V-JEPA 2Predictive Cooking AI
World model for proactive cooking assistance
Cooking Progress Tracker
Current Step
Step 1 of 4Slicing tomatoes
Keep slices 1/4 inch thick for best presentation
V-JEPA 2 Predictions
Next Action Prediction
Next: You'll need to slice the mozzarella to match thickness
How V-JEPA 2 Works
Visual Understanding
Analyzes video input to understand the current state of ingredients and cooking progress in real-time.
Predictive Modeling
Uses world modeling to predict likely next steps based on current actions and cooking patterns.
Proactive Assistance
Provides timely suggestions and warnings before mistakes happen, improving cooking outcomes.
Model Output Example
{
"timestamp": "2024-01-21T10:31:22.456Z",
"current_action": {
"detected": "slicing",
"object": "tomato",
"confidence": 0.97
},
"predictions": [
{
"next_action": "slice_mozzarella",
"probability": 0.89,
"timing": "within_2_minutes"
},
{
"next_action": "arrange_platter",
"probability": 0.76,
"timing": "within_5_minutes"
}
],
"suggestions": [
"Match mozzarella slice thickness to tomatoes",
"Prepare serving platter now"
],
"boundaryml_confidence": 0.98 // Structured output validation
}Integration Benefits
- Prevents common cooking mistakes before they happen
- Optimizes workflow by suggesting parallel tasks
- Adapts to individual cooking patterns over time
V-JEPA 2 Use Cases
Timing Optimization
Suggests when to start parallel tasks for efficient meal preparation
Error Prevention
Warns about potential mistakes based on visual cues and patterns
Skill Development
Provides contextual tips to improve technique over time