Research
Research before claims.
Primer is an active experimental research program.
We evaluate capabilities under frozen protocols, preserve negative results, and distinguish internal benchmarks from external validation.
The central question is narrow and testable: can an AI system acquire knowledge generated after its checkpoint is frozen, retain that knowledge, and apply it to problems it has never seen?
Method
Built to be tested.
Post-freeze
Test knowledge the model could not simply have memorized from its original training.
Verified
A generated answer is not automatically treated as knowledge.
Persistent
Learning should survive beyond a single interaction.
Measurable
Positive and negative experimental results both matter.
Program
Progress.
- Foundation
Measuring post-training learning
Completed - Acquisition
Novel knowledge acquisition demonstrated
Completed - Efficiency
Learning efficiency improved
Completed - Memory
Persistent knowledge demonstrated
Completed - Composition
Knowledge reuse demonstrated
Completed - Generalization
Expanding what Primer can learn
In progress - Next
Scaling and external evaluation
Upcoming
Current research areas
- Post-training learning
- Persistent knowledge
- Knowledge transfer
- Generalization
- Scaling
- Evaluation
Results published on this site come from internal research evaluations. External validation is ongoing.