About
The Inference Weekly
AI research moves fast. We slow it down for you. Every article is a deep dive into a research paper, a system, or an idea worth understanding — written for engineers who want to build on what's happening at the frontier.
Mission
Transform cutting-edge AI research into clear, practical, and engaging articles for engineers, researchers, and technology enthusiasts. We believe great research communication accelerates progress.
Topics We Cover
LLMs
Large language models, scaling laws, and foundation models.
Agents
Autonomous AI agents, tool use, and multi-agent systems.
Vision
Computer vision, multimodal models, and image generation.
Robotics
Embodied AI, robot learning, and physical intelligence.
Reasoning
Chain-of-thought, formal reasoning, and planning.
Infrastructure
Training at scale, inference optimization, and tooling.
Benchmarks
Evaluations, leaderboards, and capability measurements.
Our Principles
Content is the hero.
Every design decision exists to serve the reader. No noise.
Accuracy over accessibility.
We never dumb things down. We find better explanations.
Engineers first.
We write for people who will implement, not just observe.
The Team
The people behind every deep dive.
Harshit Sinha
EditorML engineer and researcher specialising in deep learning architectures, training dynamics, and model evaluation. Translates dense methodology sections into intuitions that actually stick — with the maths kept intact.
Rishabh Tripathi
EditorSoftware engineer and AI researcher with a focus on LLMs, inference optimisation, and systems design. Writes about the engineering decisions behind frontier models — the tradeoffs that don't make the abstract but matter most in practice.
Want to contribute?
We publish deep dives from engineers and researchers building at the frontier.
Get in touch