Track which assets LLMs are recommending to the public in real-time
A data platform analyzing systematic biases in AI investment recommendations
Discover how large language models like ChatGPT show systematic biases towards certain stocks, creating unique investment opportunities through "hallucination yield" - the measurable premium LLMs assign to specific companies.
AI Model Opinions
Live data showing what different AI models think about stock returns
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HYPERSTITION
Hyperstition, a term coined by Nick Land and Mark Fisher, describes ideas or narratives that become real through their widespread belief and dissemination. It's a blend of "hyper" (beyond or above) and "superstition," suggesting a belief system that, through its very existence, shapes reality.
Essentially, hyperstitions are self-fulfilling prophecies or beliefs that, when widely adopted, can cause their own manifestation.
LLM investment recommendations may function as hyperstitions—the more these AI systems promote certain assets, the more likely those recommendations become reality through collective belief and action.
Top AI Recommendations
Aggregated investment recommendations from all AI models
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Detailed Analysis Pages
Deep dive into individual assets with comprehensive AI model analysis, sortable data tables, and historical trends
Tesla
TSLAElectric vehicle and clean energy company analysis
Bitcoin
BTCWorld's largest cryptocurrency investment analysis
NVIDIA
NVDALeading AI and graphics processing company analysis
More detailed analysis pages coming soon for additional assets
How It Works
Our platform systematically analyzes LLM responses to identify investment biases and market premiums
DATA COLLECTION
Periodically query multiple LLM services about investment recommendations and stock preferences
ANALYSIS
Compile responses into trending reports and identify systematic biases and preferences
INSIGHTS
Access data through our API and charting tools to understand LLM market premiums
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Important Legal Disclaimer
This is not financial advice and is only for research purposes. The information provided should not be used for financial decisions. Use at your own risk - we offer NO warranty regarding accuracy or reliability.