InthecinderellaprojectbyShalendra gaur·8h agoYour LLM agent re-reads its history every step. We measured what that costsThe difference was not the model. It was what the model was handed at each step.
Varun Rajput·2d agoWhy May a Model Get Slower on a Bigger Machine?When two libraries both assume they own every CPU core, adding cores can make things slower. Here’s why, and how to spot it.A response icon1A response icon1
Mehmet Özgen ÖZDOĞAN·3d agoLocal AI Is Getting Stronger: Distributed Inference, Agent Concurrency, and the Projects Worth a…A year ago, “local AI” mostly meant one model on one laptop, great for privacy and tinkering, awkward for anything with real concurrency…A response icon1A response icon1
Priya Srivastava·4d agoAI Upskilling Day 1: How LLMs Actually Run : Tokens, Weights, and GPUs ExplainedMotivation :A response icon1A response icon1
Lyndon Carlson·6d ago“Plan My Whole Year”: The Request That Made Us Build Our Own ModelWeek one of the AWS Startups Custom-Model Inference Fellowship: the problem, the plan, and how we’ll know if it worked.A response icon1A response icon1
InL’IA en langue françaisebyPatrick Meyer·Nov 3Quelle IA locale pour votre machine ?Ollama, LM Studio, Magnitude & Lemonade : à quoi sert chaque outil, comment savoir si votre machine peut suivre, et à quelle vitesse…A response icon1A response icon1
InStackademicbyFaisal haque·Nov 3Want to Run Open-Source AI in Production? Start HerePick one useful job for an open model, then work out what it will take to run it reliably.A response icon1A response icon1
Sean Fraser·Nov 1What decades of networking and distributed systems engineering can teach us about AI inferenceThe models are new. Many of the constraints are familiar.
Chaesang Jung·Nov 12026 Cloud Solutions Report, #10: Inference Infrastructure (2) — Token SupplySold out before it is built, and 95% unused once rented. Reading the token factory’s P&L has become the buyer’s job.
