The Mistral 8x7b, aka Mixtral 8x7b, is an open-source implementation of the “Mixture of Experts model”, combining eight 7 billion parameter models for task-specific processing. While GPT-4 is rumored to use a similar architecture, it’s important to note that Mistral is not the first to employ this concept. The Mixture of Experts model, an older idea in AI, has seen a resurgence due to modern computational advances.

Despite its innovative approach, the high hardware demands of such models limit their widespread use. The AI industry is trending towards developing large, complex models and subsequently distilling them into more practical, smaller versions. Projects like OpenMoE also explore this concept, indicating a broader interest and application in the field.

Key Takeaways:

  1. Mixtral 8x7B as Open Source Mixture of Experts: This model demonstrates how multiple specialized networks can be integrated for efficiency and specialization.
  2. GPT-4 and Mixture of Experts Speculation: Rumors suggest GPT-4 might incorporate a Mixture of Experts architecture to enhance its capabilities.
  3. Mistral Not the Pioneer: While innovative, Mistral is not the first to implement the Mixture of Experts model, as evidenced by other projects like OpenMoE.
  4. Revival of an Established AI Concept: The Mixture of Experts model, though historical, is gaining traction with the advent of advanced computational technologies.
  5. Challenges in Accessibility and Future Trends: The need for significant computational power makes such models less accessible, and the AI field is moving towards creating and refining large, complex models into more user-friendly versions.

Reference video:

Play around with the Mixtral 8x7B model:

nateraw/mixtral-8x7b-32kseqlen – Replicate
MistralAI’s new 8x7B Mixture of Experts (MoE) base model for text generation