Why We Name LignumAI Versions After Wood Species
At LignumAI, our model versions are named after wood species — progressing from very soft to very hard. It’s more than a theme: it’s a practical way to describe how our intelligence layers evolve over time.
In nature, wood begins light and flexible, then becomes denser and stronger as the structure matures. In engineering terms, density is often a useful proxy for how much load a material can carry and how stable it remains under stress. Our models follow a similar arc: early versions prioritize adaptability and learning, while later versions emphasize precision, reliability, and “structural” consistency.
From Softwood to Hardwood: What It Means for Our Models
Each wood species in our naming convention represents a milestone — not just “bigger,” but more refined: better at handling edge cases, more stable across real-world data, and more dependable for production-grade use.
- Soft & Lightweight — quick to iterate, highly flexible, excellent for exploration and early learning.
- Medium Density — stronger generalization, better consistency, improved performance on mixed-quality inputs.
- Hard & Dense — high precision, robust behavior under complexity, dependable repeatability for demanding workflows.
Version 1: Balsa
Our first release is called Balsa — a wood known for being exceptionally light and easy to shape. It’s a fitting name for a first model: fast to adapt, forgiving during experimentation, and surprisingly capable for its “weight.” Balsa is where we learn quickly: we test, measure, and refine with speed.
A Few Examples of the Species Ladder
Here are a few species that illustrate the progression — along with what they represent in our model roadmap:
Balsa (Very Low Density)
Model meaning: rapid learning, high flexibility, exploration mode.
Why it fits: lightweight and easy to work with — ideal for early iterations.
Pine (Low to Medium Density)
Model meaning: dependable baseline, practical generalization, strong “everyday” performance.
Why it fits: common in construction framing — versatile and reliably structural.
Cedar (Medium Density, Naturally Resilient)
Model meaning: improved stability, better resistance to messy inputs and edge cases.
Why it fits: known for durability and resistance — built to last in imperfect environments.
Oak (High Density)
Model meaning: precision, repeatability, stronger reasoning “load-bearing.”
Why it fits: dense and strong — the kind of wood you trust for long-term structural work.
Ebony (Very High Density, Rare)
Model meaning: our most demanding inference tier — reserved for the hardest problems.
Why it fits: exceptionally hard and rare — used when the requirements are uncompromising.
“Like wood, intelligence is grown — not rushed. Our naming convention is a reminder that strength comes from iteration, density comes from learning, and reliability comes from time.”
As LignumAI progresses through this ladder, you’ll be able to understand — at a glance — whether a given version is meant for experimentation, balanced production use, or high-precision workloads.