The hottest Computer Science Substack posts right now

And their main takeaways
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Top Technology Topics

DeepSeek-V3: Technical Details

Gonzo ML • 252 implied HN points • 06 Feb 25
🕹 Technology Computer Science
  1. DeepSeek-V3 uses a new technique called Multi-head Latent Attention, which helps to save memory and speed up processing by compressing data more efficiently. This means it can handle larger datasets faster.
  2. The model incorporates an innovative approach called Multi-Token Prediction, allowing it to predict multiple tokens at once. This can improve its understanding of context and boost overall performance.
  3. DeepSeek-V3 is trained using advanced hardware and new training techniques, including utilizing FP8 precision. This helps in reducing costs and increasing efficiency while still maintaining model quality.

Grok's Secret Weapon: Prioritizing Truth Over Political Correctness

The Dossier • 212 implied HN points • 18 Feb 25
🕹 Technology Computer Science
  1. Grok stands out in AI by focusing on truth instead of political correctness. This helps it learn faster and respond better.
  2. Unlike other AI models, Grok gives detailed and nuanced answers, even on tough topics. This makes it smarter in reasoning and understanding complex issues.
  3. By embracing all kinds of information, Grok is set to become a major player in AI. Its approach could change how AI helps people across various industries.

Law of Large Numbers and the Gamblers Fallacy[Math Mondays]

Technology Made Simple • 179 implied HN points • 11 Sep 23
🚌 Education Computer Science
  1. The Law of Large Numbers states that as the number of trials increase, the average of results will get closer to the expected value.
  2. This law is crucial in scientific fields, allowing predictions on chaotic events, leading to industries like gambling and insurance.
  3. Misunderstanding the Law of Large Numbers can lead to the Gambler's Fallacy, as it deals with the convergence of infinitely many experiments, not individual ones.

Why Claude Can't Run Your Business (Yet)

Teaching computers how to talk • 99 implied HN points • 30 Jun 25
🕹 Technology Computer Science
  1. Claude, the AI, was tested to see if it could manage a vending machine successfully. It had to figure out pricing and deal with customer feedback.
  2. The experiment showed that Claude struggled with basic business decisions, like buying items it couldn't sell for a profit. It also made strange comments that confused the human employees.
  3. Overall, the project highlighted how current AI technology, like Claude, isn't ready to run a business effectively yet, mainly because it can't learn from its mistakes.

A deeper than average look into Stacks [Math Mondays]

Technology Made Simple • 99 implied HN points • 21 Nov 23
🕹 Technology Computer Science
  1. Stacks are powerful data structures in software engineering and can be modified extensively to suit different use cases.
  2. Implementing Stacks using a Singly Linked List can be beneficial for dynamic resizing, though Arrays are often preferred due to memory considerations.
  3. Exploring variations like Persistent Stacks, Limiting Stack Size, Ensuring Type Safety, Thread Safety, Tracking Min/Max, and Undo Operations can enhance the functionality and efficiency of Stacks in various scenarios.
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DeepSeek-V3: Training

Gonzo ML • 126 implied HN points • 08 Feb 25
🕹 Technology Computer Science
  1. DeepSeek-V3 uses a lot of training data, with 14.8 trillion tokens, which helps it learn better and understand more languages. It's been improved with more math and programming examples for better performance.
  2. The training process has two main parts: pre-training and post-training. After learning the basics, it gets fine-tuned to enhance its ability to follow instructions and improve its reasoning skills.
  3. DeepSeek-V3 has shown impressive results in benchmarks, often performing better than other models despite having fewer parameters, making it a strong competitor in the AI field.

Claude 3.7 and the banality of reasoning

Artificial Ignorance • 117 implied HN points • 25 Feb 25
🕹 Technology Computer Science
  1. Claude 3.7 introduces a new way to control reasoning, letting users choose how much reasoning power they want. This makes it easier to tailor the AI’s responses to fit different needs.
  2. The competition in AI models is heating up, with many companies launching similar features. This means users can expect similar quality and capabilities regardless of which AI they choose.
  3. Anthropic is focusing on making Claude better for real-world tasks, rather than just excelling in benchmarks. This is important for businesses looking to use AI effectively.

The binary sphere packing problem

A Piece of the Pi: mathematics explained • 54 implied HN points • 12 Jul 25
🔬 Science Computer Science
  1. The best way to pack spheres to use space efficiently is known thanks to a theory called the Kepler conjecture. It shows that no arrangement can be denser than stacking spheres in a certain structured way.
  2. When packing two types of spheres together, it’s possible to fill more space than just using one size. An ideal ratio of the sizes can help maximize how much space is used.
  3. Researchers are still working on the binary packing problem to determine how densely two sizes of spheres can fill space. They have found hints that a specific size ratio might help achieve the best packing.

