Knowledge Cutoff
Knowledge cutoff is the date after which an AI model has no training data, affecting what information it can reference without real-time retrieval.
Definition
Knowledge cutoff refers to the point in time when an AI model's training data ends. For example, if a model has a knowledge cutoff of January 2024, it won't have information about events after that date unless it uses RAG or browsing capabilities. This affects how AI systems cite and reference your content.
Why It Matters
Content published after an AI's knowledge cutoff won't be in its base knowledge. However, RAG-enabled systems can still retrieve and cite recent content. Understanding this helps you strategize content timing and updates.
How to Test with TestMyGEO
TestMyGEO checks whether your content is within major AI models' knowledge cutoffs and assesses RAG-accessibility for newer content.
Best Practices
- Create evergreen content that remains relevant
- Update content regularly to stay current
- Ensure content is accessible to RAG systems
- Build authority before major AI training updates
- Focus on timeless expertise alongside timely content
Common Mistakes to Avoid
- Relying only on time-sensitive content
- Not updating content after knowledge cutoffs
- Blocking AI crawlers from accessing new content
Frequently Asked Questions
Will AI cite my new content?
Yes, if the AI uses RAG (like Perplexity or ChatGPT with browsing). Base models without retrieval can only cite content from before their cutoff date.