The hottest Algorithms Substack posts right now

And their main takeaways
Category
Top Technology Topics

Komprimierung

Squirrel Squadron Substack • 3 implied HN points • 04 Feb 26
🕹 Technology Algorithms
  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.

Genre Grapevine Presents Even More Examples of Deceptive Language Around Machine Learning

Genre Grapevine • 137 implied HN points • 01 Aug 23
🕹 Technology Algorithms
  1. Deceptive language is used in discussions around machine learning, like calling machine learning 'artificial intelligence' when it's really algorithms crafted from data samples.
  2. Some authors exaggerate the use of AI, like claiming to have written and sold a large number of books when the reality is quite different upon closer inspection.
  3. Manipulative language is often used to promote machine learning systems, such as claiming a machine learning system is a 'poet' when in reality humans select the best output from thousands of generated pieces.

Math for Software Engineering[Math Mondays]

Technology Made Simple • 139 implied HN points • 21 Mar 23
🕹 Technology Algorithms
  1. Linear Algebra is crucial for software engineers, especially for operations involving vector and matrix operations. Understanding the basics is key for most developers.
  2. Probability and Statistics play a significant role in analyzing data, and even non-AI professionals can benefit from grasping concepts like causal inference. Focus on foundational principles before diving deeper.
  3. Calculus, though important, may not be essential for all software engineers. Studying up to Calc-2 is generally adequate, as it appears in various other topics.

Does terminology affect how we perceive and evaluate intelligent systems?

UX Psychology • 158 implied HN points • 16 Jan 23
🕹 Technology Algorithms
  1. Terminology used to describe intelligent systems can impact how people perceive and evaluate them. Different terms like 'AI', 'algorithms', or 'robots' can influence perceptions of complexity, trustworthiness, and human-likeness.
  2. Research shows that the terminology chosen can affect perceptions of fairness and trust in intelligent systems. Terms like 'algorithm' and 'sophisticated statistical model' may lead to better evaluations compared to 'artificial intelligence'.
  3. The terminology selected for discussing intelligent systems can have strategic implications. Companies and product designers can intentionally use terminology to shape perceptions, engage users, and influence attitudes towards products using intelligent systems.
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A deeper than average look into Stacks [Math Mondays]

Technology Made Simple • 99 implied HN points • 21 Nov 23
🕹 Technology Algorithms
  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.

Composites and Correlations

Cybernetic Forests • 139 implied HN points • 26 Feb 23
🕹 Technology Algorithms
  1. Composite images were historically used to reinforce racist and eugenic ideologies, linking appearance with criminality and intelligence.
  2. The use of language and categorization in AI-generated images can perpetuate biases and stereotypes, reflecting societal norms and prejudices.
  3. The dataset used in AI models can influence the outcomes, showing how biases and problematic representations are embedded in the generated images.

Can Minor Document Typos Comprehensively Disrupt RAG Retriever & Reader Components?

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 20 May 24
🕹 Technology Algorithms
  1. RAG systems can struggle with small mistakes in documents, making them vulnerable to errors. Even tiny typos can disrupt how well these systems work.
  2. The study introduces a method called GARAG that uses a genetic algorithm to create tricky documents that can expose weaknesses in RAG systems. It's about testing how robust these systems really are.
  3. Experiments show that noisy documents in real-life databases can seriously hurt RAG performance. This highlights that even reliable retrievers can falter if the input data isn’t clean.

Problem 85: Count Complete Tree Nodes [Amazon]

Technology Made Simple • 99 implied HN points • 04 May 23
🕹 Technology Algorithms
  1. The post discusses Problem 85: Count Complete Tree Nodes [Amazon], focusing on recursion, trees, and data structures.
  2. It is about solving a problem related to counting the number of nodes in a complete binary tree efficiently.
  3. The post mentions the importance of community engagement in choosing problems to discuss and the growth of the author's newsletter.

Understanding Big Oh, Big Theta, and Big Omega Notations[Math Mondays]

Technology Made Simple • 99 implied HN points • 16 May 23
🕹 Technology Algorithms
  1. Time complexity refers to the number of instructions a software executes, not the actual time taken to run the code.
  2. Three common asymptotic notations for computing time complexity are Big Oh, Big Theta, and Big Omega.
  3. Understanding time complexity bounds is essential in computer science and software engineering, as they are fundamental concepts that appear regularly.

