Deep Dives

an actual issue when coping with very large datasets. What I mean by “very large” is data that exceeds the capability of a single machine’s RAM.  A few of the key friction points Pandas...

is Nikolay Nikitin, PhD. I'm the Research Lead on the AI Institute of ITMO University and an open-source enthusiast. I often see a lot of my colleagues failing to seek out the time...

, the move from a standard data warehouse to Data Mesh feels less like an evolution and more like an identity crisis. At some point, every little thing works (possibly “works” is a stretch, but...

who has written a children’s book and released it in two versions at the identical time into the market at the identical price. One version has a basic cover design, while the opposite...

that reads your metrics, detects anomalies, applies predefined tuning rules, restarts jobs when essential, and logs every decision—without you watching loss curves at 2 a.m. In this text, I’ll provide a light-weight agent designed...

chain is a goal-oriented network of processes and stock points that delivers finished goods to stores. Imagine a luxury fashion retailer with a central distribution chain that delivers to stores worldwide (the USA, Asia-Pacific, and EMEA) from a...

Introduction are currently living in a time where Artificial Intelligence, especially Large Language models like ChatGPT, have been deeply integrated into our each day lives and workflows. These models are able to quite a...

is an element of a series about distributed AI across multiple GPUs: Part 1: Understanding the Host and Device Paradigm Part 2: Point-to-Point and Collective Operations (this text) Part 3: How GPUs Communicate Part 4: Gradient Accumulation...