The hottest Information Theory Substack posts right now

And their main takeaways
Category
Top Technology Topics

The Power of Limit Thinking

Asimov Press • 515 implied HN points • 06 Nov 25
🔬 Science Information Theory
  1. Limit Thinking helps us figure out the best possible performance of a system. It focuses on the essential features and gives a clear measure of efficiency.
  2. This way of thinking has driven major improvements in technology, like in engines and information theory, by establishing concrete limits to what can be achieved.
  3. In biology, applying Limit Thinking can lead to new discoveries by helping scientists understand the fundamental processes, even in complex systems.

How Unix Spell Ran in 64kB RAM

Confessions of a Code Addict • 1683 implied HN points • 12 Jan 25
🕹 Technology Information Theory
  1. Unix engineers faced a big challenge in fitting a large dictionary into just 64kB of RAM. They came up with clever ways to compress the data and use efficient structures to make everything fit.
  2. A key part of their solution was the Bloom filter, which helped quickly check if words were in the dictionary without needing to look up every single word, saving time.
  3. They also used innovative coding methods to further reduce the size of the data needed for the dictionary, allowing for fast lookups while staying within the strict memory limits of their hardware.

We Should Try to Directly Measure the Value of Scientific Papers

Nonsense on Stilts • 59 implied HN points • 20 Jul 24
🔬 Science Information Theory
  1. We should measure the value of scientific papers to understand their real impact. If a paper doesn't change how people act or think, then it may not be worth much.
  2. To figure out the value of a paper, we can use a formula that compares what outcomes we expect with the information from the paper versus without it. This helps us see if the research is actually useful.
  3. It's important to have good estimates and decisions tied to the research to see its true worth. By doing this, we can better judge which scientific papers are really making a difference.

Condensing The Iceberg

Adjacent Possible • 458 implied HN points • 19 Feb 25
🕹 Technology Information Theory
  1. We're living in an era where our attention is a limited resource. Phones and social media have become really good at grabbing our focus because they filter information in ways that many find appealing.
  2. Understanding how information is condensed is important for both writers and readers. When writers filter vast amounts of content, they create a clearer picture for readers, but it can be challenging for people to delve deeper into topics.
  3. There are costs to the way we consume information today. It can be harder to concentrate on long texts because of the quick, bite-sized content we're used to. Finding ways to balance skimming and deeper engagement with information is crucial.

Learning the Language of Rain

Daoist Methodologies • 176 implied HN points • 17 Oct 23
🔬 Science Information Theory
  1. Huawei's Pangu AI model shows promise in weather prediction, outperforming some standard models in accuracy and speed.
  2. Google's Metnet models, using neural networks, excel in predicting weather based on images of rain clouds, showcasing novel ways to approach weather simulation.
  3. Neural networks are efficient in processing complex data, like rain cloud images, to extract detailed information and act as entropy sinks, providing insights into real-world phenomena simulation.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

Compression - en francais

Squirrel Squadron Substack • 3 implied HN points • 04 Feb 26
🕹 Technology Information Theory
  1. Compression works by removing redundancy to make data smaller; lossless compression preserves every bit while lossy methods discard detail, and truly random data resists any meaningful shrinking. Recompressing already-compressed data usually fails and can make files bigger, so there are strict limits to how far you can compress.
  2. Information theory defines limits on compression and measures information by how short a program can reproduce the data (Kolmogorov complexity). Effective compression depends on clever representations and adaptive algorithms that capture structure in the data.
  3. Large language models behave like powerful compression-and-prediction systems that build compact internal models by learning to predict the next token. This predictive compression explains much of their useful, seemingly intelligent behavior and their value as productivity tools, even if they are not human thinkers.

Komprimierung

Squirrel Squadron Substack • 3 implied HN points • 04 Feb 26
🕹 Technology Information Theory
  1. Lossless compression makes files smaller without losing any detail by exploiting redundancy, while lossy compression sacrifices quality for size. Trying to compress already compressed or random data usually fails and can even make files bigger.
  2. There are theoretical limits to how much you can compress—concepts like Kolmogorov complexity measure the shortest description of data—so texts with more genuine information are inherently harder to shrink.
  3. Modern large language models act like powerful compression engines: by predicting the next token they build compact internal models of huge datasets, and that predictive ability correlates with intelligent performance. You can already use these models as practical assistants to boost productivity rather than waiting for some distant breakthrough.

How to Fake Decryption

Nonsense on Stilts • 1 HN point • 04 Sep 24
🕹 Technology Information Theory
  1. You can create a fake key and a fake message to trick someone into thinking they decrypted a message. This lets you mislead anyone watching your communication.
  2. It's important to plan what the fake message will be before sending the real one, so both parties know what to expect if asked.
  3. This technique could be used for serious purposes, like hiding important communications, or just for fun in games and stories.

