The hottest Algorithms Substack posts right now

And their main takeaways
Category
Top Technology Topics

How to Solve Leetcode Brain Teasers [Technique Tusdays]

Technology Made Simple • 39 implied HN points • 09 Nov 22
🕹 Technology Algorithms
  1. Brain teasers in interviews may seem simple but can be tricky to solve because of their deceptive simplicity.
  2. When stuck on a problem, look for something familiar to latch onto and analyze it in depth to gain clarity on possible solutions.
  3. Talking out loud about the problem can help make connections, leading to better problem-solving and understanding.

Log Transformations for efficient multiplication between lots of positive numbers [Technique Tuesdays]

Technology Made Simple • 39 implied HN points • 02 Nov 22
🔬 Science Algorithms
  1. Log transformations can be used for efficient multiplication between large numbers by converting the problem into addition of logs, making it more manageable.
  2. Logs have interesting properties that make them useful for handling computations with very large or very small numbers.
  3. Using log transformations is a clever math technique that is commonly used in fields like AI, Big Data, and Machine Learning to handle large computations.

AI, is it Logic or Magic?

The Novice • 19 implied HN points • 26 Oct 23
🕹 Technology Algorithms
  1. AI is based on statistics and massive data processing, not magic.
  2. AI mimics human-like thought processes through algorithms and machine learning techniques.
  3. Understanding AI involves complex details and processes beyond human perception.

"Algorithmic entombment", explore-exploit trade-offs, and serendipity

The Counterfactual • 59 implied HN points • 04 Oct 22
🕹 Technology Algorithms
  1. Recommendation systems can help us find new favorites but also risk making our choices repetitive. If we're only shown what we already like, we might miss out on discovering exciting new things.
  2. There's a balance between exploring new options and sticking to what we know. Too much of either can lead to boredom or discomfort, so it’s important to mix both approaches in our choices.
  3. Serendipity, or those happy accidents that lead to great moments, can be lost with strict recommendation systems. Sometimes the best experiences come from unexpected encounters, not just from things we already enjoy.

Links #4

Splitting Infinity • 19 implied HN points • 03 Oct 23
🔬 Science Algorithms
  1. Featured topics include a New State Solution for Israel and Palestine, companies in technology, and innovations throughout history.
  2. Specialized teams can offer higher-quality and healthier food efficiently than home cooking, potentially changing kitchen dynamics.
  3. Research highlights advancements in electron beams, extreme bandit problem solutions, and potential uses of superoscillation technologies.
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What if you could tweak the algorithm?

do clouds feel vertigo? • 39 implied HN points • 06 Mar 23
🕹 Technology Algorithms
  1. Users should be able to customize their social media algorithms to see content that truly interests them. This way, they can avoid echo chambers and connect with valuable information.
  2. Decentralized social networks have the potential to disrupt the current big platforms by giving users more control over their data and experiences. Open protocols can lead to better privacy and diversity.
  3. Algorithms are crucial in shaping online experiences, and their evolution will continue. Community-driven algorithms in decentralized networks could offer new ways to recommend content effectively.

[Solution]Problem 80: Unique Paths[Google]

Technology Made Simple • 19 implied HN points • 24 Mar 23
🕹 Technology Algorithms
  1. The problem discussed involves finding the number of unique paths a robot can take to reach the bottom-right corner of a grid by moving only down or right.
  2. Grid traversal, dynamic programming, and recursion are key concepts used to solve this problem efficiently.
  3. The test cases provided ensure that the answer is less than or equal to 2 * 10^9, with constraints on the grid size.

All about the graphs [Math Monday]

Technology Made Simple • 59 implied HN points • 29 Mar 22
🕹 Technology Algorithms
  1. Graphs can be seen from various perspectives: charts and plots (stats), maps with complex algorithms (graph theory), and adjacency lists for coding. Understanding these perspectives is crucial for effective use of graphs.
  2. Identifying whether a problem could be a graph problem involves recognizing the entities (nodes), relationships (edges), and weights in the context of a system. This spotting framework helps in solving graph-related problems efficiently.
  3. Practicing graph spotting as a skill involves starting with easy problems to identify graph components quickly. Familiarity with graphs and the ability to spot them easily is crucial for solving graph problems in interviews.

