About Future Spaces
Future Spaces is a prediction and analysis platform that helps you understand what happened, what's happening, and what's likely to happen next across markets, events, and complex systems.
Beyond Context Windows
Most AI tools give the illusion of memory by stuffing conversation history into a context window. We take a fundamentally different approach: continual learning.
Traditional language models don't actually learn from their predictions. They process your messages, generate a response, and forget everything. The next time you ask, they start from scratch—relying entirely on whatever fits in their context window.
Our system is different. It evolves with each prediction trajectory, updating its understanding based on outcomes and new information. The model itself improves—not just the prompt.
The Context Window Trap
Standard LLMs face a fundamental limitation: as context grows, they either truncate important history or get confused by their own sprawling conversation. They never actually learn—they just pretend to remember.
True Model Improvement
Our approach uses continual learning to update the model weights themselves. Predictions get better over time because the model genuinely learns from each trajectory—not because we're feeding it more chat history.
What You Can Do
Future Spaces synthesizes information from prediction markets and real-world sources to deliver actionable analysis:
- ✦Understand complex events — Get clear breakdowns of markets, geopolitics, technology shifts, and more
- ✦Trace historical context — See how past events shaped the present and what patterns emerge
- ✦Make better predictions — Leverage improving models that learn from prediction outcomes
- ✦Connect the dots — Discover relationships between seemingly unrelated events and trajectories
Built for Iteration
Every prediction and analysis on Future Spaces can be refined. Add your own assumptions, explore alternative scenarios, and build on previous analyses. Your feedback directly contributes to improving the system's accuracy over time.
Powered By
General text generation, article analysis, and real-time information synthesis.
Continual learning predictions and trajectory modeling that improves over time.
A Note on Accuracy
While our continual learning approach improves prediction quality over time, no system is infallible. We recommend using Future Spaces as one input among many when making important decisions. Always verify critical information against primary sources.