MrComputerScience.com
Blog For Marketing And Tech Nerds
This page collects a wide range of my best articles on artificial intelligence, programming, data science, deep learning, Java, Python, Rust, and the ever-evolving world of computer science. Continue reading to explore my projects, experiments, and long-form insights from years of building and learning in tech.
Ever feel like you understand the theory behind algorithms or programming but struggle to connect those ideas to real-world projects? That’s a common challenge. If you’ve ever wondered how concepts like neural networks, machine learning models, or code optimization actually come together in practice, you’re in the right place. Let’s figure it out together.
Whether you’re diving into Python for data analysis, experimenting with AI frameworks, studying how software systems scale, or just curious about the latest developments in computer science, this collection is designed to help. I’ll share practical tutorials, experiments, and discoveries from years of exploring the tech landscape hands-on.
Scroll down to browse my articles across AI, programming, and data science and start learning concepts you can truly apply.
WASI Preview 2's component model fundamentally changes how WebAssembly modules are composed, linked, and instantiated at the edge. Instead of monolithic blobs that carry all their dependencies, …
Continue Reading about What WASI Preview 2’s Component Model Changes for Edge Cold Starts →
Rust's async runtime gives you more control over scheduling, memory layout, and I/O handling than Go or most C++ async frameworks, but that control comes with complexity. Getting sub-100-microsecond …
Continue Reading about Optimizing Rust Async for Ultra-Low-Latency Networking →
NISQ (Noisy Intermediate-Scale Quantum) devices cannot run Shor's or Grover's algorithms at meaningful scale today, let alone more complex fault-tolerant algorithms. The core challenges are qubit …
Continue Reading about Fault-Tolerant Quantum Algorithms Beyond Shor’s on NISQ Devices →
A mutex is owned by exactly one thread and must be released by the thread that acquired it. A semaphore is a counter with no ownership: any thread can signal it and any thread can wait on it. Using a …
Continue Reading about Mutex vs Semaphore: When the Wrong Choice Deadlocks You →
The ABA problem occurs when a thread reads a value A from shared memory, gets preempted, another thread changes the value to B and then back to A, and the first thread resumes and incorrectly …
Continue Reading about The ABA Problem in Concurrent Programming Explained →
Effect handlers and monads both manage side effects in functional programs, but they solve the composition problem differently. Monads require explicit lifting and threading through every function in …
Continue Reading about Effect Handlers vs Monads: When to Use Which →
