Predicting the Future Everyone claims they can’t predict the future. But mathematically, we can do better than guessing. The real problem isn’t the lack of predictive tools, it’s that most people never learned to use them. Let’s say we’re trying to predict if it’ll rain tomorrow. Last year, during this same month it rained 5 out of 30 days. A simple way to calculate the probability is by dividing the rainy days by the non-rain days: ...
Scheduling is an interesting optimization problem that we encounter every day. You schedule things like brushing your teeth, driving to work, and eating a meal, whether consciously or subconsciously. I’m sure most people (me included) don’t care to fully optimize their personal schedule in favor of adding a buffer between tasks. Someone who is trying to optimize their schedule is in for a monumental task. This type of scheduling problem is similar to an NP-hard problem in computer science, sometimes called the “Job-Shop Scheduling” problem. NP-hard problems are problems in which new inputs increase complexity combinatorially. In other words, adding a new task to your schedule would greatly increase the time required to fully optimize it. And that is the key piece of information here: fully optimize. What benefit do you actually get from having the most streamlined schedule if you have to schedule 2 hours a day optimizing your schedule tomorrow? ...
Caching involves storing frequently accessed data in a temporary storage location to improve performance and reduce the need to access slower storage systems. Deciding when to evict items from the cache when it reaches capacity is a key challenge. If important items are removed, performance can degrade. Some common cache eviction strategies are: Least Recently Used (LRU): Removes items accessed the longest time ago. Least Frequently Used (LFU): Removes items that have been accessed the least number of times. First in First Out (FIFO): Removes the items added the longest time ago. As a real-world example, a library “caches” books at the front that are frequently requested, so that patrons can access them quickly without having to wait for the book to be retrieved from the shelves. ...
Note: The following post is not financial advice. It is for informational purposes only. Popularity of Crypto The following data, primarily from 2024, provides perspective on crypto’s popularity: Global Crypto Adoption (2025): Users, Rates & Country Data $3.5 trillion estimated crypto market value. 9.9% Crypto adoption rate globally. Over 13k cryptocurrencies. Bitcoin has 40% of the market share in Crypto. Especially considering Bitcoin’s impressive adoption, why doesn’t it serve as a reliable currency or investment? For a currency, broad acceptance and stability are essential, but volatility remains a major issue. As an investment, it should have economic value, yet it lacks intrinsic value. ...
Static Site Generators (SSGs) pre-generate all site pages at build time, producing plain HTML files that load almost instantly for users because there is no need for server processing. In contrast, Server-Side Rendering (SSR) renders each page on demand with every user request, which requires a running server (of course) and will lead to slower load times when the page isn’t cached. To add further contrast, Client-Side Rendering (CSR) usually causes the slowest initial load time because even when a page is cached, all dynamic content will need to be fetched and rendered by the client’s (your) computer. ...