Articles about Large Language Models in Technology & AI
Large language models get stuck in the past, and updating them is a nightmare. A new framework called MEMO offers a clever solution: a separate, dedicated "memory" model that teaches old LLMs new tricks without the cost or chaos.
Move your LLM app from a messy prototype to a production-ready system. This guide walks you through building a complete Langfuse observability pipeline, from tracing and prompt management to scoring and experiments.
Researchers have found the exact neurons that make LLMs refuse harmful requests. A new method called CNA can turn them off like a light switch, without damaging the model's performance.
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.