The hottest Algorithms Substack posts right now

And their main takeaways
Category
Top Technology Topics
Graphs For Science • 52 implied HN points • 24 Feb 24
  1. k-Core Decomposition is a way to explore the structure of networks by identifying the largest subgraph where every node has a specified minimum degree.
  2. The k-Core Decomposition algorithm involves recursively removing nodes with degrees lower than a specified threshold to reveal the k-core and k-shell structure of a graph.
  3. The degree of a node in a k-core doesn't have an upper limit, providing unique insights into network connectivity beyond traditional degree-based analysis.
CPU fun • 121 implied HN points • 22 Feb 24
  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.
One Thing • 573 implied HN points • 01 Feb 24
  1. Utilize small, alternative search engines that offer unique approaches not influenced by market trends
  2. Consider using unconventional methods when searching, such as leveraging platforms like Reddit for information
  3. Prioritize authentic search experiences, focusing on genuine connections and unique discoveries rather than catering solely to algorithms
Peter Boghossian • 609 implied HN points • 30 Jan 24
  1. Johann Hari and Peter Boghossian discuss the impact of technology addiction on attention spans and society.
  2. They emphasize the role of social media in capturing attention and keeping users engaged through algorithms.
  3. The shortened attention spans affect relationships, political engagement, and democracy.
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TheSequence • 1106 implied HN points • 18 Jan 24
  1. Discovering new science is a significant challenge for AI models.
  2. Google DeepMind's FunSearch model can generate new mathematics and computer science algorithms.
  3. FunSearch uses a Language Model to create computer programs and iteratively search for solutions in the function space.
Low Latency Trading Insights • 117 implied HN points • 11 Feb 24
  1. The requirements for a rate-limiting algorithm include precise event counting, fast performance especially during market turbulence, and minimal impact on cache memory.
  2. Creating a rate-limiting algorithm using a multimap for counting events has inefficiencies; a better solution involves enhancements for optimal performance.
  3. A bounded approximation approach for rate limiting achieves memory efficiency by assuming a minimum time precision and implementing a clever advance-and-clear mechanism.
The Rectangle • 113 implied HN points • 09 Feb 24
  1. The release of the Vision Pro highlights a split in culture between bootlickers and contrarians.
  2. Bootlickers overly defend products and praise them, while contrarians overly criticize and find flaws in them.
  3. Algorithmisation exacerbates this cultural division by boosting controversial content and leading us into binary situations.
Dan Davies - "Back of Mind" • 334 implied HN points • 19 Jan 24
  1. Supply and demand for electricity become more unpredictable with an increasing proportion of wind and solar energy
  2. The profit motive drives the application of information processing power and bandwidth to solve energy planning problems
  3. Market trading and the profit motive are ways to match the variety of the energy problem with the regulatory system
Fprox’s Substack • 39 implied HN points • 12 Feb 24
  1. Softmax is a non-linear normalization layer commonly used in neural networks to compute probabilities of multiple classes.
  2. When implementing Softmax, numerical stability is crucial due to exponential function's rapid growth, requiring clever techniques to prevent overflow.
  3. RISC-V Vector (RVV) can be used to efficiently implement complex functions like Softmax, with stable and accurate results compared to naive implementations.
Let's talk games & AI. • 4 implied HN points • 19 Feb 24
  1. In about 7.5 years, there is potential for playing any game experience whenever you want.
  2. The speed of GenAI model advancements will likely lead to faster response times for gaming.
  3. Over the next few years, GenAI will revolutionize how games are created and played through user-generated content, dynamic gaming experiences, and cloud gaming solutions.
Implications, by Scott Belsky • 530 implied HN points • 18 Nov 23
  1. AI-powered algorithms are driving polarization by optimizing for attention-grabbing content, widening the surface area of topics that stoke anger.
  2. Our social media feeds are now sourced from algorithmic preferences rather than social networks, shaping the content we are exposed to.
  3. The benefits of physical proximity in fostering creativity and relationships for teams will lead to the emergence of new technologies and management strategies supporting hybrid and remote work environments.
Zero Day • 659 implied HN points • 11 Oct 23
  1. European standards body may make new encryption algorithms public due to backlash over secrecy.
  2. Previously kept secret algorithms had major flaws, prompting consideration for greater transparency.
  3. Independent researchers found vulnerabilities, including intentional backdoors, in old encryption algorithms in use for over 25 years.