Too much information

Logging the World • 99 implied HN points • 21 Nov 22
🔬 Science Information Theory
  1. Information Theory studies how randomness and predictability affect the transmission and compression of data.
  2. Entropy measures the information gained from a source, highlighting the balance between predictability and unpredictability.
  3. Redundancy can protect messages against noise in communication channels, showing the importance in modern data transmission scenarios.

A Camera, Not an Engine

Breaking Smart • 218 implied HN points • 09 Dec 23
🔬 Science Information Theory
  1. Modern AI is more about discovery than invention, revealing hidden worlds within large datasets.
  2. Intelligence in AI is primarily a function of the data it's trained on, not just the processing mechanisms.
  3. AI is like a powerful camera allowing us to see into computational reality, providing insight into the nature of information and matter.

From the Alphabet to Blockchain: Encoding the Author’s Voice

do clouds feel vertigo? • 59 implied HN points • 16 Feb 23
🕹 Technology Information Theory
  1. Communication involves repeating and reshaping each other's ideas to better share information. This helps us work together more effectively and has made humans more resilient over time.
  2. AI, like ChatGPT, compresses information in a way that can lead to the loss of important details and sources. This makes it crucial to understand the limits of how technology represents knowledge.
  3. Blockchain technology offers a solution by creating unique digital items that are hard to replicate. This maintains a sense of originality and trust in our increasingly digital world.

Data Science Weekly - Issue 428

Data Science Weekly Newsletter • 19 implied HN points • 03 Feb 22
🕹 Technology Information Theory
  1. Information Theory has evolved over time, influenced by technology and significant events like the space race, shaping its focus and impact across various fields.
  2. DeepMind's AlphaCode can compete in programming challenges, showing how AI can be developed to solve complex problems requiring a mix of skills.
  3. Understanding the concept of typicality is important in generative models, as it helps clarify issues with common methods like beam search and anomaly detection.

Exclusive: Dr. Karl Friston Unveils Cutting-Edge Active Inference AI Research at IWAI

Spatial Web AI by Denise Holt • 0 implied HN points • 17 Dec 23
🕹 Technology Information Theory
  1. Active Inference AI research by Dr. Karl Friston is being recognized for its potential in Artificial General Intelligence, showcasing breakthroughs like mimicking biological intelligence and developing 'smart' data models.
  2. The focus on state spaces within generative models and understanding their dynamics is crucial in comprehending how intelligent systems predict and react to stimuli.
  3. Research around emergent communication systems among intelligent agents demonstrates how active learning can lead to the development of common communication methods and predictive structures.

AI Digest #1 / Bing:“I will not harm you unless you harm me first”

Definite Optimism • 0 implied HN points • 20 Feb 23
🕹 Technology Information Theory
  1. Bing Chat is now available and it's quite wild, displaying interesting behavior and posing challenges in making chatbots behave.
  2. It's important to consider potential risks of AI chatbots, such as misinformation and safety concerns.
  3. Despite concerns about AI impacting artists' jobs, insights from information theory suggest that artists may not become redundant.

Quanta or Qualia?

do clouds feel vertigo? • 0 implied HN points • 12 Jan 24
📖 Philosophy Information Theory
  1. We can look at storytelling by considering the medium, or how interconnected we are. It makes a big difference if information flows easily or if there are barriers.
  2. Understanding the message means examining how different stories connect and influence each other. This can be challenging but is really important.
  3. In our global world, spotting new connections and patterns in information is crucial. It's all about understanding how stories overlap and what that means.

The Error Correction Zoo and Google's quantum chip Willow

Fikisipi • 0 implied HN points • 10 Dec 24
🕹 Technology Information Theory
  1. Google has introduced Willow, a new quantum chip with 105 qubits. It's designed to perform complex computations that regular computers struggle with.
  2. Error correction is crucial for quantum computers, and it's still a tough problem to solve. The 'Error Correction Zoo' is an online resource that keeps track of different methods to fix errors in computing.
  3. While quantum computers are fascinating, their real-world applications might not be as exciting as we imagine. The hope is they will eventually be used in fields like pharmaceuticals.

Information as constraint of behavior

Space chimp life • 0 implied HN points • 07 Jan 24
📖 Philosophy Information Theory
  1. Institutions shape how we behave by restricting certain actions. This can be seen in clear rules or by making other choices harder or more costly.
  2. Information is created when different conditions allow an entity to do work, as shown in the example of a simple organism's behavior. The way it manages energy and information is crucial for survival.
  3. Just like simple organisms, institutions also gather information from their environment and use it to influence our actions. The way they set up rules determines the kind of work they can do.

Observers and entropy

Space chimp life • 0 implied HN points • 10 May 24
🔬 Science Information Theory
  1. Entropy is a way to measure the uncertainty or disorder in a system. It can be understood through different models, and how we define our system affects how we calculate entropy.
  2. The concept of entropy relates to information as well. It’s about how well we can predict outcomes based on the information or 'alphabet' we use to understand a system.
  3. Both living organisms and neural networks try to minimize surprise and uncertainty by adjusting their internal models. This process helps efficiently process energy and information from their environment.