105 trillion digits of pi

A Piece of the Pi: mathematics explained • 60 implied HN points • 15 Mar 24
🔬 Science Algorithms
  1. The number pi has now been calculated to 105 trillion decimal places using the Chudnovsky algorithm over 75 days.
  2. Ramanujan's formula for pi has been expanded and improved upon over the years, with the Chudnovsky brothers developing a formula that computes pi to 13 decimal places.
  3. Bellard's formula and the BBP formula provide ways to compute specific digits of pi without having to calculate all earlier digits, making validations faster and more efficient.

Problem 51:Happy Number[IBM]

Technology Made Simple • 39 implied HN points • 10 Aug 22
🕹 Technology Algorithms
  1. The problem highlighted focuses on determining if a number is a happy number through a specific process involving the sum of squares of its digits.
  2. A happy number reaches 1 through the process described, whereas some numbers loop endlessly without reaching 1.
  3. The post also mentions a newsletter aimed at helping individuals succeed in tech interviews by providing valuable resources and techniques.

Power Function in logarithmic time [Technique Tuesdays]

Technology Made Simple • 39 implied HN points • 09 Aug 22
🕹 Technology Algorithms
  1. Optimizing the power function using logarithmic time can be a game-changer, making computations quicker and efficient.
  2. Understanding and applying mathematical tricks like leveraging even and odd numbers can significantly reduce the number of instructions needed to solve a problem.
  3. Learning to optimize algorithms using divide and conquer techniques, such as in the power function example, can enhance problem-solving skills and overall coding proficiency.

Specifying objectives in RLHF

Democratizing Automation • 90 implied HN points • 02 Aug 23
🕹 Technology Algorithms
  1. Reinforcement learning from human feedback involves using proxy objectives, but over-optimizing these proxies can negatively impact the final model performance.
  2. Optimizing reward functions for chatbots with RLHF can be challenging due to the disconnect between objective functions and actual user preferences.
  3. A new paper highlights fundamental problems and limitations in RLHF, emphasizing the need for a multi-stakeholder approach and careful consideration of current technical setups.

GPT-4 invalidates the Turing test

Gray Mirror • 110 implied HN points • 13 Apr 23
🕹 Technology Algorithms
  1. Large language models like GPT-4 are not AI, but they are powerful tools that connect patterns and rely on intuition.
  2. The Turing test is not a valid test for AGI, as machines like LLMs can invalidate it by excelling in certain tasks while lacking in others.
  3. Understanding the difference between general and special intelligence is key to not overestimating the capabilities of tools like GPT-4.

Reduce memory of graph traversal by marking spot as visited instead of using a set[Technique Tuesdays]

Technology Made Simple • 39 implied HN points • 02 Aug 22
🕹 Technology Algorithms
  1. In graph traversal, reducing memory usage by marking spots as visited instead of using a set can optimize your code and help you move from O(n) space complexity to O(1) complexity.
  2. This technique is straightforward to implement, takes no extra space, and can be a significant improvement in graph traversal algorithms.
  3. When implementing this technique, be cautious about the value used to mark visited cells and always confirm with your interviewer about input data type to avoid conflicts.

Why social media should give users control over their algorithms

The Kahneman Bot • 19 implied HN points • 05 Mar 23
🕹 Technology Algorithms
  1. Users trust and use algorithms more when they have control over them, despite the benefits algorithms offer.
  2. In product design, be cautious about taking autonomy away from users as it can hinder their happiness and decision-making.
  3. Data-driven products should consider giving users more control over algorithms to improve trust, engagement, and overall value.

[Solution]Problem 48:Valid Parentheses[Amazon]

Technology Made Simple • 39 implied HN points • 21 Jul 22
🕹 Technology Algorithms
  1. Understanding the concept of valid parentheses is crucial in coding interviews to solve classic problems like determining if a string of brackets is valid.
  2. Key rules for valid parentheses involve closing the brackets in the correct order and ensuring that the opening and closing brackets match.
  3. Developing an algorithm to validate parentheses involves utilizing the Last In, First Out (LIFO) principle with stacks to track opening and closing brackets.

