Deep Dives

which have pervaded nearly every facet of our day by day lives are autoregressive decoder models. These models apply compute-heavy kernel operations to churn out tokens one after the other in a way...

: Overparameterization, Generalizability, and SAM The dramatic success of recent deep learning — especially within the domains of Computer Vision and Natural Language Processing — is built on “overparameterized” models: models with good enough parameters to memorize the training data...

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...