… or any consensus algorithm that relies on an unstable equilibrium. In this post we explore the fundamental issue with the consensus algorithms that rely on unstable equilibrium, using the Avalanche family as an example. We mainly focus on the Slush, Snowflake, and Snowball algorithms that are the stepping stones…

The bare minimum. The majority of people coming to Rust have C/C++ background which allows them to easily transition into Rust parallelism since it is so similar. However, for many people coming from other languages, it is a challenge. In this post, we will walk through the standard Rust parallelism…

Rust, being a relatively new language, is still on its path to gaining wide support by IDEs. Most in our team use CLion for Rust development which is especially great for local debugging, alas it is not free. Since we are developing a blockchain it requires careful orchestration of the…

No, seriously, this time for real Coming to Rust from C++ and learning about lifetimes is very similar to coming to C++ from Java and learning about pointers. At first, it looks like an unnecessary concept, something a compiler should have taken care of. Later, as you realize that it…

Since we set out to solve programming, our initial goal is to figure out how computers can solve algorithmic problems. Recently, we published a great overview post on this — “Are we close to having machines solve TopCoder problems?” that described our approach. Today, we want to showcase our progress…

Machine learning is known for its difficulties with interpretability, or rather its absence. Which is an issue if your users have to work with the numeric output, like in the systems used in sales, trading or marketing. If the user’s interpretation of the ML output is wrong the actual metrics…

Or how to shoot yourself in the foot with a bazooka. Many of us frown upon the technical debt but generally, it is not a bad thing. Technical debt is an instrument which is justified when we need to meet some release deadlines or unblock a colleague. The problem with…

As I was going through some great Machine Learning books like ISL, ESL, DL I got very confused with how they explain MSE (Mean Squared Error) and its bias-variance decomposition. Bias-variance decomposition is extremely important if you want to get a really good grasp of things like overfitting, underfitting, and…