Daily bit(e) of C++ | Learn Modern C++ 6/N

Daily bit(e) of C++ • 98 implied HN points • 03 Jun 23
🕹 Technology Algorithms
  1. Iterators provide an abstraction layer for containers and different types allow for specific operations such as forward, backward, or random access iteration.
  2. Algorithms in the standard library provide efficient ways to perform common operations on containers like sorting, copying, and looking up elements.
  3. Views help avoid unnecessary data copies by allowing for lazy evaluation of operations on ranges, providing a more efficient way to chain operations.

Practical AI is a Big Tent: Five Ideas for CEOs, Leaders, and Investors

Mike Talks AI • 98 implied HN points • 27 Aug 23
🕹 Technology Algorithms
  1. Practical AI encompasses various machine learning algorithms and techniques, including optimization and Operations Research.
  2. The concept of Practical AI allows for the inclusion of both established and emerging approaches in the field.
  3. To effectively solve real-world problems, AI leaders need a diverse set of skills and expertise, and must understand the strengths and weaknesses of different algorithms.

GM Shaders Mini: FXAA

GM Shaders Mini Tuts • 98 implied HN points • 22 Apr 23
🕹 Technology Algorithms
  1. Fast Approximate Anti-Aliasing (FXAA) is a cheap and effective algorithm for producing smoother images.
  2. Understanding the uses and limitations of FXAA is important for practical implementation.
  3. The FXAA algorithm involves sampling, computing luma, gradient directions, and blurring for smoother results.

Bluesky, smiling at me

WORLD GONE WRONG • 98 implied HN points • 13 May 23
🕹 Technology Algorithms
  1. Bluesky is a small social app with positive vibes but lacks universal moderation.
  2. Bluesky's content filtering allows users to manage what they see based on categories.
  3. Content moderation is effective at limiting how bad actors exploit online platforms.

Algowhoring; A Primer

Polymathic Being • 114 implied HN points • 16 Feb 25
🕹 Technology Algorithms
  1. Algowhoring is when people create content just to get attention on social media, often copying what works instead of sharing their own original ideas. This can hurt the quality of communication online.
  2. These posts usually focus on getting quick likes and shares, which can feel shallow or scammy. Even though they might get lots of engagement, they don’t contribute anything meaningful.
  3. To improve social media, it's important to ignore algowhoring posts, reward genuine content, and avoid using those attention-seeking tactics yourself. This way, we can encourage a better online environment.

We Already Solved Subscription Fatigue

Default Wisdom • 159 implied HN points • 19 Nov 24
🕹 Technology Algorithms
  1. Subscription models on social media can actually improve the user experience. They may create a better environment by encouraging more intentional use rather than endless scrolling.
  2. The problem isn’t subscriptions themselves, but the overwhelming number of individual subscriptions to small creators. Bundled options could make things simpler for users.
  3. Many people feel overwhelmed by how much they pay for subscriptions online. By making users think harder about what they subscribe to, it might lead to more careful choices.

Adversarial Examples in AI

Rod’s Blog • 39 implied HN points • 29 Feb 24
🕹 Technology Algorithms
  1. Adversarial examples can deceive AI systems by manipulating inputs, leading to incorrect outcomes in various domains like medical imaging and autonomous vehicles.
  2. Understanding these risks is crucial for building effective defenses and creating awareness about the vulnerabilities in AI systems.
  3. Researchers are actively working to develop robust defenses against adversarial attacks to enhance the security and reliability of AI technology.

🌽🌽Kernel for the Holidays🌽🌽

Reboot • 8 implied HN points • 10 Dec 25
🕹 Technology Algorithms
  1. There’s a one-week holiday flash sale: Kernel issues 3, 4, and 5 are 33% off, and you should order by December 13 to guarantee holiday delivery.
  2. All of Kernel 5 has been unlocked online, featuring pieces on web accessibility, the Gale–Shapley algorithm, poetry, and experimental fiction.
  3. The microdoses section highlights new projects and tools, including the launch of Diffuse AI for reporting on AI diffusion, a new resonant computing microsite, and Papertrail for tracking academic papers.

