AI Data Platform

The ABCD stack applied to data infrastructure. Each layer enables the next.

The Stack

Layer	Function	Data Application	Key Players
A - AI	Pattern recognition, model training	Converts raw data into predictions	OpenAI, Anthropic, open-weight models
B - Blockchain	Immutable record, coordination	Data provenance, payment rails, governance	Solana, Ethereum, purpose-built L1s
C - Crypto	Aligned incentives	Token rewards for collection, staking for quality	Protocol-specific tokens
D - DePIN	Physical infrastructure	Sensors, GPUs, storage nodes	GEODNET, io.net, Filecoin

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Layer D: Physical Infrastructure

The foundation. Hardware deployed by communities that collects, stores, and processes data.

Device Categories

Category	Function	Examples	Economics
Sensors	Collect environmental data	GEODNET receivers, WeatherXM stations	Token rewards per data point
Hotspots	Provide connectivity	Helium hotspots, WiFi nodes	Data transfer credits
Storage nodes	Persist data	Filecoin miners, Arweave nodes	Storage fees
GPU nodes	Process data	io.net workers, Render nodes	Compute fees

The Transmitter-Actuator Spectrum

            Passive                      Active
         ┌──────────────────────┬──────────────────────┐
Fixed    │ SENSORS              │ ACTUATORS             │
         │ GEODNET, WeatherXM   │ Smart locks, valves   │
         ├──────────────────────┼──────────────────────┤
Mobile   │ MAPPERS              │ ROBOTS                │
         │ Hivemapper, drones   │ Optimus, delivery bots│
         └──────────────────────┴──────────────────────┘

See Robotics Industry for the full capability matrix.

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Layer C: Token Economics

Crypto aligns incentives across the data supply chain. Without tokens, community infrastructure doesn't bootstrap.

Token Mechanisms

Mechanism	Purpose	Example
Proof of contribution	Reward data collection	GEODNET token rewards per epoch
Burn-mint equilibrium	Demand-driven supply	Render RNDR burn on compute purchase
Data credits	Usage-denominated	Helium DC burn for data transfer
Staking	Quality commitment	Slashing for bad data, rewards for uptime

Token Flow

Users pay for data/compute → Protocol revenue
       ↓                           ↓
  Token burn (demand)      Operator rewards (supply)
       ↓                           ↓
  Deflationary pressure    Infrastructure expansion

Health metric: When token burn from real usage exceeds new issuance, the protocol has product-market fit. Before that, it's subsidized growth.

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Layer B: Blockchain Infrastructure

Coordination, settlement, and trust layer for data markets.

Functions

Function	What It Enables	Why Blockchain
Provenance	Track data from source to model	Immutable audit trail
Settlement	Instant payment for data/compute	No 30-day invoicing
Governance	Protocol parameter decisions	Token-weighted voting
Identity	Device and operator credentials	Self-sovereign, portable
Attestation	Data quality proofs	Cryptographic verification

Chain Selection

Chain	Strength	Used By
Solana	Speed, low cost	Render, Hivemapper, io.net
Ethereum L2s	Security, composability	Filecoin, various DePIN
Purpose-built	Domain optimization	Helium (own L1), GEODNET

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Layer A: AI and Intelligence

The value creation layer. Raw data becomes predictions, decisions, and autonomous actions.

AI Applications on DePIN Data

Data Source	AI Application	Value Created
GEODNET positioning	Centimeter autonomous navigation	Self-driving, precision agriculture
Hivemapper imagery	Real-time map intelligence	Logistics, insurance, urban planning
WeatherXM climate	Hyperlocal weather prediction	Agriculture, energy, aviation
Helium coverage	Network optimization	IoT deployment, connectivity planning
Grass web data	Training data for LLMs	Foundation model improvement

The Intelligence Stack

Raw Data → Features → Models → Predictions → Actions → Outcomes
              ↑                                            ↓
              └──── Outcomes generate new training data ───┘

The compounding effect: Better data → better models → better predictions → more valuable data demand → more devices deployed → better data.

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Stack Integration

The four layers are interdependent. Missing any layer breaks the loop.

Missing Layer	What Breaks	Result
No DePIN	No physical data collection	Models starve
No Crypto	No incentive alignment	Operators leave
No Blockchain	No coordination or settlement	Trust breaks
No AI	No value creation from data	Data has no buyer

Full Stack Flow

D (Devices collect) → B (Chain records) → C (Tokens reward) → A (AI trains)
        ↑                                                           ↓
        └──────────── A (AI predictions) create demand for D ──────┘

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Build Decisions

Component	Build	Buy	Use Protocol
Sensor hardware	If unique data type	Standard devices	DePIN protocol
Storage	Never	Cloud for hot	Filecoin for cold
GPU compute	If proprietary model	Hyperscaler	io.net, Render
Token economics	If launching protocol	N/A	Existing protocol
AI models	If domain-specific	API access	Open-weight

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Context

• AI Data Overview — The transformation thesis
• Protocols — Workflows at each layer
• Players — Who builds at each layer
• DePIN — Physical infrastructure patterns
• ABCD Stack — The broader technology framework