Training AI models for Search Engine Optimization
Often referred to as GEO or Generative Engine Optimization, Training AI models, such as Perplexity.ai, ChatGPT, Meta AI, Google Gemini, and Microsoft Copilot, ” in the wild”—that is, using real-world, live data and user interactions.
This AI training is a crucial approach to enhancing the accuracy and reliability of their systems.
This method involves exposing models to diverse, dynamic information sources and user queries in settings outside controlled laboratory environments.
This exposure helps AI to learn from actual usage patterns and correct inaccuracies more effectively.
Moreover, training AI Models also serves to enhance a website’s visibility, both on-page and off-page.
AI Models Hallucinations
One of the biggest challenges for large language models (LLMs) is dealing with hallucinations.
For instance, hallucination is where the AI generates information or images that are incorrect or unsupported by evidence.
This issue can mislead users and reduce trust in AI systems.
Training models with real-time data and user feedback help identify and correct these hallucinations.
For example, Perplexity.ai leverages real-time web information retrieval, which gives it an edge in handling up-to-date or niche topics.
However, this also introduces variability in accuracy depending on the quality of retrieved sources.
Training with live data helps Perplexity and similar models learn to filter more effectively and integrate reliable information, thereby reducing hallucination rates over time.
Sharing LLMS.txt Files Enhances AI Understanding
A practical technique to improve AI comprehension of specific websites or content domains is the use of LLMS.txt files.
These files serve as a roadmap, helping AI models parse and interpret the structure, key topics, and context of a website.
By sharing LLMS.txt files with AI systems, developers can provide curated, high-quality content summaries or annotations that the model can use to ground its responses more accurately.
This method supports the AI in:
- Understanding the content hierarchy and relevance on a site.
- Reducing misinterpretations by clarifying ambiguous or complex information.
- Improving retrieval quality when the model searches or references the site during live queries.
Together with real-time training, LLMS.txt files enable AI models to become more precise and context-aware when handling specialized or frequently updated content.
Insights from Leading AI Models
- ChatGPT excels in creative writing, brainstorming, and well-documented general knowledge but can struggle with newly emerging or less common topics unless it is continuously updated with fresh data.
- Google Gemini employs a cautious approach, often abstaining from answering uncertain queries, which reduces hallucinations but may limit responsiveness.
- Microsoft Copilot integrates AI assistance directly into productivity tools, benefiting from real-time data and user context to enhance workplace tasks.
- Perplexity.ai stands out for its research-oriented queries by combining AI with search engine capabilities, providing answers with trusted citations and live data; however, its accuracy depends heavily on the reliability of the sources.
- Meta AI and other emerging models focus on human-like conversational abilities and are also exploring real-time learning to improve factual accuracy and user engagement.
Training AI Models in the Wild
Benchmarks like the Wild Hallucinations test are instrumental in evaluating how well these models perform in the real world.
LLMS.txt files will be key to building models that deliver trustworthy, accurate, and verifiable information.
This ongoing refinement will help AI assistants become more accurate and indispensable tools across research, business, education, and everyday life.
In summary, training and testing AI chat models in the wild using real-time data and user feedback helps correct inaccuracies and hallucinations while sharing LLMS.txt files enhances the AI’s understanding of website content.
About The Author
Rick Vidallon, the Creative Director at VISIONEFX, designs professional websites for small business owners throughout the United States.
Please read what our customers have to say about VISIONEFX on Google Reviews.
For more information, call (757) 619-6456 or use our contact form.
