The hottest Modeling Substack posts right now

And their main takeaways
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2024 Interconnects year in review

Democratizing Automation • 229 implied HN points • 31 Dec 24
🕹 Technology Modeling
  1. In 2024, AI continued to be the hottest topic, with major changes expected from OpenAI's new model. This shift will affect how AI is developed and used in the future.
  2. Writing regularly helped to clarify key AI ideas and track their importance. The focus areas included reinforcement learning, open-source AI, and new model releases.
  3. The landscape of open-source AI is changing, with fewer players and increased restrictions, which could impact its growth and collaboration opportunities.

From bare-bones to holistic machine learning

Mindful Modeler • 159 implied HN points • 08 Aug 23
🕹 Technology Modeling
  1. Machine learning can range from simple, bare-bones tasks to more complex, holistic approaches.
  2. In bare-bones machine learning, the modeling choices are defined, making it about the model's performance and tuning.
  3. Holistic machine learning involves designing the model to connect with the larger context, considering factors like uncertainty, interpretability, and shifts in distribution.

Week #3: Conformal Prediction For Regression

Mindful Modeler • 279 implied HN points • 03 Jan 23
🔬 Science Modeling
  1. In regression, conformal prediction can turn point predictions into prediction intervals with guarantees of future observation coverage.
  2. Starting from point predictions or non-conformal intervals from quantile regression are two common approaches to creating prediction intervals.
  3. Conformalized mean regression and conformalized quantile regression are two techniques to generate prediction intervals in regression models.

Moving Past RLHF: In 2025 We Will Transition from Preference Tuning to Reward Optimization in Foundation Models

TheSequence • 189 implied HN points • 29 Dec 24
🕹 Technology Modeling
  1. Artificial intelligence is moving from preference tuning to reward optimization for better alignment with human values. This change aims to improve how models respond to our needs.
  2. Preference tuning has its limits because it can't capture all the complexities of human intentions. Researchers are exploring new reward models to address these limitations.
  3. Recent models like GPT-o3 and Tülu 3 showcase this evolution, showing how AI can become more effective and nuanced in understanding and generating language.

Novaxia vs Bigpharmia

Logging the World • 199 implied HN points • 04 Nov 22
🔬 Science Modeling
  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.
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Understanding Different Uncertainty Mindsets

Mindful Modeler • 179 implied HN points • 24 Jan 23
🔬 Science Modeling
  1. Understanding the fundamental difference between Bayesian and frequentist interpretations of probability is crucial for grasping uncertainty quantification techniques.
  2. Conformal prediction offers prediction regions with a frequentist interpretation, similar to confidence intervals in linear regression models.
  3. Conformal prediction shares similarities with the evaluation requirements and mindset of supervised machine learning, emphasizing the importance of separate calibration and ground truth data.

Preventing model exfiltration with upload limits

Redwood Research blog • 19 implied HN points • 08 May 24
🕹 Technology Modeling
  1. Preventing model exfiltration can be crucial for security; setting upload limits can be a simple yet effective way to protect large model weights from being stolen.
  2. Implementing compression schemes for model generations can significantly reduce the amount of data that needs to be uploaded, providing an additional layer of protection against exfiltration.
  3. Limiting uploads, tracking and controlling data flow from data centers, and restricting access to model data are practical approaches to making exfiltration of model weights harder for attackers.

Launch Of Modeling Mindsets Book 🐙

Mindful Modeler • 139 implied HN points • 08 Nov 22
🚌 Education Modeling
  1. Having multiple modeling mindsets can help overcome challenges in modeling projects.
  2. Different modeling approaches have different strengths and limitations.
  3. It's valuable to understand a variety of modeling mindsets to enhance problem-solving abilities.

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

Technology Made Simple • 59 implied HN points • 14 Mar 23
🕹 Technology Modeling
  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.

The Most Amazing Week in Gen AI Releases

TheSequence • 84 implied HN points • 15 Dec 24
🕹 Technology Modeling
  1. Several major tech companies like OpenAI, Google, and Microsoft launched new AI models in a single week. This shows how quickly AI technology is progressing.
  2. OpenAI's Sora model allows users to create videos from text descriptions, but it has some limitations. It's an exciting step for video generation!
  3. Google's Gemini 2.0 has improved capabilities, allowing it to handle more complex tasks and interact more effectively with users.

