The hottest Modeling Substack posts right now

And their main takeaways
Category
Top Climate & Environment Topics

No, Sora has not “learned physics”

Marcus on AI • 3589 implied HN points • 02 Mar 24
🕹 Technology AI Physics Modeling
  1. Sora is not a reliable source for understanding how the world works, as it focuses more on how things look visually.
  2. Sora's videos often depict objects behaving in ways that defy physics or biology, indicating a lack of understanding of physical entities.
  3. The inconsistencies in Sora's videos highlight the difference between image sequence prediction and actual physics, emphasizing that Sora is more about predicting images than modeling real-world objects.

OpenAI's moat

TechTalks • 334 implied HN points • 15 Jan 24
🕹 Technology AI Open Source Modeling Monetization Innovation
  1. OpenAI is building new protections to safeguard its generative AI business from open-source models
  2. OpenAI is reinforcing network effects around ChatGPT with features like GPT Store and user engagement strategies
  3. Reducing costs and preparing for future innovations like creating their own device are part of OpenAI's strategy to maintain competitiveness
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The Social Network (Part 2)

Logging the World • 279 implied HN points • 13 Apr 23
🔬 Science Networks Statistics Social media Modeling
  1. Real social networks exhibit more complex behaviors than simple mathematical models can capture.
  2. The structure of social media follower counts differs significantly from the Erdős–Rényi network model, with some users having exponentially more followers than others.
  3. Recent network models like the Barabási-Albert model better represent the dynamics of online social networks like Twitter, where heavy-tailed distributions of follower counts emerge.

Getting Started with LoRAs + Vodka Photorealism

followfox.ai’s Newsletter • 176 implied HN points • 15 Jun 23
🕹 Technology AI Training Modeling
  1. The post discusses getting started with LoRAs and creating a photorealistic LoRA for Vodka models.
  2. It includes steps like downloading and using a LoRA, training the first LoRA, and finally fine-tuning a custom LoRA for photorealistic results.
  3. The process involves using specific tools, datasets, and parameters to train LoRAs, and explores possibilities for creating high-quality, realistic images.

Novaxia vs Bigpharmia

Logging the World • 199 implied HN points • 04 Nov 22
🔬 Science Health Graphs Vaccines Modeling Data Analysis
  1. Understand the impact of vaccines on disease spread: Novaxia and Bigpharmia are examples of two scenarios showing how vaccines can affect the spread of a disease differently.
  2. Graphs help visualize data trends: Using different types of graphs can show how disease spread changes over time and the effectiveness of interventions like vaccines.
  3. Consider the importance of logarithmic scales: Logarithmic scales can provide a different perspective on data trends, allowing for better understanding of the impact of interventions like vaccines.

Why you should analyze the distribution of your Data [Math Mondays]

Technology Made Simple • 59 implied HN points • 14 Mar 23
🕹 Technology Data Analysis Math Software Engineering Modeling Statistics
  1. Analyzing the distribution of your data is crucial for accurate analysis results, helps in choosing the right statistical tests, identifying outliers, and confirming data collection systems.
  2. Common techniques to analyze data distribution include histograms, boxplots, quantile-quantile plots, descriptive statistics, and statistical tests like Shapiro-Wilk or Kolmogorov-Smirnov.
  3. Common mistakes in analyzing data distribution include ignoring or dropping outliers, using the wrong statistical test, and not visualizing data to identify patterns and trends.

Deep and obvious points in the gap between your thoughts and your pictures of thought

world spirit sock stack • 2 implied HN points • 16 Feb 24
📖 Philosophy Truth Thoughts Imagination Reality Modeling
  1. Some thoughts can feel profound or obvious, depending on your perspective and understanding. What may seem like a tired cliché to one person can be a significant insight to another.
  2. Our perception of the future is often based on our own imagined versions of it, rather than the actual future itself. Realizing this distinction can be eye-opening.
  3. Sometimes, what seems like common sense can actually challenge our existing thought patterns, leading to moments of revelation and shifts in perspective.

Will PostgreSQL switch to a Thread-based model ?

Engineering At Scale • 14 implied HN points • 24 Jun 23
🕹 Technology Database Architecture Modeling Software Development Performance
  1. PostgreSQL currently uses a process-based model for handling client connections and managing data.
  2. The process-based model offers advantages like fault isolation, security guarantees, and efficient resource management.
  3. Although there are advantages to the process-based model, the community is considering a switch to a thread-based model for PostgreSQL in the future.

Modeling p(doom) with TrojanGDP

Data Taboo • 5 implied HN points • 22 Sep 23
🕹 Technology AI Modeling Ethics GDP Automation
  1. There is a lack of mathematical models to assess AI existential risks like p(doom).
  2. The academic community has historically ignored existential risks from AI superintelligence.
  3. The proposed TrojanGDP model aims to estimate the lower bound of AI risk based on factors like GDP contribution and neural Trojan rediscovery.

Building the Digital Abacus, an Open-Source Mathematical Modeling App

Human Programming • 3 HN points • 24 Jul 23
🕹 Technology Math Programming UI/UX Open Source Modeling
  1. The Digital Abacus tool allows users to visually understand complex math equations by interactively manipulating values on a flowchart and seeing real-time updates in a plot.
  2. The tool uses a graph data structure called RelGraph to store values and constraints, allowing for easy representation of equations and composite operations.
  3. The system solves for dependent values by updating values iteratively in the graph until equilibrium is reached, showing the math solving process in real-time.

Study 1b: This One Weird Trick does NOT cause incorrectness cascades

From AI to ZI • 0 implied HN points • 20 Apr 23
🔬 Science Research Analysis Statistics Modeling Data Sharing
  1. Study found that changing question format from multiple choice to true/false did not significantly affect GPT-3.5's tendency to prefer factual answers
  2. The study showed mixed results for the hypotheses tested regarding the accuracy of answers based on question format and context
  3. Despite some limitations and deviations from the original plan, the study provided insights on how GPT-3.5 performs in providing factual answers