Create model candidates
Foundation Models
Evolving the models themselves — merging fine-tuned expert models into stronger ones without further fine-tuning.
EvoGM · Evolutionary model mergingEnabling intelligence to adapt, create, and evolve across digital and physical worlds.
Genesis main keeps Assistant conversations in interactive sessions and brings pending approvals into a review dialog with the exact code and target node.
Genesis main adds a local MCP endpoint for starting tasks, tracking them by ID and retrieving their results from a coding agent.
Account-level model profiles, subscription authentication and a shared remote server reshape configuration in Genesis 0.14.1. Here is what changes and what to check when upgrading.
01Why Evolution
Evolution is nature's most proven way to create intelligence. EvoX brings that loop to AI: generate many candidates, test them for real, keep what works, and build on it — so capability compounds through experiment instead of hand-tuning.
Create diverse candidates; in later rounds, inherit and vary retained solutions.
02Applications
From models to agents, robots, and scientific discovery — one evolutionary loop, applied wherever intelligence needs to adapt.
Create model candidates
Evolving the models themselves — merging fine-tuned expert models into stronger ones without further fine-tuning.
EvoGM · Evolutionary model mergingThe root agent branches from main
Recursive agents that decompose, build, and evolve entire codebases — from a blank repository to shipped software.
Genesis · Recursive agentic systemPolicies control stride, lift, balance and timing
Evolving robot control policies through massively parallel interaction with simulated environments.
EvoRL · Evolutionary reinforcement learningPropose airfoils with different camber and thickness
Data-driven black-box optimization for scientific and engineering design, validated on supercritical airfoils.
EvoGO · Supercritical airfoil design03Hardware
Turn batches of complex tasks into tensor computation.