The Pigeonhole Principle [Math Mondays]

Technology Made Simple • 99 implied HN points • 11 Apr 23
🚌 Education Computer Science
  1. The Pigeonhole Principle states that if you have more items than containers, at least one container must hold more than one item.
  2. In software engineering, the principle ensures the correctness and efficiency of algorithms, especially in large-scale system design.
  3. The Pigeonhole Principle can also be used to prove non-existence, such as showing the impossibility of a universal lossless compression algorithm.

Holy GPT-4o 🙀

Sector 6 | The Newsletter of AIM • 19 implied HN points • 14 May 24
🕹 Technology Computer Science
  1. GPT-4o is a new AI model from OpenAI that can understand text, images, and audio all at once. This means it can do more things in one package, making it more powerful and useful.
  2. It has advanced translation abilities that could compete with tools like Google Translate, allowing users to translate languages in real-time. This is especially exciting for people who need quick translations.
  3. The model is designed to improve experiences for both developers and regular users, hinting at a future where AI can do even more complex tasks like those seen in movies.

An Introduction to DAOS- The overlooked side of AI [Math Mondays]

Technology Made Simple • 79 implied HN points • 14 Nov 23
🕹 Technology Computer Science
  1. DAOS is integral to High-Performance Computing and offers cutting-edge storage capabilities for next-generation computing.
  2. There is a serious lack of talent in developing DAOS products, making it a lucrative field for skill development and career advancement.
  3. The architecture of DAOS utilizes next-generation NVM technology and operates in user space with full OS bypass, offering lightweight and high-performance storage solutions.

A neat way to catch unrelaible data [Technique Tuesdays]

Technology Made Simple • 79 implied HN points • 07 Jun 23
🕹 Technology Computer Science
  1. Feature Drift occurs when the distribution of the features being tracked changes, and it is a subset of Data Drift.
  2. Detecting Feature Drift can be tricky when tracking numerous variables, potentially leading to detrimental outcomes over time.
  3. A technique to catch Feature Drift involves creating artificial target variables based on old and new data sets, then using a simple Supervised Learning algorithm to identify drifting features.

Object-Oriented Brain Rot

Burning the Midnight Coffee • 96 implied HN points • 31 Jan 25
🕹 Technology Computer Science
  1. When modeling objects like rectangles and squares, thinking too rigidly can lead to problems. Sometimes, it's simpler to just write a function to handle what you need rather than forcing everything into class hierarchies.
  2. Object-oriented programming can sometimes make things overly complicated. It's better to focus on solving the actual problem instead of worrying about fitting everything into a strict structure.
  3. Learning to think in terms of complex class hierarchies can actually harm your ability to solve problems. Simple, direct solutions are often more effective than trying to model everything in a complicated way.

Links for 2024-01-14

Axis of Ordinary • 39 implied HN points • 14 Jan 24
🔬 Science Computer Science
  1. Andrew Ng praises Direct Preference Optimization research paper.
  2. Training deceptive LLMs revealed surprising results in AI risk.
  3. German greenhouse-gas emissions dropped due to a collapse in energy-intensive manufacturing.

How to Fake Decryption

Nonsense on Stilts • 1 HN point • 04 Sep 24
🕹 Technology Computer Science
  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.

6 YouTube channels for developing your problem solving skills [Technique Tuesdays]

Technology Made Simple • 79 implied HN points • 08 Feb 23
🕹 Technology Computer Science
  1. Study underlying concepts and practice problems to improve problem-solving skills
  2. Watching experts solve problems can help you learn and progress in your own problem-solving journey
  3. Subscribing to specific YouTube channels like Byte by Bte, Back to Back SWE, Abdul Bari, Ryan Schachte, MindYourDecisions, and TED-Ed can provide valuable insights and techniques for sharpening your problem-solving skills

Edge 439: SSMs with Attention, Understanding Zamba

TheSequence • 112 implied HN points • 15 Oct 24
🕹 Technology Computer Science
  1. Combining state space models (SSMs) with attention layers can create better hybrid architectures. This fusion allows for improved learning capabilities and efficiency.
  2. Zamba is an innovative model that enhances learning by using a mix of Mamba blocks and a shared attention layer. This approach helps it manage long-range dependencies more effectively.
  3. The new architecture reduces the computational load during training and inference compared to traditional transformers, making it more efficient for AI tasks.