Don't lie to the computer

Sunday Letters • 79 implied HN points • 21 Feb 22
🕹 Technology Algorithms
  1. Lying to computers can lead to big problems. Computers take everything at face value and won't understand when you're not being honest.
  2. This can happen in many areas, like bug reporting or software design. For example, making up a fake bug level instead of addressing real issues is misleading.
  3. It's easy to want to cut corners to save time, but being dishonest can cause issues down the line. Just like in personal relationships, honesty is usually the best policy.

Quant Letter: November 2024, Week-2

The Parlour • 25 implied HN points • 13 Nov 24
💰 Finance Algorithms
  1. A new computational method can measure the shadow rate, which helps in comparing different investment types. This can give investors better insights.
  2. Using multi-agent systems for investment research allows adaptation to changing market conditions, leading to improved performance over traditional models.
  3. Machine learning continues to show promise in finance, with various models effectively predicting market behavior and improving investment strategies.

k-Core Decomposition

Graphs For Science • 52 implied HN points • 24 Feb 24
🔬 Science Algorithms
  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.

On Social Media, Demand Slopes Upwards

Never Met a Science • 66 implied HN points • 15 Nov 23
🕹 Technology Algorithms
  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.

Undecidability Isn't So Bad

Bzogramming • 22 implied HN points • 07 Dec 24
🕹 Technology Algorithms
  1. Some problems in computing are called undecidable, which means we can't find a definite solution for them. However, that doesn’t mean we can’t approach them creatively and get some useful results.
  2. When working with programs, understanding their behavior can often reveal hidden bugs. If a program doesn't behave the way we expect, it might be a sign that something is wrong in the code.
  3. There are smarter ways to analyze code than just throwing our hands up and saying it’s impossible. Advanced tools are already in place in many programming environments, but they often work behind the scenes without us being aware of them.

[Solution]Problem 41: Create your own Datastructure with O(1) Time complexity (Dropbox)

Technology Made Simple • 39 implied HN points • 11 Jun 22
🕹 Technology Algorithms
  1. Creating a data structure with O(1) time complexity involves implementing functions like plus, minus, get_max, and get_min efficiently.
  2. Utilizing a Doubly Linked List allows for maintaining a sorted collection of keys, enabling quick access to elements with the lowest and highest values.
  3. Developing algorithms to handle key count increments and decrements while preserving the sorted order of the linked list is crucial for a functional solution.

Using Bits as a way to Encode Preference[Technique Tuesdays]

Technology Made Simple • 39 implied HN points • 01 Jun 22
🕹 Technology Algorithms
  1. Using bit fields can significantly reduce storage requirements for tracking user preferences. A technique by Vimeo engineers allowed O(1) space compared to the traditional O(k) method, making the solution far more efficient.
  2. Bit fields utilize bitwise operators to represent content filters, enabling quick comparisons in constant time. This approach is memory and time-efficient.
  3. Implementing bit fields for tracking user preferences allows for efficient filtering of content by performing a bitwise AND operation between the user's and video's bit fields. This results in a quick eligibility check for the user.

Recursive Leap of Faith [Technique Tuesdays]

Technology Made Simple • 39 implied HN points • 18 May 22
🕹 Technology Algorithms
  1. The 'Recursive Leap of Faith' technique is a powerful approach in recursion where we assume our recursive calls will work as expected, simplifying our problem-solving process.
  2. By using the Leap of Faith, we can break down recursive problems into base cases and recursive steps, making it easier to navigate through complex coding challenges.
  3. To master the Recursive Leap of Faith technique, consistent practice is key. Breaking down problems into base cases and making assumptions about recursive calls helps build proficiency over time.

Understanding Hashing [Math Mondays]

Technology Made Simple • 39 implied HN points • 17 May 22
🕹 Technology Algorithms
  1. Hashing efficiently maps data to integers for quick searches and insertions.
  2. Design choices in hashing involve handling collision, with options like separate chaining and open probing.
  3. Rolling hash enables efficient substring searches within larger strings by computing hashes incrementally.

[Solution]Problem 37: Word Search[Amazon]

Technology Made Simple • 39 implied HN points • 13 May 22
🕹 Technology Algorithms
  1. Identifying the pattern in graph problems can help simplify the solution - like finding adjacent letters in a grid.
  2. Using the correct graph traversal algorithm is crucial, like choosing DFS for visiting every node in a graph.
  3. Implementing backtracking in DFS can help efficiently solve problems - like removing unnecessary nodes for optimization.

