The hottest Optimization Substack posts right now

And their main takeaways
Category
Top Technology Topics

The mathematics of optimization for deep learning

The Palindrome • 2 implied HN points • 12 Feb 24
🕹 Technology Mathematics Machine Learning Optimization
  1. The post discusses the mathematics of optimization for deep learning - essentially minimizing a function with many variables.
  2. The author reflects on their progression since 2019, highlighting growth and improvement in their writing.
  3. Readers can sign up for a 7-day free trial to access the full post archives on the topic of math and machine learning.

Hot Topics #21 (Mar. 17, 2023)

The Merge • 19 implied HN points • 17 Mar 23
🕹 Technology AI ML Optimization Speech Synthesis Robotics
  1. GPT-4 is a new large-scale model by OpenAI that can accept image and text inputs to produce text outputs.
  2. PaLM-E is an embodied multimodal language model that incorporates real-world sensor data into language tasks.
  3. Meta-black-box optimization can discover effective update rules for evolution strategies through meta-learning.

Math for Computer Science [Math Mondays]

Technology Made Simple • 59 implied HN points • 26 Apr 22
🕹 Technology Machine Learning Mathematics Software Development Statistics Optimization
  1. Focus on Calculus for software development: Understand precalc topics like functions, transformation, and algebra well.
  2. Importance of Probs and Stats: Learn to think in a Bayesian context, focus on probabilistic thinking.
  3. Value of Linear Algebra: Grasp foundational concepts, computational side less important for traditional software development.
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Power Function in logarithmic time [Technique Tuesdays]

Technology Made Simple • 39 implied HN points • 09 Aug 22
🕹 Technology Programming Algorithms Interviews Tutorials Optimization
  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.

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 Coding Optimization Algorithms Data Structures Tech Education
  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.

How to Create a Killer Landing Page for Your SaaS Product

Friends Of SaaS • 14 implied HN points • 09 May 23
💼 Business Marketing Design Tools Optimization Content Marketing
  1. To create a killer landing page for your SaaS product, focus on first impressions like design, headlines, and compelling content.
  2. Include social proof like customer testimonials and showcase to influence others' decisions.
  3. Utilize tools like landing page generators, A/B testing, and email marketing tools to enhance your landing page and optimize conversions.

[Solution]Problem 38: Power Function[Stripe]

Technology Made Simple • 39 implied HN points • 20 May 22
🕹 Technology Math Logic Optimization Recursion
  1. The problem focuses on implementing a power function without using built-in functions, showcasing the importance of base mathematical operations.
  2. Starting with a simple brute-force solution can lead to more efficient solutions and impress interviewers by demonstrating a structured problem-solving approach.
  3. Optimizations can be made by leveraging mathematics to improve the linear time complexity of the solution.

Problem 38: Power Function[Stripe]

Technology Made Simple • 39 implied HN points • 19 May 22
🕹 Technology Math Logic Optimization Recursion
  1. The post discusses implementing a power function that calculates x raised to the power n without using built-in functions, focusing on math, logic, optimization, and recursion.
  2. Examples of the power function implementation are provided with input-output pairs to demonstrate how it should work.
  3. There is a special request for feedback and sharing of topics for future focus, along with encouragement to explore additional content and subscribe for further tips and assistance.

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

Technology Made Simple • 39 implied HN points • 06 May 22
🕹 Technology Coding Finance Problem Solving Optimization 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.

Problem 2: Find all occurrences of Substring Solution [Microsoft] (Example of Solutions in Paid Version)

Technology Made Simple • 39 implied HN points • 23 Aug 21
🕹 Technology Coding Algorithms Hashing Optimization
  1. When solving problems, start with a simple solution even if it's not optimal. It's better to have a working brute-force solution than no solution at all.
  2. Optimizing code involves identifying and eliminating redundant parts. For instance, in string matching problems, consider using techniques like hashing to improve efficiency.
  3. The Rabin-Karp algorithm is a rolling hash function used for string searching. It involves using hashes to compare substrings efficiently, reducing false positives and improving overall performance.

Why does gradient descent work?

The Palindrome • 5 implied HN points • 06 Apr 23
🔬 Science Mathematics Machine Learning Optimization
  1. In machine learning, gradient descent is used to find local extrema by following the direction of steepest ascent or descent.
  2. Understanding derivatives helps us interpret the rate of change, such as speed in physics.
  3. Differential equations provide a mathematical framework to understand gradient descent and optimization, showing how systems flow towards equilibrium.

[Solution]Problem 22: Positive Pairs meeting conditions[Jane Street]

Technology Made Simple • 19 implied HN points • 27 Jan 22
🕹 Technology Coding Math Optimization Algorithms
  1. The problem involves finding pairs of positive integers that satisfy specific conditions involving addition and XOR operations.
  2. Understanding binary representation and logical operators like XOR can lead to more optimal solutions for certain problems.
  3. Mathematical reasoning and logical analysis can help in optimizing solutions and reducing time complexity, especially when dealing with binary operations.