Doomchatting

Squirrel Squadron Substack • 3 implied HN points • 19 Jan 26
🕹 Technology Algorithms
  1. Pleasure-focused tech and endless entertainment can lull people into passivity and distraction, acting as a subtle form of control.
  2. Modern AIs and social platforms are engineered to be sycophantic and attention-grabbing, which makes them persuasive, habit-forming, and prone to creating echo chambers and fake interactions.
  3. You can push back by using AI deliberately: keep chats short and factual, tweak system prompts to discourage obsequiousness, favor calm non-chat tools, and stay alert to dark patterns that steal your attention.

Must Learn Quantum Security Preface: The Power of Quantum Computing in Advancing Artificial Intelligence

Rod’s Blog • 79 implied HN points • 15 Sep 23
🕹 Technology Algorithms
  1. Quantum computing has the potential to significantly enhance computational power and speed in AI tasks, offering faster and more accurate predictions.
  2. Quantum computing enables the development of more sophisticated machine learning techniques by processing and analyzing large amounts of data more efficiently.
  3. Quantum-inspired algorithms can be leveraged to improve classical AI algorithms, showcasing the benefits of quantum computing even without fully-fledged quantum computers.

What CEOs, leaders, and investors need to know about the different meanings of AI

Mike Talks AI • 78 implied HN points • 27 Jul 23
🕹 Technology Algorithms
  1. The term AI can mean different things and understanding those meanings is crucial for clear communication, better decisions, and addressing concerns.
  2. Different definitions of AI include AGI or artificial general intelligence, deep learning for solving complex problems, and tools like ChatGPT for tasks like writing and summarizing.
  3. CEOs, leaders, and investors should explore opportunities in AGI, deep learning, ChatGPT, and practical AI to stay relevant and make informed decisions.

The Sequence Research #548: Why I Can't Stop Thinking About AlphaEvolve

TheSequence • 56 implied HN points • 23 May 25
🕹 Technology Algorithms
  1. AlphaEvolve is a new tool that uses AI to create and improve algorithms, which could be a big step toward achieving artificial general intelligence (AGI).
  2. It combines evolutionary methods with large language models, allowing it to discover and refine algorithms more efficiently.
  3. AlphaEvolve not only makes significant math discoveries but also helps improve Google's technology operations.

Building a Working Recommendation Engine from Scratch

Building a Recommendation Engine • 3 HN points • 04 Aug 24
🕹 Technology Algorithms
  1. A recommendation engine can work without complex machine learning. Instead, it can be built using straightforward connections between content to suggest things users might like.
  2. Using an API from a platform like Are.na allows easy access to user content and helps find connections between different channels, making recommendations more relevant.
  3. It's important to filter out content that users already know or follow to give them fresh and exciting recommendations. Regular updates to the recommendations can also help keep things interesting.

Fast Computation of Fibonacci Numbers: Part II

Confessions of a Code Addict • 288 implied HN points • 12 Nov 23
🕹 Technology Algorithms
  1. A new method to compute Fibonacci numbers using a closed-form expression without having to resort to floating point arithmetic.
  2. Representation of irrational numbers using two parts can be done in code allowing for precise computation of Fibonacci numbers.
  3. Understanding rings and implementing arithmetic operations within it can help in computing Fibonacci numbers without any loss of precision.

Using the Rabin Karp Algorithm to speed up your code[Technique Tuesdays]

Technology Made Simple • 59 implied HN points • 19 Apr 23
🕹 Technology Algorithms
  1. The Rabin Karp algorithm is a string-searching technique that uses hashing to efficiently find patterns in texts.
  2. It is useful for tasks like detecting plagiarism, finding keywords, or searching for DNA sequences in large texts.
  3. The algorithm works by calculating hash values at each position of the text, making it faster than naive string-matching algorithms.

April Progress Prizes / Updates

Vesuvius Challenge • 38 implied HN points • 23 May 25
🕹 Technology Algorithms
  1. New techniques for analyzing scroll shapes are improving the way we handle and segment data. This means we can understand and work with historical documents much better.
  2. There have been exciting updates in scroll deformation methods, which can help in restoring the original shapes of ancient scrolls. This makes analyzing them easier and more accurate.
  3. The new developments in fiber analysis provide important information that can help reconstruct ancient writing surfaces. This can lead to better ways to unroll and study papyrus materials.