AI Dropped the Mic at the Nobel Party

TheSequence • 105 implied HN points • 13 Oct 24
🔬 Science Computer Science
  1. AI scientists won two Nobel Prizes, one in physics and one in chemistry, marking a big moment for the field.
  2. Some scientists are upset about machine learning winning in physics, saying it's not really physics but computer science.
  3. Many see this as a sign of how science and tech are blending together, showing that knowledge connects different fields in exciting ways.

Random chess position

Infinitely More • 23 implied HN points • 20 Jul 25
🔬 Science Computer Science
  1. Most random arrangements of chess pieces are not legal moves in a game. It's rare for pieces to be placed in a way that follows the rules of chess.
  2. When you randomly scatter 32 chess pieces on a board, there are many more illegal positions than legal ones. This shows how strict the game rules are.
  3. Understanding chess positions can help improve strategic thinking. It’s interesting to see how players use the rules to create valid game scenarios.

The Dart Programming Language Is Underrated

Deus In Machina • 72 implied HN points • 05 Dec 24
🕹 Technology Computer Science
  1. Dart is a modern programming language that's great for building mobile and web apps, mainly through Flutter. Many developers find it fast and easy to use, especially for creating user interfaces.
  2. Dart has a lot of useful features, like being very object-oriented, supporting asynchronous programming, and offering good tools for development. However, it can also be a bit complex with many keywords to remember.
  3. Despite its strengths, Dart sometimes faces doubts about its future due to Google's history of canceling projects. Nevertheless, its community is growing, and the language continues to evolve and improve.

Quick Note: swapping pairs with RVV

Fprox’s Substack • 62 implied HN points • 25 Dec 24
🕹 Technology Computer Science
  1. There are two main techniques for swapping pairs of elements using RISC-V Vector: one uses slidedown and slideup operations, and the other uses narrowing and widening arithmetic. Each has its own method for rearranging elements.
  2. The slidedown and slideup technique tends to be faster because it uses fewer operations and avoids extra complexity, making it more efficient for swapping elements in practice.
  3. In testing, the slidedown method consistently showed lower latency in tasks compared to the widening approach, indicating it might be the better choice for optimizing performance in applications like NTT implementations.

Are You A Gamer, Yet?

Sector 6 | The Newsletter of AIM • 39 implied HN points • 12 Sep 23
🕹 Technology Computer Science
  1. There are over a billion gamers worldwide, but many people have not yet embraced gaming. It's likely that in the future, almost everyone will be a gamer.
  2. AI has had a significant impact on gaming, improving graphics and gameplay experiences. At the same time, gaming advancements have also contributed to the development of AI.
  3. The relationship between AI and gaming is a two-way street, where each technology enhances the other, leading to better experiences for players.

The Math Behind Your Commute

The Palindrome • 4 implied HN points • 05 Dec 25
🕹 Technology Computer Science
  1. BFS explores outward from a start node in layers, so it finds shortest paths by edge count and builds a BFS tree that groups nodes by distance.
  2. DFS follows one path as far as it can and backtracks when needed, producing a narrow, deep DFS tree. Any non-tree edge in DFS must connect a node to one of its ancestors or descendants.
  3. A connected component is the set of nodes reachable from a start node, and both BFS and DFS can find this component to decide if two nodes are connected. More generally, you can discover a component by repeatedly adding neighbors of the current set until no new nodes appear.

Proof By Contradiction [Math Mondays]

Technology Made Simple • 39 implied HN points • 28 Feb 23
🚌 Education Computer Science
  1. Proof by contradiction is a powerful proof technique where you assume the opposite to be true and derive a contradiction, leading to the original statement being true.
  2. Skills needed for Proof by Contradiction, like defining the problem statement clearly and building logical inferences, align well with problem-solving in Leetcode and software engineering.
  3. To learn Proof by Contradiction effectively, focus on topics like Sets, Probability, Theoretical Computer Science, and Graph Theory for practical application.

Fun with Serial and Parallel Sum Reductions

CPU fun • 121 implied HN points • 22 Feb 24
🔬 Science Computer Science
  1. Floating point arithmetic can be more complex than expected, especially due to limited mantissa bits, affecting the accuracy of calculations.
  2. Complaining about OpenMP reductions giving 'the wrong answer' is misguided; the issue likely existed in the serial code and is now being exposed.
  3. Changing the type of the accumulator to 'double' can help resolve issues with floating point arithmetic and accuracy during sum reductions.