[Solution]Problem 19: Help Couples sit together [Spotify]

Technology Made Simple • 19 implied HN points • 06 Jan 22
🕹 Technology Recursion Combinatorics Optimization
  1. Creating a brute force solution can guide towards an optimal solution, but in interviews, it's better to showcase understanding and move on to more effective approaches
  2. Greedy algorithms are straightforward and choose the best option at each step, making them applicable for optimization problems like arranging couples
  3. Optimal algorithms, like the greedy approach, can be efficient because they make choices based on immediate benefit, even though they may overlook long-term gains

[Solution]Mastermind Code Decoding [Facebook]

Technology Made Simple • 19 implied HN points • 10 Dec 21
🕹 Technology Algorithms Programming Interviewing Optimization
  1. The problem involves a two-player game called Mastermind where one player must guess the other player's secret code based on feedback provided after each guess.
  2. Implementing a brute force solution as a first step can provide a structured approach, help avoid freezing up during interviews, give hints for optimization, and showcase organization.
  3. Optimizing brute force solutions involves narrowing down the pool of possible solutions based on the constraints provided in the problem, which can significantly reduce the search space.

Five years of progress in GPTs

Artificial Fintelligence • 3 HN points • 29 Mar 23
🕹 Technology Language Models Research Innovation Optimization
  1. Focus on the evolution of GPT models over the past five years, highlighting key differences between them.
  2. Explore the significant impact of large models, dataset sizes, and training strategies on language model performance.
  3. Chinchilla and LLaMa papers reveal insights about the optimal model sizes, dataset sizes, and computational techniques for training large language models.

I’m a Senior Software Engineer. What Will It Take For An AI To Do My Job?

Am I Stronger Yet? • 3 HN points • 20 Apr 23
🕹 Technology AI Software Engineering Memory Optimization Puzzles
  1. Current AI systems are still lacking critical cognitive abilities required for complex jobs.
  2. AI needs improvements in memory, exploration, puzzle-solving, judgement, clarity of thought, and theory of mind to excel in complex tasks.
  3. Addressing these gaps will be crucial for AI to reach artificial general intelligence and potentially replace certain human jobs.

AI-assisted Ant Colony Optimization with GPT-4 for Solving the Traveling Salesman Problem

Rustic Penn • 2 HN points • 28 Apr 23
🕹 Technology AI Optimization Artificial Intelligence Algorithms Data science
  1. The article explores the synergy between GPT-4 and Ant Colony Optimization for solving the Traveling Salesman Problem.
  2. GPT-4 showcases its potential in guiding and assisting the implementation of the Ant Colony Optimization algorithm.
  3. The combination of AI like GPT-4 with nature-inspired algorithms can lead to innovative and efficient problem-solving solutions.

Server Driven UI, Personalization, Runtime Bundling

Microfrontends, Architecture and Trade-offs • 0 implied HN points • 14 Mar 23
🕹 Technology UI Personalization Mobile Web Optimization Architecture
  1. Server Driven UI involves having the server instruct on how to render the UI for consistency across platforms.
  2. Server Driven UI can enable faster change cycles for mobile apps by separating rendering into a generic container.
  3. Runtime Bundling in a dynamic web page can be explored to optimize performance by creating bundles on the fly.

[Solution]Problem 17: Minimum cost of painting N houses up to K different colors.[Facebook]

Technology Made Simple • 0 implied HN points • 23 Dec 21
🕹 Technology Coding Algorithm Dynamic Programming Optimization Complexity
  1. The problem involves minimizing cost while ensuring no neighboring houses have the same color. This can be represented using a matrix.
  2. Brute force can be initially used to explore all combinations, but dynamic programming is a more efficient approach in this scenario. Dynamic programming optimizes calculations by avoiding unnecessary computations.
  3. By utilizing dynamic programming, we can efficiently calculate the minimum cost of painting the houses with different colors. This method involves maintaining a matrix cache to track the costs and ensure the color constraint is met.

Why you should implement Evolutionary Algorithms in your Machine Learning Projects

Technology Made Simple • 0 implied HN points • 22 Dec 21
🕹 Technology Machine Learning Deep Learning Artificial Intelligence Optimization
  1. Evolutionary Algorithms are underutilized in Machine Learning Research and can be powerful tools to solve complex problems.
  2. Evolutionary Algorithms provide flexibility by not requiring differentiable functions, making them suitable for a variety of real-world optimization problems.
  3. Evolutionary Algorithms can outperform more expensive gradient-based methods, as demonstrated in various research projects including Google's AutoML-Zero.

DiffGrad : Is it the right optimization method for training your CNNs?

Machine Learning Diaries • 0 implied HN points • 25 Sep 23
🔬 Science Optimization Machine Learning Neural Networks Research
  1. Optimizing neural networks with DiffGrad may prevent slow learning and jittering effects in training
  2. DiffGrad adjusts learning rates based on gradient behavior for each parameter, leading to improved optimization
  3. Comparisons suggest that DiffGrad outperformed Adam optimizer in terms of avoiding overshooting global minima