Articles about Large Language Models in Technology & AI
Large Language Models are powerful but huge. Let's walk through a practical, hands-on guide to shrinking them with post-training quantization techniques like FP8, GPTQ, and SmoothQuant, and see which one wins.
Training AI on long sequences is painfully slow due to attention costs. Nous Research's Lighthouse Attention offers a clever, training-only solution that speeds things up by 1.7x without sacrificing quality.
Ever wonder how we get powerful AI models that don't require a supercomputer to run? The secret is a process called distillation, where massive "teacher" models train smaller "student" models. Let's break down how it works.
Are your LLM API bills getting out of hand? Learn how to use NadirClaw, a smart routing layer, to automatically send simple prompts to cheap models and complex ones to powerful models. This hands-on guide will walk you through cutting costs without sacrificing performance.
Stop treating your LLM like a black box. Let's walk through how to build a modular, skill-based agent system in Python—think of it as an operating system for your AI.
Ever wonder how AI models learn to be helpful and not just... weird? We'll walk you through the entire process, from basic instruction-following to advanced reasoning, using tools you can run yourself.
Tired of LLM outputs that are *almost* right? Let's move beyond basic prompting and look at five specific, systematic techniques that will give you the reliable, structured, and production-ready results you actually need.
Ever feel that awkward pause when talking to a voice assistant? Sakana AI's new KAME architecture aims to fix that by letting AI speak instantly while a powerful LLM refines the answer in real time. It's the best of both worlds: speed and smarts.
If you've ever watched a progress bar crawl during AI training, you know the pain. NVIDIA researchers have tackled the single biggest bottleneck with a clever technique that offers a huge speedup without sacrificing quality.
Large Language Models are brilliant but forgetful. We'll show you how we moved beyond simple search to build an RL-powered agent that learns how to find the right information, making AI answers smarter and more accurate.
LoRA is a go-to for efficient fine-tuning, but it has a hidden flaw. We break down why it struggles to learn new facts and how a simple fix, RS-LoRA, can solve the problem.
We've all seen the impressive AI agent demos, but how do we separate real capability from clever marketing? Let's talk about the seven key benchmarks that truly test an agent's ability to reason, code, and operate in the real world.