Most AI progress today is driven by scaling more parameters, more data, more compute. Elyana explores a different hypothesis: that intelligence can be enhanced through memory, causal reasoning, abstraction, mental simulation, concept formation, and cross-domain transfer working together as a unified cognitive system.
We're especially interested in feedback around:
How users think Elyana should balance reasoning vs speed.
Whether long-term memory makes AI more useful in real-world workflows.
What types of problems require causal understanding rather than simple pattern matching.
Where current AI systems fail because they lack a world model or common-sense reasoning.
If you've used Elyana, we'd love to know where it surprised you, where it failed, and what cognitive capability you believe AI is still missing today.
