Shrijith Venkatramana, building git-lrc, explains that sequence transduction—transforming one sequence into another—was the original problem that led to modern large language models. Early neural netw…
Shrijith Venkatramana, building git-lrc, explains the evolution of LLM evaluation metrics from BLEU to BLEURT and COMET. BLEU, introduced in 2002, measures n-gram overlap and correlates with human jud…
Shrijith Venkatramana, building git-lrc, explains that synthetic data has become a key ingredient for scaling modern large language models. By 2022, frontier AI labs had exhausted much of the public h…
Google's Tensor Processing Units (TPUs) are specialized chips designed for neural network matrix multiplications, differing fundamentally from GPUs. Unlike GPUs, which evolved from graphics rendering,…
Shrijith Venkatramana, building git-lrc, explains the three phases of post-training that transform pretrained LLMs into helpful assistants. The process starts with supervised fine-tuning (SFT) on cura…
Shrijith Venkatramana, building git-lrc, explains that modern AI systems rely on a two-step recipe: generative pre-training followed by discriminative fine-tuning. Pre-training involves predicting the…
Shrijith Venkatramana, a developer building git-lrc, explains that NVIDIA Collective Communications Library (NCCL) is the critical infrastructure enabling multi-GPU training of large language models. …
Shrijith Venkatramana, developer of git-lrc, explains how kernel fusion reduces memory bandwidth bottlenecks in LLM inference. By combining multiple GPU operations into a single kernel, intermediate d…
Shrijith Venkatramana, developer of git-lrc, explains how prompt caching in LLMs can dramatically reduce latency and cost by reusing internal representations from previous requests. The technique cach…
Shrijith Venkatramana, building git-lrc, explains KV Cache, a key optimization in LLM inference that avoids recomputing key-value pairs for previous tokens during autoregressive generation. By caching…
Shrijith Venkatramana, an AI engineer building the code reviewer git-lrc, argues that theorem prover Lean4 could solve a critical flaw in large language models: their inability to guarantee correctnes…
Shrijith Venkatramana built Gemini Nano Book Lab, a Chrome extension that uses the browser's built-in Prompt API to answer questions about a 1.25-million-character memoir entirely on-device. The exper…
The article, written by Shrijith Venkatramana, discusses the debate over whether developers need to read AI-generated code, arguing that while reading every line is no longer necessary for many tasks,…