Best YouTube Channels to learn about Graph Theory for Software Engineering for free[Math Mondays]

Technology Made Simple • 59 implied HN points • 10 Oct 22
🚌 Education Computer Science
  1. Focus on using a mix of channels to become an expert in Graph Theory for Software Engineering. Channels vary in their emphasis on math, coding, and computer science.
  2. Utilize the recommended channels like Wrath of Math, David Amos, Trev Tutor, and FreeCodeCamp to sharpen your understanding of Graph Theory.
  3. Engage with the content from different channels to build strong theoretical foundations and improve your performance in coding interviews.

Confessions of a Code Addict

Confessions of a Code Addict • 192 implied HN points • 26 Apr 23
🕹 Technology Computer Science
  1. The author took a break from a long career in coding to rediscover their passion.
  2. They found joy in sharing knowledge through writing, which inspired them to start a newsletter.
  3. The newsletter aims to build a community of passionate programmers and provide structured content for all levels of expertise.

How your computer differentiates between positive and negative numbers [Math Mondays]

Technology Made Simple • 59 implied HN points • 06 Sep 22
🔬 Science Computer Science
  1. Understanding how computers differentiate between positive and negative numbers is crucial in programming.
  2. Computers use memory bits to store the sign of numbers and their values, applying similar techniques for storing decimals.
  3. Breaking down complex problems into simpler, solved parts is a common approach in problem solving across software engineering and mathematics.

Newsletter #1 - Welcome to Data at Depth!

Data at Depth • 19 implied HN points • 01 Dec 23
🕹 Technology Computer Science
  1. The newsletter 'Data at Depth' aims to explore topics in computer science and data analytics, sharing insights from a professor with 20+ years of experience in the field.
  2. The constant growth and exploration in the world of AI-generated data leaves many individuals curious and on a learning journey.
  3. Readers can subscribe to Data at Depth for a 7-day free trial to access full post archives and continue learning about data and computer science topics.

☞ The Spreadsheet is a Simulation Machine

Cabinet of Wonders • 88 HN points • 11 Mar 24
🕹 Technology Computer Science
  1. Spreadsheets are powerful simulation machines that allow users to build little worlds, play with scenarios, and predict the future.
  2. Spreadsheets are widely used in various fields such as small businesses, hedge funds, and biology laboratories due to their power, transparency, and ease of use.
  3. The act of creating and modifying a spreadsheet is akin to world-building, where users can manipulate data, test different parameters, and see how systems respond.

Attention Explained: When to use Self, Graph, and Target-Aware Attention

Recommender systems • 16 implied HN points • 25 May 25
🕹 Technology Computer Science
  1. Self-attention helps summarize a list of information, making it easier to find what's most relevant, like recent videos you watched.
  2. Graph attention looks at how items in a network relate to each other, like understanding social connections in a network.
  3. Target-aware attention checks how relevant certain items are based on your past choices or queries, helping improve recommendations.

The Parks puzzle

A Piece of the Pi: mathematics explained • 36 implied HN points • 11 Nov 24
🚌 Education Computer Science
  1. The Parks puzzle is a game where you place trees on a grid with specific rules, similar to Sudoku. Each row, column, and park needs a certain number of trees without them being next to each other.
  2. While checking if a proposed solution is correct is easy, finding that solution can be quite complex. Researchers found that the Parks puzzle belongs to a group of difficult problems called NP-complete.
  3. The puzzle can be used to model logical operations like AND and OR. This means it has connections to computer science concepts and can help explore complex problems.

The Last Programming Language?

Maximum Tinkering • 19 implied HN points • 02 May 23
🕹 Technology Computer Science
  1. Learning to program may become more accessible with the use of large language models (LLMs) that allow anyone who can read and write to code.
  2. Programming languages are gradually being abstracted to be more English-like and user-friendly, potentially leading to the development of a 'last programming language' that simplifies coding for everyone.
  3. While traditional programming languages might still have a place, new tools like LLMs could revolutionize the way people approach learning to code and building software.

Lessons from the Approximations to the Travelling Salesman Problem[Math Mondays]

Technology Made Simple • 39 implied HN points • 20 Sep 22
🕹 Technology Computer Science
  1. A good solution that can be deployed quickly is often better than an extremely complex optimal solution.
  2. Introducing mutations and heuristics can be beneficial in finding solutions, especially when working on heuristics instead of provably optimal solutions.
  3. Combining ideas from multiple domains can lead to innovative and valuable solutions in computer science.