Liberty’s Highlights • 452 implied HN points • 18 Oct 23
  1. It's liberating to realize that most fields are understandable to an interested outsider, focusing on big ideas.
  2. Exploring new fields and combining knowledge from different areas can lead to rich and interesting discoveries.
  3. Taking calculated risks and thorough preparation can lead to successful outcomes in business decisions, like pushing all the chips in.
Democratizing Automation • 182 implied HN points • 06 Dec 23
  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.
Confessions of a Code Addict • 286 implied HN points • 12 Nov 23
  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.
Luminotes • 7 implied HN points • 09 Feb 24
  1. AprilTags are similar to QR codes but are used as fiducial markers in robotics for localization purposes.
  2. AprilTags, created by the reputable robotics lab April, enable systems to localize features in 6 degrees of freedom using a single image.
  3. AprilTags differ from QR codes as they are designed for easy detection in low resolution, unevenly lit, or cluttered images and can detect multiple tags.
Recommender systems • 26 implied HN points • 20 Jan 24
  1. Reducing selection bias and popularity bias in ranking is important for recommender systems.
  2. An advocated approach is to factorize user interaction signals to account for biases originating from power users and power items.
  3. The proposals for causal/debiased ranking involve factorization, mutual information, and mixture of logits to improve the ranking model.
Confessions of a Code Addict • 158 HN points • 05 Nov 23
  1. A linear algebra technique can be applied to compute Fibonacci numbers quickly with a logarithmic time complexity.
  2. Efficient algorithms like repeated squaring can compute powers of matrices in logarithmic time, improving performance for Fibonacci number calculations.
  3. A closed form expression using the golden ratio offers a direct method to compute Fibonacci numbers, showing different approaches with varied performance.
Bzogramming • 30 implied HN points • 07 Jan 24
  1. Physics has alternative framings like Lagrangian and Hamiltonian mechanics, which could inspire new ways of viewing computation.
  2. Reversible computing, preserving information by having bijective gates, is crucial for energy efficiency and future computing technologies.
  3. Studying constraint solvers and NP-complete problems can lead to insights for accelerating search algorithms and developing new computing approaches.
Fprox’s Substack • 27 HN points • 09 Jan 24
  1. Transposing a matrix in linear algebra is a common operation to switch row-major and column-major layouts to optimize computations.
  2. Different techniques like strided vector operations and in-register methods can be used to efficiently transpose matrices using RISC-V Vector instructions.
  3. Implementations with segmented memory variants and vector strided operations can be more efficient in terms of retired instructions compared to in-register methods for matrix transpose.
Kyle Chayka Industries • 175 implied HN points • 11 Oct 23
  1. Twitter used to be a vibrant platform for diverse discussions and connections, but has now deteriorated due to algorithms and glitches.
  2. Finding spaces for meaningful human interaction on the internet is becoming increasingly challenging as platforms focus more on algorithms and less on authentic conversations.
  3. Despite the challenges, platforms like Substack are emerging as potential spaces for cultivating genuine communities and conversations.
Never Met a Science • 66 implied HN points • 15 Nov 23
  1. In the attention economy of social media, demand can increase as supply increases, leading to an unsustainable positive feedback loop.
  2. The attention economy operates differently from traditional market economies, with attention being a key commodity rather than money.
  3. Consumers, producers, and algorithms play unique roles in driving the positive feedback loop of the attention economy, which can have far-reaching implications.
GM Shaders Mini Tuts • 157 implied HN points • 11 Sep 23
  1. Alpha blending in shader programming requires blending colors and alpha channels separately.
  2. Weighted averages provide greater control for combining multiple elements together in shaders.
  3. Creating a simple 3D perspective effect in shaders involves scaling with a linear gradient.
Tyler Glaiel's Blog • 567 HN points • 17 Mar 23
  1. GPT-4 can write code when given existing algorithms or well-known problems, as it remixes existing solutions.
  2. However, when faced with novel or unique problems, GPT-4 struggles to provide accurate solutions and can make incorrect guesses.
  3. It's crucial to understand that while GPT-4 can generate code, it may not be reliable for solving complex, new problems in programming.
GM Shaders Mini Tuts • 157 implied HN points • 02 Sep 23
  1. When working with shaders, think in terms of vector fields to direct the flow and create gradients.
  2. Consider the acceptable input domains and the output ranges of your functions to prevent errors and unexpected results.
  3. Utilize periodic functions for repetition, sine and cosine for waves and rotations, dot product as a ruler, and exponentiation for adjusting brightness levels.