Founder
Gregory Villines
Geometric information theory, applied topology, and edge intelligence — backed by a granted U.S. patent and a public body of research on SSRN.
The Practice
Structure as the instrument.
The through-line of the work is simple to state and hard to do: treat structure as the instrument. Most hard problems are not short of data — they are short of the right geometry to see the data in. Find that geometry and the answer tends to become obvious.
That conviction runs from a signals-intelligence lineage through a granted patent and into a working line of compression and inference systems.
Signals Lineage
From the signal to the structure.
Trained as a USAF signals-intelligence specialist, then working as an NSA network analyst — years spent pulling structure out of noisy, adversarial channels.
That discipline — assume the signal is hidden, assume the measurement is contested, and recover the structure anyway — is the same one applied today to markets, language models, and encryption.
Research Focus
Seven lines of inquiry.
Geometric Information Theory
Treating information as a structured object with shape, curvature, and topology — not just a count of bits.
Topological Data Analysis
Persistent homology and related tools to detect structure that survives noise and scale.
Labor-Market Econometrics
Measurement-integrity work on employment, credentialing, and workforce policy.
Compression & Tokenization
Learned tokenization and representation that pushes past conventional byte-pair limits.
LLM Inference Efficiency
KV-cache quantization and inference architecture for cheaper intelligence at scale.
Edge AI & IoT
Carrying capable models onto constrained devices at the edge of the network.
Encryption Architecture
Applied cryptographic design, anchored by a granted U.S. patent.
Applied Systems
Research that ships.
Glyph · Tokenization
A learned tokenization system compressing text past conventional byte-pair encoders — ≈ 9.1 characters per token.
Quark · Embedding
A compact embedding scheme for dense semantic representation under tight memory budgets.
nd‑kv‑quant · Open Source
Apache 2.0 KV-cache quantization via norm–direction decomposition — ≈ 4× compression near full precision, benchmarked on Qwen, Llama, and Mistral.
Edge-AI Prototype
A working prototype carrying inference onto constrained edge hardware.
Genesis · Cognitive Architecture
An experimental architecture for structured reasoning and memory.
FIG. 1 — Volumetric Helix Encryption · U.S. Patent No. 12,039,405 B1
U.S. Patent No. 12,039,405 B1 — Volumetric Helix Encryption (granted).
nd‑kv‑quant, Apache 2.0 — benchmarked on Qwen, Llama, and Mistral.
Public research body on SSRN spanning topology, econometrics, and energy systems.
USAF signals intelligence; NSA network analysis.
Engage
Start a conversation.
Whether it is a research collaboration, an acquisition question, or a hard problem you need looked at — send the details and you will get a direct response.