06 — First Steps

NTL-specific actions from now to research preview.

NTL-specific actions from now to research preview.

Status: ACTIVE

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Repository (nyuchi-ntl/ntl)

Immediate Actions

1. Create ntl-signal crate in crates/ntl-signal/

   • Scaffold Node, Signal, Synapse, SignalNetwork types
   • Implement channel transport layer (in-process, Rust mpsc)
   • Basic tests: create nodes, connect, emit, verify activation
   • This is Phase 1 of the signal primitive roadmap

2. Add research docs to docs/research/

   • Move these .mdx files into the repo
   • Set up Mintlify at openntl.org with research section visible

3. Update README to reflect the ML-at-transfer-layer positioning

   • Lead with “infrastructure-level machine learning”
   • The twelve principles summary
   • Hardware neural engine story

Near-Term Engineering

Week	Deliverable
1-2	ntl-signal crate with weight-based routing (Phase 1: Fallback backend)
3-4	Basic tests, benchmarks at 100-1000 node scale
5-6	ONNX routing model integration (Phase 2: OnnxCpu backend)
7-8	Hardware NPU research — Core ML and NNAPI exploration
9-10	Training pipeline: sync protocol feedback → weight updates
11-12	Research preview alongside SiafuDB launch

Research Questions to Answer

1. ONNX Runtime Rust bindings: Does the ort crate support all target platforms? iOS, Android, WASM?
2. NPU access: What’s the path from ONNX model to Core ML (iOS) and NNAPI (Android)?
3. Model size: What’s the minimum routing model that produces meaningful improvements over weight-based routing?
4. Training frequency: How often can we run gradient updates on-device without impacting battery?
5. Privacy: Do routing features (device state, activity patterns) create privacy risks if the model is exported?

Outreach

When	Who	What
After ntl-signal works	Rust community (r/rust, Discord)	The signal primitive — new concurrency paradigm
After ONNX integration	ML community	Neural routing on NPU hardware
After IPv6 research	Networking community	Signal propagation without NAT

Lead with the signal primitive for Rust community (they love new concurrency primitives). Lead with ML principles for ML community. Lead with IPv6 architecture for networking community. Each community enters through their interest and discovers the larger vision.

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Crate Structure

ntl/
├── crates/
│   ├── ntl-signal/                 # ← BUILD THIS FIRST
│   │   ├── Cargo.toml
│   │   └── src/
│   │       ├── lib.rs
│   │       ├── node.rs             # Node struct, accumulation, activation
│   │       ├── signal.rs           # Signal trait, DataSignal
│   │       ├── synapse.rs          # Synapse, transformation, learning rules
│   │       ├── network.rs          # SignalNetwork, topology management
│   │       ├── routing/
│   │       │   ├── mod.rs
│   │       │   ├── fallback.rs     # Weight-based (Phase 1)
│   │       │   ├── onnx.rs         # ONNX model (Phase 2)
│   │       │   └── npu.rs          # Hardware NPU (Phase 3)
│   │       └── transport/
│   │           ├── mod.rs
│   │           ├── channel.rs      # In-process (Rust mpsc)
│   │           ├── local.rs        # Same machine (Unix socket)
│   │           ├── network.rs      # Same LAN (TCP/QUIC)
│   │           └── fabric.rs       # Global (IPv6)
│   ├── ntl-core/                   # Existing
│   ├── ntl-cli/                    # Existing
│   ├── ntl-node/                   # Existing
│   └── ntl-edge/                   # Existing
├── docs/research/                  # These documents
└── ...

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April 2026 — The Bundu Foundation