3. Core Features

3.1 Connect to Earn

How it Works

Neurolov's Connect to Earn feature enables users to share their GPU resources through their browser using WebGPU technology. This innovative approach allows for:

• Direct GPU access through modern browsers

• Zero installation requirements

• Real-time resource sharing

• Automated reward distribution

Browser Compatibility Check

The platform automatically performs these compatibility checks:

1. WebGPU Support

   • Browser version verification

   • GPU driver compatibility

   • Hardware capabilities assessment

2. Performance Validation

   • GPU compute capability

   • Memory availability

   • Network stability

   • Connection speed

Resource Sharing Settings

Users can customize their resource contribution:

1. Performance Settings

   • GPU usage limit (%)

   • Memory allocation

   • Workload preferences

   • Schedule configuration

2. Optimization Options

   • Power usage settings

   • Thermal management

   • Network bandwidth limits

   • Priority settings

Earnings Tracking

Real-time monitoring of:

1. Current Earnings

   • Hourly rate

   • Daily accumulation

   • Performance bonuses

2. Historical Data

   • Earnings history

   • Performance metrics

   • Contribution statistics

   • Reward calculations

3.2 GPU Marketplace

Listing Your GPU

Process for GPU providers:

1. Registration Requirements

   • Hardware specifications

   • Performance benchmarks

   • Availability schedule

   • Pricing structure

2. Verification Process

   • Hardware validation

   • Performance testing

   • Network stability check

   • Security verification

Renting GPUs

For GPU renters:

1. Search and Selection

   • Filter by specifications

   • Compare prices

   • Check availability

   • Review performance metrics

2. Rental Process

   • Duration selection

   • Payment options

   • Resource allocation

   • Access credentials

Pricing Structure

1. Dynamic Pricing Model

   • Base rate calculation

   • Demand multiplier

   • Performance factors

   • Duration discounts

2. Fee Structure

   • Platform fees (1%)

   • Transaction costs

   • Payment processing

   • Additional services

Rating System

1. Provider Ratings

   • Uptime metrics

   • Performance scores

   • Reliability index

   • User feedback

2. Renter Ratings

   • Payment history

   • Usage patterns

   • Resource respect

   • Communication

3.3 AI Model Marketplace

Available Models

Pre-deployed AI models:

1. NeuroGPT

   • Architecture: 12-layer, 768-hidden, 12-heads

   • Parameters: 110M

   • Use cases: Sentiment analysis, NER, QA

2. NeuroVision

   • Architecture: EfficientNet-B4 backbone

   • Features: FPN integration

   • Use cases: Medical imaging, object detection

3. NeuroAudio

   • Architecture: GPT-3 based

   • Parameters: 1.5B

   • Use cases: Audio generation, music creation

Model Integration

1. Integration Methods

   • API access

   • SDK implementation

   • Direct deployment

   • Custom integration

2. Framework Support

   • TensorFlow

   • PyTorch

   • ONNX

   • MLflow

Usage Terms

1. Licensing Options

   • Commercial use

   • Research use

   • Trial period

   • Custom licensing

2. Resource Requirements

   • Minimum GPU specs

   • Memory requirements

   • Network bandwidth

   • Storage needs

Performance Metrics

1. Model Monitoring

   • Inference speed

   • Accuracy metrics

   • Resource usage

   • Cost analysis

2. Optimization Tools

   • Performance tuning

   • Resource optimization

   • Cost efficiency

   • Scaling options

Deployment Options

1. Quick Deploy

   • One-click deployment

   • Pre-configured settings

   • Auto-scaling

   • Monitoring setup

2. Custom Deploy

   • Advanced configuration

   • Resource allocation

   • Performance tuning

   • Custom monitoring

Security Features

1. Model Security

   • Access control

   • Data encryption

   • Secure inference

   • Privacy protection

2. Deployment Security

   • Secure channels

   • Authentication

   • Monitoring

   • Threat detection