Be a centaur

Sunday Letters • 39 implied HN points • 04 Dec 23
🕹 Technology Modeling
  1. Technology is changing fast, and it's important to keep learning and adapting. It's easy to think things have settled down, but we're still on an upward curve.
  2. As AI models improve, they will be more useful in specific areas. It's crucial to understand how to use these models effectively to stay competitive.
  3. To stay relevant, we need to focus on asking the right questions instead of just knowing the answers. Learning how to work with AI tools can give you an edge.

#89 Design in miniature

Design Lobster • 199 implied HN points • 11 Oct 21
🎨 Art & Illustration Modeling
  1. Design can create illusions to make large buildings appear small.
  2. Using models, like papier-mâché creatures, can enhance understanding in design.
  3. The act of making things, like models and prototypes, is essential for true understanding in design.

SNT for Dummies

Gordian Knot News • 131 implied HN points • 06 Jan 24
🔬 Science Modeling
  1. SNT model is crucial for understanding radiation harm.
  2. Dose rate through time is important to realistic radiation harm models.
  3. SNT is more accurate and easy to implement than LNT for assessing radiation harm.

Tang Shiping predicts Trump "highly likely" to win - probability more than 60%

Pekingnology • 56 implied HN points • 03 Nov 24
🇺🇸 U.S. Politics Modeling
  1. A professor predicts that Donald Trump has a greater than 60% chance of winning the 2024 U.S. presidential election. This prediction is based on computer simulations rather than traditional polling.
  2. The simulations suggest Trump will likely win key states like Michigan, Ohio, and Florida, while Harris is expected to win states like Georgia and Arizona.
  3. The forecasting method used is known as Agent-Based Modeling, which combines real data about voters and economic conditions to make predictions rather than relying on expert opinions.

Links and composite keys

Minimal Modeling • 101 implied HN points • 09 Aug 23
🕹 Technology Modeling
  1. Consider using unique constraints for composite keys to ensure data integrity
  2. Splitting tables can be a useful exercise for a cleaner data model
  3. Primary keys serve as both a uniqueness constraint and an identity marker in a table

Smarter Multimodal Models, RPG Benchmarks, and Surprising Scaling Insights

HackerPulse Dispatch • 5 implied HN points • 22 Aug 25
🕹 Technology Modeling
  1. Ovis2.5 is a new language model that processes images in high quality and has a special mode for tough tasks. It's designed to be both quick and accurate.
  2. HeroBench tests how well models can plan in complex virtual games, showing that some models struggle with smart decision-making and organization.
  3. A study on GPT-OSS models found that smaller models can sometimes perform better than larger ones, proving bigger isn't always better in AI.

4-S model

The Century of Biology • 27 implied HN points • 24 Mar 23
🔬 Science Modeling
  1. Technology is changing our relationship with biology.
  2. A model of read, write, edit helps understand DNA technologies.
  3. Focus on Sequencing, Synthesis, Scale, and Software in genetic technologies.

APIs with bounded contexts

microapis.io • 3 HN points • 06 Mar 23
🕹 Technology Modeling
  1. Aligning APIs with the business strategy and ensuring usability are key for API success.
  2. Domain-driven design helps in creating successful APIs by modeling processes and flows that align with the business domain.
  3. Despite challenges, applying domain-driven design to APIs can be achieved by using heuristics to model operations and flows.

Will PostgreSQL switch to a Thread-based model ?

Engineering At Scale • 15 implied HN points • 24 Jun 23
🕹 Technology Modeling
  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 Modeling
  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.

AI Towns and Agent Based Modeling

Magis • 3 HN points • 26 Aug 23
🕹 Technology Modeling
  1. Agent-based modeling uses computer agents to simulate interactions and behavior based on rules.
  2. Large Language Models (LLMs) could enhance agent-based modeling by providing agents with realistic context and knowledge.
  3. Improved agent-based modeling could revolutionize economic forecasting by simulating population-level effects and simplifying forecasting.

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 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.

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

Human Programming • 3 HN points • 24 Jul 23
🕹 Technology 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.