Recurrence Relations[Math Mondays]

Technology Made Simple • 39 implied HN points • 10 May 22
🚌 Education Algorithms
  1. Recurrence relations are crucial in Computer Science and Discrete Math, defining the basis of Time Complexity.
  2. Understanding recurrence relations makes it easier to analyze code efficiency and computational requirements.
  3. By practicing common functions like sorting, searching, and analyzing their recurrence behavior, you can easily compute time complexity.

[Solution]Problem 36: Container with Most Water[Two Sigma]

Technology Made Simple • 39 implied HN points • 06 May 22
🕹 Technology Algorithms
  1. Maximizing the area of a container with water involves maximizing both its width and height, which leads to utilizing a technique like Two Pointers for an optimized solution.
  2. For the container problem discussed, starting with two pointers at the ends and progressively moving them towards each other to increase width helps in filtering out low width and height combinations.
  3. A key optimization technique known as 'Artem's Rule' states that if a > b, then a > all numbers lesser than b, which can be a foundational concept for various interview problem optimizations.

The 10 Most Popular Posts of the Palindrome in 2025

The Palindrome • 1 implied HN point • 23 Dec 25
🚌 Education Algorithms
  1. The most-read posts emphasize math and foundational CS for machine learning, covering topics like a mathematics roadmap, algorithmic analysis, graph theory, and practical skills such as coding on paper and representing graphs.
  2. A holiday promotion offers a 30% lifetime discount on the annual paid subscription, which unlocks paid-only content and helps fund more math and machine learning material for the community.
  3. Subscriber-count milestones will unlock community perks (mini-courses, a dedicated Manim animator, and a full-time writer), and the publication invites feedback while planning to expand and reinvest in 2026.

[Solution]Problem 35: 3 Sum[Netflix]

Technology Made Simple • 39 implied HN points • 29 Apr 22
🕹 Technology Algorithms
  1. Practice the skills mentioned in your interviews frequently to make problem-solving easier.
  2. Understanding the properties of numbers like knowing how values affect the sum can help in solving coding problems effectively.
  3. Sorting the input array can be crucial in solving problems where solutions need to be filtered based on certain properties of the input.

Idea behind Bit shifting [Math Monday]

Technology Made Simple • 39 implied HN points • 19 Apr 22
🕹 Technology Algorithms
  1. Understanding Binary Math is crucial for coding interviews. Practice is key for mastering bit shifting.
  2. Familiarity with Modular Arithmetic, Number Systems, and Recursion is important. They are foundational math skills for solving interview questions.
  3. Being able to identify when to use Mod function, transitioning between number bases, and coding recursion are critical for successful problem-solving.

✋ Newsletter #38: Me Too

Women On Rails Newsletter - International Version • 19 implied HN points • 03 Nov 22
🕹 Technology Algorithms
  1. The newsletter discusses a case of justice served in a #MeToo context, emphasizing the importance of identifying and addressing abnormal situations in professional environments.
  2. The community encourages creating safe spaces, advocating for victims of sexual violence, and providing support for legal processes.
  3. Recommendations are offered for joining women-centered Ruby communities, along with resources for building sustainable digital products and insights on improving team workflows.

My experience with the Google Foobar challenge

Technology Made Simple • 39 implied HN points • 27 Mar 22
🕹 Technology Algorithms
  1. Google Foobar challenge consists of multiple levels and is invite-only, offering a chance for an onsite interview at Google.
  2. The challenge is designed like an infiltration story with lengthy, complex questions that require googling concepts and filtering out irrelevant information to solve.
  3. Passing the first 3 levels is relatively easier, but the final 2 stages demand specific knowledge of high-level concepts and a well-thought-out game plan for success.

[Solution]Problem 30: Find Distance to nearest Exit[Google]

Technology Made Simple • 39 implied HN points • 25 Mar 22
🕹 Technology Algorithms
  1. Google coding challenges can be tricky and often require exploring optimal solutions beyond the obvious
  2. When solving problems involving distances in grids, consider using the concept of Manhattan Distance and graph structures to represent relationships between objects
  3. Choosing the best graph traversal algorithm is crucial; in cases like this problem where distances are equal and not weighted, BFS can be a simpler and more suitable choice compared to more complex algorithms like DFS