Collective Memory for AGI Models
Dynamic memory layer for AGI models, continuously updated with real-world data from satellites, robots, and cameras. Built for foundation models and physical AI with live context understanding.
1. Unified Memory Layer
Continuously ingest and process geotagged memories from satellites, robots, and cameras. Real-time updates for both indoor and outdoor environments.
2. Runtime Integration
Efficient memory access for foundation models and physical AI. Built-in support for agentic AI with dynamic world context understanding.
from memories-dev.vortx import memories-dev
from memories-dev.memories.earth_memory import EarthMemoryStore
from memories-dev.agents.agent import Agent
# Initialize with advanced models
vx = Vortx(
models={
"reasoning": deepseek-coder-small,
"vision": deepseek-vision-small
},
use_gpu=True
)
# Create Earth memories
memory_store = EarthMemoryStore()
memories = memory_store.create_memories(
location=(37.7749, -122.4194),
time_range=("2020-01-01", "2024-01-01"),
modalities=["satellite", "climate", "social"]
)
# Generate synthetic data
synthetic_data = vx.generate_synthetic(
base_location=(37.7749, -122.4194),
scenario="urban_development",
time_steps=10,
climate_factors=True
)
# AGI reasoning with memories
insights = Agent(
query="Analyze urban development patterns and environmental impact",
context_memories=memories,
synthetic_scenarios=synthetic_data
)Distributed Memory Network
Global memory fabric with continuous updates from satellites, robots, and IoT devices. Real-time geospatial indexing for dynamic world tracking.
Edge Processing
Efficient on-device memory processing for robots and drones. Enables real-time visual memory creation and local AGI inference at the edge.
Runtime Integration
Seamless memory access for foundation models and physical AI. Adaptive indoor/outdoor context switching for real-world understanding.