Numbers and Narrative: Modeling, Story Telling and Investing

Musings on Markets • 0 implied HN points • 24 Jun 14
💼 Business Modeling
  1. Valuation is about finding a balance between numbers and narratives. Numbers help provide a foundation, while stories give context to data.
  2. Relying only on numbers can lead to misleading conclusions and shallow analysis. Understanding the story behind the numbers is essential for making informed investment decisions.
  3. Creating a strong narrative can attract investors, but it must be supported by solid numbers. Good storytelling combined with reliable data can improve the chances of investment success.

SQLCoder-70b Becomes the Leading AI SQL Model

AI Disruption • 0 implied HN points • 27 Apr 24
🕹 Technology Modeling
  1. SQLCoder-70b is a leading AI SQL model that outperforms GPT-4 in text-to-SQL generation, showing potential to surpass it.
  2. SQLCoder-70b achieved remarkable breakthroughs in data processing speed and accuracy, making it a significant development in the AI field.
  3. The model was shockingly released on Hugging Face during the peak of the AI wave, demonstrating its competitiveness in the industry.

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

From AI to ZI • 0 implied HN points • 20 Apr 23
🔬 Science Modeling
  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

How To Track Market Actors Like Ants?

Surfing the Future • 0 implied HN points • 19 Apr 24
💼 Business Modeling
  1. Understanding complex systems through model ecosystems can offer insights.
  2. Tracking market dynamics, like carbon flow or toxins, is crucial for social and environmental impacts.
  3. Economic forecasting models are under scrutiny, highlighting the need for improved market design and monitoring.

INFORMS Article on Decision Scientist

Mike Talks AI • 0 implied HN points • 13 Dec 23
🕹 Technology Modeling
  1. Data Scientist term evolved during analytics movement, comprising diverse skills.
  2. Emergence of 'Decision Scientist' role to specialize in turning data into decisions.
  3. Advocacy for the INFORMS community to fully embrace the job title of Decision Scientist.

Weekly Questions - Domain-Driven Design

🔮 Crafting Tech Teams • 0 implied HN points • 07 May 23
🕹 Technology Modeling
  1. Domain-Driven Design focuses on modeling the business language used to define your domain, not the models directly.
  2. DDD concepts do not replace E-R diagrams and planning; they serve to provide a different approach to understanding and representing the domain.
  3. Crafting Tech Teams offers a 7-day free trial for those interested in exploring more about Domain-Driven Design and tech team development.

A model for computing goals as signals

Space chimp life • 0 implied HN points • 30 May 23
🕹 Technology Modeling
  1. Detecting the position of a particle is crucial, as it helps decide if action is needed or not. A good detection system can distinguish between being inside or outside a boundary.
  2. The effectiveness of an actuator is important too. It should reliably apply force when needed, helping to keep the particle within the desired area.
  3. Adding more detectors and actuators can enhance the chances of success, but they still can't guarantee it. Each added component improves the probability but only approaches success asymptotically.

Managing Your OpenAI Token Use

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 28 Nov 23
🕹 Technology Modeling
  1. Managing OpenAI token usage is important for understanding costs. Each interaction you have with the model uses a certain number of tokens, which can add up quickly.
  2. Tokens are calculated differently depending on the model you use. It's essential to know how to convert text to tokens to estimate the cost for your specific needs.
  3. Most current implementations of LLMs focus on experimentation rather than real-time use. This means many users are not fully aware of the cost implications associated with extensive token use in their applications.

OpenAI Seeding, Model Fingerprints & Log Probabilities

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 14 Nov 23
🕹 Technology Modeling
  1. The seed parameter helps in reproducing responses from an AI by combining it with the user prompt. This means if you want the same answer again, you need to use the same seed with the same question.
  2. System fingerprints are used to track changes in the AI model or environment. If the fingerprint changes, the responses might also change, so it’s important to keep track of this along with the seed.
  3. Log probabilities will be introduced to help understand which responses the AI is likely to give. This feature can be useful for improving things like search functions and suggestions.

Large Language Models, Foundation Models & Multi-Modal Models

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 13 Mar 23
🕹 Technology Modeling
  1. Large Language Models (LLMs) are being developed into Foundation Models that can handle tasks beyond just language, like images and voice. This shows how technology is evolving to be more versatile.
  2. GPT-4 is now seen as a Multi-Modal Model that combines different types of data, allowing it to work with text, images, and more. This expands the possibilities for AI applications.
  3. As the use of LLMs increases, there will be more focus on creating fine-tuned models. This means turning unstructured data into structured data for better interaction and understanding.