RESEARCH PROGRAM // KNOLINK LABS

Foundations of
Machine Intelligence.

We explore learning algorithms, inference topologies, developer tools, and the infrastructure required to make intelligent systems reliable, deterministic, and computationally lean.

4 ACTIVE STREAMS3 REPOSITORIESOPEN COLLABORATION
01 — DOMAINS OF INQUIRY

Active Research Streams

FUNDAMENTAL INQUIRY // SOFTWARE PROVING GROUNDS

[01]PRAXIS // SELF-PLAY

Strategic Agent Learning & Deep Search

Investigating how capable strategic behavior emerges from autonomous feedback loops, deep tree search algorithms, and dual-head policy/value networks in competitive environments.

TECHNICAL VECTOR
Parallel Monte Carlo Tree Search rollouts with neural priors
Asynchronous experience replay buffers and value stabilization
Emergent heuristic representation without hand-crafted features
[02]APOLEMIA // RUNTIME

Dynamic Activation Sparsity & Kernel Topologies

Moving beyond monolithic compute paradigms. We research mathematical kernels and dynamic routing layers where only task-relevant parameter subsets fire during inference, reducing execution energy by up to 88%.

TECHNICAL VECTOR
Dynamic routing gate networks operating in < 0.1ms
Custom INT8 and INT4 tensor kernel compilation
KV-cache retention across distributed multi-cluster boundaries
[03]ENTROPY // COMPILER

Contextual Code Intelligence & Semantic ASTs

Studying how models ingest multi-file codebases, build hierarchical abstract syntax trees, and verify generated patches across cross-module dependencies in browser-native execution sandboxes.

TECHNICAL VECTOR
Semantic AST dependency parsing across heterogeneous languages
Cross-file type safety checking before rendering completions
Deterministic compiler feedback loops in WebAssembly isolates
[04]CLOUD // MESH

Heterogeneous Distributed Compute Topology

Engineering algorithms for scheduling neural network layers across diverse GPU, NPU, and edge hardware nodes without latency degradation.

TECHNICAL VECTOR
Dynamic lookahead batch scheduling across cluster meshes
Decoupled prefill and decode execution pipelines
Hardware-level memory enclave isolation (Intel SGX / AMD SEV)
02 — PUBLICATIONS

Published Findings

PEER LOGS & SYSTEM ARCHITECTURE REVIEWS

AUG 2026
PUB_041 // PRAXIS

Emergent Strategic Search in Deep RL Environments

Demonstrating how parallel MCTS rollouts combined with policy network priors outperform traditional alpha-beta heuristics in state-space depth and branch pruning.

Author:
Praxis Research Group
JUL 2026
PUB_038 // APOLEMIA

Activation Sparsity in Production-Scale Inference Runtimes

Evaluating KV-cache retention, custom quantization kernels, and sparse weight routing across heterogeneous cloud and edge compute fabrics.

Author:
Systems Architecture Lab
MAY 2026
PUB_029 // ENTROPY

Semantic Abstract Syntax Tree Parsing for Model Reasoning

How multi-file dependency trees provide foundational context for accurate code synthesis, preventing regression across isolated workspace modules.

Author:
Developer Experience Group
ACADEMIC & INDUSTRY COLLABORATION

Collaborate with Knolink Research

We coordinate with university research groups, independent scientists, and systems engineering teams. Reach out to request datasets, benchmarks, or coordinate on prototype evaluations.