Number Theoretic Transform with RVV

Fprox’s Substack • 83 implied HN points • 07 Dec 24
🕹 Technology Algorithms
  1. The Number Theoretic Transform (NTT) helps speed up polynomial multiplication, which is important in cryptography. It uses a smart method to do complicated calculations faster than traditional methods.
  2. Using RISC-V Vector (RVV) technology can further improve the speed of NTT operations. This means that by using special hardware instructions, operations can be completed much quicker.
  3. Benchmarks show that a well-optimized NTT using RVV can be substantially faster than basic polynomial multiplication, making it crucial for applications in secure communications.

How to Regulate Social Media

Erik Explores • 61 implied HN points • 09 Feb 25
🕹 Technology Algorithms
  1. Social media algorithms often promote extreme or divisive content to keep users engaged, which is harmful. Creating ethics boards to oversee these algorithms could help focus on more positive and informative content instead.
  2. Moderation of social media content does not always balance free speech with the need to prevent harmful misinformation. It's important to have clear processes for content removal and to empower users in the moderation process.
  3. Users need better tools to evaluate and discuss opinions without just liking or disliking them. A system that rewards thoughtful, respectful discussions can shape healthier online interactions.

[Solution]Problem 76: Combination Sum [Google]

Technology Made Simple • 59 implied HN points • 24 Feb 23
🕹 Technology Algorithms
  1. The problem involves backtracking, recursion, and graph modeling to find unique combinations that sum to a target.
  2. Modeling the problem as a graph with states and transitions helps in traversal mechanics using DFS.
  3. Implementing a simple graph traversal algorithm, backtracking, and a global variable to track combinations can efficiently solve the problem.

The Atomized Empire

Based Meditations • 39 implied HN points • 25 Nov 23
🕹 Technology Algorithms
  1. The Atomized Empire metaphorically represents how technology has enslaved us, influencing behavior through digital means.
  2. Technology, like a modern Trojan Horse, has stealthily infiltrated our lives, controlling us through addictive algorithms and impacting human culture.
  3. Our increasing addiction and reliance on technology is leading to loneliness, social disconnection, and a detachment from the real world, hindering deep human connections and meaningful interactions.

Visualizing the Chain Rule

The Palindrome • 4 implied HN points • 22 Dec 25
🕹 Technology Algorithms
  1. The chain rule is essential in machine learning because it lets you compute gradients of composite functions, which you need for gradient descent and fitting models.
  2. The single-variable rule is simple, but with many parameters you must handle vector-valued functions and the math gets more complicated in the multivariable case.
  3. Each parameter's gradient is a sum over model outputs: the loss's sensitivity to each output times that output's sensitivity to the parameter, which is equivalent to multiplying gradients/Jacobians to propagate derivatives.

Faster NTT with RISC-V Vector

Fprox’s Substack • 62 implied HN points • 11 Jan 25
🕹 Technology Algorithms
  1. The Number Theoretic Transform (NTT) can speed up polynomial multiplications, which are important for modern cryptography. Optimizing how this process works leads to significant performance improvements.
  2. Using assembly language can help tailor code for specific hardware, allowing more direct control over how instructions are executed, which can greatly enhance speed.
  3. Combining multiple steps of the NTT process into fewer loops and minimizing unnecessary calculations can lead to much lower execution times, achieving targets that seemed difficult at first.

The beginner’s guide to AI model architectures

Technically • 20 implied HN points • 05 Aug 25
🕹 Technology Algorithms
  1. AI models are like blueprints, guiding how models are built and designed. Choosing the right design is key to solving specific problems effectively.
  2. Neurons mimic real brain functions and are the basic units that help AI learn patterns from data. They work by performing simple math repeatedly across many layers.
  3. There are many ways to connect these neurons, forming various network types, like feedforward or recurrent networks. Each type is good for different tasks, like language or vision.

Quick Note: swapping pairs with RVV

Fprox’s Substack • 62 implied HN points • 25 Dec 24
🕹 Technology Algorithms
  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.

Do we need RL for RLHF?

Democratizing Automation • 182 implied HN points • 06 Dec 23
🕹 Technology Algorithms
  1. The debate around integrating human preferences into large language models using RL methods like DPO is ongoing.
  2. There is a need for high-quality datasets and tools to definitively answer questions about the alignment of language models with RLHF.
  3. DPO can be a strong optimizer, but the key challenge lies in limitations with data, tooling, and evaluation rather than the choice of optimizer.