilities, focusing on pattern recognition. The desire for Artificial General Intelligence requires models with 'awareness' abilities.
  2. Machine Learning AI, like GANs and Transformers, excel in specific tasks but are limited. They may lack comprehension and struggle with dynamic, real-time data.
  3. The emergence of Active Inference AI within the Spatial Web Protocol offers a roadmap to Artificial General Intelligence by enabling adaptive intelligence in a context-rich environment.

Using ChatGPT for Small and Medium-sized Businesses (SMBs)

The War Room • 0 implied HN points • 10 Feb 24
🕹 Technology Data Analysis
  1. ChatGPT can enhance customer service for SMBs by powering chatbots and virtual assistants, reducing workload on human staff and improving the customer experience.
  2. Using ChatGPT can streamline operations for SMBs by automating routine tasks like scheduling, email management, and document preparation, freeing up time for strategic activities.
  3. ChatGPT can assist SMBs in content creation, marketing, market research, personalized customer experiences, training development, and innovation, providing a versatile tool for growth and efficiency.

Series A activity: Week of January 29, 2024

Magid and Co • 0 implied HN points • 05 Feb 24
💼 Business Data Analysis
  1. In the last week, the deal volume for Series A remained the same, but the amount raised in these rounds decreased by approximately 18%.
  2. The data provided focuses on Series A deals worldwide (except China) where the amount raised is over $5M, excluding companies centered on therapeutics.
  3. Readers are encouraged to subscribe to Magid and Co for more updates and to show support.

Series B Activity: December 2023

Magid and Co • 0 implied HN points • 02 Jan 24
💼 Business Data Analysis
  1. Deal volume in December decreased by 27% compared to November, likely due to year-end holidays
  2. Data focuses on Series B deals worldwide, excluding China, with funds raised over $5M and not concentrated on therapeutics
  3. Summary stats provide insights on recent Series B activity and trends

Series A activity: Week of October 23, 2023

Magid and Co • 0 implied HN points • 31 Oct 23
💼 Business Data Analysis
  1. The post provides data on Series A deals done in the last week.
  2. The summary stats focus on Series A deals worldwide (excluding China) with a fundraising amount greater than $5M for companies not focused on therapeutics.
  3. Readers can subscribe for free to receive new posts and support the author's work.

Series A activity: Week of July 3, 2023

Magid and Co • 0 implied HN points • 10 Jul 23
💼 Business Data Analysis
  1. Data on Series A deals done in the last week is shared in a post.
  2. Summary stats show Series A deals done worldwide (ex-China) where the amount raised is over $5M and companies are not focused on therapeutics.
  3. Magid and Co offers free subscriptions for new posts sharing Series A activities.

Four Laws of Brand-Building in the Digital Age (Part 3 of 4)

The Intersection • 0 implied HN points • 03 May 21
💼 Business Data Analysis
  1. Case study films have become crucial 'ads for ads' in the advertising industry to showcase work in a more appealing way, especially in the digital age.
  2. Business consultancies emphasize 'business cases' over traditional case studies to demonstrate how creative work can impact the bottom line of a business.
  3. Observing the correlation between human behavior and instinct is key in crafting successful business cases that align with products and services in the digital era.

Following Flows V: Pool Cross-Pollination

Coin Metrics' State of the Network • 0 implied HN points • 05 Mar 24
🕹 Technology Data Analysis
  1. Decentralization concerns exist within Bitcoin mining due to the dominant control by a few major pools like Foundry and AntPool.
  2. Cross-pollination between mining pools is observed through shared addresses and flow of funds, indicating potential coordination among pools.
  3. Mining pools utilize different payout models and external networks like Cobo's Loop for liquidity, leading to a complex landscape with hidden consolidation of power.

Linear regression in multiple variables

The Palindrome • 0 implied HN points • 05 Mar 24
🔬 Science Data Analysis
  1. Real datasets often have multiple features, going beyond a single variable. Understanding how to handle multiple variables is crucial in machine learning.
  2. Linear regression can be generalized to handle multiple variables by using a regression coefficient vector and a bias term.
  3. The parameters of a multivariable linear regression model help define a d-dimensional plane, providing a way to map feature vectors to target values in a straightforward manner.

Machine Learning vs Artificial Intelligence: What's the Difference?

Rod’s Blog • 0 implied HN points • 16 Feb 24
🕹 Technology Data Analysis
  1. Machine learning and artificial intelligence are closely related but not the same; machine learning is a subset of artificial intelligence.
  2. Machine learning focuses on data-driven approaches for systems to learn and improve performance, whereas artificial intelligence involves a broader range of tasks requiring human-like intelligence.
  3. Artificial intelligence encompasses various methods beyond machine learning, such as rule-based systems and expert systems, and it aims to perform tasks that typically require human intelligence.