Another DeepSeek Moment

Two Minute Papers

Resumen

DeepSeek's Flash model has received an astonishing update, demonstrating dramatic performance improvements, in some cases, more than sevenfold. What's even more remarkable is that this new Flash model not only surpasses its previous version but also outperforms DeepSeek's larger 'pro' model, despite maintaining the same underlying architecture and size. The secret lies in 'post-training,' a crucial step that teaches the model how to effectively use its existing knowledge and strategies. This powerful open-source model is freely available for download, allowing users to run it locally, and highlights the incredible potential of open science to bring advanced AI capabilities to everyone. The video's host emphasizes that if this pace continues, we could soon see billion-dollar-level AI accessible on consumer hardware, underscoring the revolutionary impact of making knowledge available to all.

Capítulos

  1. 0:00Deep Seek 2: Rendimiento increíble
  2. 0:42La
  3. 1:52El poder del post-entrenamiento
  4. 3:45La promesa del código abierto
  5. 4:31Lambda: Herramienta para IA

Temas tratados

  • DeepSeek Flash Model Performance
  • The Role of Post-Training in AI

+6 temas más (contenido completo al seguir el canal)

Extracto de la transcripción

It is simply incredible what just happened. Deep Seeks 2 latest AI systems appeared just about 3 months ago and the quicker flash model is getting an update already and this is unbelievable. I don't even know where to start. One, the new flash model is way better than the previous one. Many of these results more than doubled. One went 7x in just one revision, just a bit after the original release. Is this real life? And two, it gets better. Look, it not only beats the previous flash version, but also beats the pro version that is about five times larger. I mean, what? We often say that benchmarks are not everything and these are not even all of them. Yes, but a change this huge cannot be ignored. So what happened? How did they do this black magic? New model that was trained longer? Nope. The underlying model architecture and size is the same. So what changed? Excuse me. Is this some kind…