La IA local ya es igual de buena que la frontera

Summary

En este vídeo, el autor demuestra que los modelos de IA locales (en particular el Qwen 2.6 27B con variantes MTP) pueden ser tan efectivos como los modelos de frontera para el desarrollo de software complejo. Explica cómo configurar un entorno local, el uso de hardware adecuado, la importancia de no depender de 'one-shots' y por qué la metodología de desarrollo iterativo paso a paso (baby steps) es clave para evitar errores acumulativos. A través de la creación de un modelo 3D del sistema solar, ilustra cómo una buena comunicación con el agente y una arquitectura bien definida permiten obtener resultados profesionales de manera eficiente y local.

Topics covered

• Hardware y configuración local
• Backend para inferencia local

+4 more topics (full content when you follow the channel)

Transcript excerpt

Local models are just as good as frontier models. I already said it, go share on Twitter that Hola, Mundo is talking pure nonsense. But if you're still curious to know why I'm saying this, stay tuned to this video because I'm going to show you exactly how I'm using a local model to build software. We're going to go step by step, we're going to do the planning, we're going to separate this whole project by tasks, by modules, by files. We will also select the stack that we want to build and finally we will let the local agent with local artificial intelligence build it. So, the first thing we need to talk about is the hardware we're going to use for this test. In case you didn't know, artificial intelligence models have to run on the graphics card, specifically on the graphics card's VAM. If you don't do it that way, the inference speed will be, let's say, quite slow. So, if you want…