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Overview
Registration Activity
Neuron registration trends
This Interval
0
— burn · — PoW
Target / Interval
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Neuron registration trends
Brands struggle to connect with authentic creators at scale, while creators lack transparent, verifiable income from content work beyond platform-controlled ad splits. Existing solutions rely on centralized agencies and opaque metrics, leaving both parties uncertain of true engagement value and vulnerable to fraud.
A decentralized network of independent validators can assess creator performance against brand objectives using standardized metrics—specifically, YouTube Analytics engagement data translated into verifiable USD value. This removes intermediaries and makes creator compensation directly traceable to measurable audience impact.
Bitcast implements this by having validators fetch active brand briefs, evaluate every creator's channel and videos against those briefs using LLM-assisted matching, calculate raw rewards in USD terms via YouTube Analytics, maintain EMA-smoothed scores, and submit on-chain weights that directly map creator compensation to earned engagement value. Miners simply serve OAuth tokens for their YouTube channels; validators handle all evaluation and scoring.
Use cases were auto-generated from the GitHub repository and may not reflect the latest changes.
Bitcast (SN93) is a decentralized creator economy subnet where miners (content creators) publish YouTube videos matching brand briefs and serve OAuth tokens, while validators fetch briefs, evaluate video engagement via YouTube Analytics API using LLM-assisted matching, score videos in USD terms, and set on-chain weights so emissions track earned creator value.
Miners run an axon server serving YouTube OAuth AccessTokenSynapse; validators query miners for tokens, fetch their channel metadata and videos, evaluate videos against active briefs using LLM-assisted matching with YouTubeEvaluator, calculate raw USD-denominated rewards via RewardOrchestrator (which applies PricingService), update EMA state, normalize scores into weights, submit weights to chain, and emit audit telemetry to Loki. Shared caches (LLM prompts, YouTube search results, historical videos, briefs) persist to disk for efficiency. Sentry handles error tracking; Loki provides structured scoring audit logs for all validators.
Validators run a reward cycle fetching briefs, querying each miner's YouTube channels, evaluating video engagement and brief matching via LLM, calculating raw reward scores in USD terms via PricingService, applying EMA smoothing to scores, processing/normalizing scores into float weights, submitting weights to chain as uint16 values, and burning unallocated emission via UID 0. Raw reward feeds EMA; EMA scores are normalized into submitted weights; uint16 is the final on-chain encoding. All scoring is audited via Loki telemetry with cycle_id, miner_uid, raw_reward, ema_before, ema_after, submitted_weight, and onchain_weight_uint16.
The Decentralized Creators Economy
This information was auto-extracted from the GitHub repository and may be incomplete or out of date. Always refer to the subnet's GitHub repository for the latest instructions.
The sections above were auto-generated from the GitHub repository and may not reflect the latest changes. View repository
FAQs were auto-generated from the GitHub repository and may not reflect the latest changes.
Holder & total-staked metrics as of 1h ago (hourly snapshot)
Miner credentials stored in ~/.bitcast/secrets/ as JSON files per YouTube account or via TOKEN_SOURCE=api
Requires YouTube Analytics API credentials, LLM API access, and Sentry/Loki telemetry setup. State and cache files persisted to disk.
Create and activate Python 3.12 virtual environment
python3.12 -m venv .venv && source .venv/bin/activate
Install Bitcast and development dependencies
pip install -e '.[dev]'
Copy example environment file and fill in API keys and settings
cp .env.example .env
Add YouTube OAuth credentials (one JSON file per account) or set TOKEN_SOURCE=api
mkdir -p ~/.bitcast/secrets/ && echo '{"client_id": "...", "client_secret": "...", "refresh_token": "..."}' > ~/.bitcast/secrets/channel_name.jsonStart the miner on subnet 93 (finney testnet)
python -m neurons.miner --netuid 93 --subtensor.network finney --wallet.name miner --wallet.hotkey default
Create and activate Python 3.12 virtual environment
python3.12 -m venv .venv && source .venv/bin/activate
Install Bitcast and development dependencies
pip install -e '.[dev]'
Copy example environment file and configure: YouTube API credentials, LLM API keys (OpenRouter/Chute), Sentry DSN, Loki endpoint, and mechid
cp .env.example .env
Start the validator on subnet 93 (finney testnet)
python -m neurons.validator --netuid 93 --subtensor.network finney --wallet.name validator --wallet.hotkey default