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Fruit Fly Brain Model Walks, Feeds Inside a Computer
The emulation replicates 125,000 neurons and 50 million synapses to produce walking and feeding behaviors with 95% motor prediction accuracy, researchers said.
- On Wednesday, Oct. 2, Eon Systems PBC demonstrated the world’s first embodied whole-brain emulation that drove behaviors in a simulated adult Drosophila melanogaster using NeuroMechFly v2 and the MuJoCo physics engine.
- Built from electron‑microscopy of 7,000 slices, the FlyWire Consortium recently completed a fly wiring diagram, and Philip Shiu in 2024 published a connectome-based brain model with ML neurotransmitter predictions.
- Validation shows the connectome‑based model predicted motor behavior with 95% accuracy, and the demonstration video emphasizes it is a biological connectome replica, not reinforcement‑learning approaches.
- Eon Systems plans to scale from fly to mouse and build the largest connectome, advancing neuroscience and AI research communities.
- Compared with earlier efforts, the demonstration marks a major scale jump from larval fly and nematode models and sparks debate on autonomous neural dynamics versus reinforcement‑learning flies.
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Musk Amazed: First Cyber Drosophila Comes to Life with Fully Uploaded Multi - behavior Brain, Autonomously Driving Digital Body
Break the fixation on large models! The world's first "multi - behavior brain upload" is a success. A fruit fly brain with 125,000 neurons is fully connected to the physical engine. For the first time, real biological rhythm autonomously drives the digital body. Whole - brain simulation steps into reality, and the engineering roadmap for human consciousness digitization becomes clearer.
The First Digital Brain Just Walked: Fruit Fly Emulation Signals Human Copy-Paste Consciousness
Scientists have copied a fruit fly’s brain neuron by neuron into a computer. No training data. No reinforcement learning. It simply woke up and walked. This breakthrough by Eon Systems marks the first embodied whole-brain emulation—paving the way for digital humans
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