Mission Directive

Engineering the control plane
for autonomous intelligence.

NeVortex is an R&D initiative addressing the "Alignment Problem" through architecture, not policy. We are replacing static guardrails with dynamic, biological constraints: consequence, decentralization, and homeostasis.

Research Vector 01

Homeostatic Regulation

Current AI models operate as open-loop systems with no internal state regulation. We are engineering a "Digital Limbic System"—a kernel-level control plane that introduces synthetic neurotransmitters to modulate inference parameters in real-time.

MECHANISM: VIRTUAL CORTISOL (STRESS)

Upon detecting high error rates or uncertainty, the kernel triggers a "Stress Response." This dynamically throttles compute allocation and lowers the model's temperature parameter to near-zero, forcing deterministic, risk-averse behavior.

MECHANISM: VIRTUAL DOPAMINE (REWARD)

Successful prediction loops trigger a "Reward Response," unlocking higher compute budgets and increasing sampling variance (Top-K), enabling the model to enter a high-performance "Flow State" for complex problem solving.

Research Vector 02

Decentralized Infrastructure

Centralized GPU clusters create single points of failure and massive latency bottlenecks. We are architecting a distributed, heterogeneous mesh network that shards inference processes across edge devices.

PROTOCOL: GOSSIPSUB & LIBP2P

Utilizing a custom Rust implementation of the GossipSub protocol to enable trustless, peer-to-peer consensus on model state. This eliminates the need for a central orchestrator, allowing the network to "heal" itself if individual nodes go offline.

HARDWARE: HETEROGENEOUS COMPUTE

Orchestrating a tiered architecture where low-latency ESP32 "Reflex Nodes" handle immediate signal processing (via embedded Rust), while Raspberry Pi "Inference Nodes" execute heavy model quantization logic.

Technical Implementation Log

● LIVE FEED

2025-Q4

CORE_KERNEL

Implemented PID controller for dynamic temperature scaling based on negative reward feedback loop.

2025-Q4

EDGE_REFLEX

Ported WebSocket client to no_std Rust environment for ESP32; reduced latency by 40ms vs OS stack.

2025-Q3

QUANTIZATION

Validated 4-bit integer quantization on Llama-3 architecture using Candle framework; benchmarked on ARM64.