OSCEN | Intelligence that grows

The Problem

AI today is powerful.
But it can't learn from experience.

~0.3 Wh

per query

GPT-4o uses ~0.3 Wh per query. Multiply by billions of daily requests.

Epoch AI, 2025

$100M+

to train

Training a frontier model costs $100M+. And when it's done, it's frozen forever.

Public filings

0

real-time learning

Once deployed, these models can't learn from experience. Static weights. No adaptation.

By design

What if intelligence could grow?

The Answer

A brain that learns
like a child.

Learns from experience

+

One million spiking neurons connected by 1.19 billion synapses. Learning happens through spike timing, the same mechanism biological brains use. No training datasets. No gradient descent.

Explore the architecture →

Runs on milliwatts

+

Spiking neural networks compute only when neurons fire. On neuromorphic hardware, that means 73–109× less energy than traditional AI. The efficiency gap widens at scale.

See the benchmarks →

Grows through phases

+

Like a human brain, OSCEN develops through infant, toddler, juvenile, adolescent, and mature phases. Each phase changes what the brain learns, what it prunes, and what it preserves forever.

Read the science →

Works with any body

+

Camera, microphone, IMU, touch sensor. Any input. Servos, motors, speakers. Any output. The brain connects to any robotic body through a universal message bus. The brain is the product.

View the integration →

Proof

Not a concept.
A running system.

1,001,800

neurons

11 brain regions. 24 synapse groups. Sensory, motor, association, prediction, working memory, all connected and learning.

6

learning rules

STDP, eligibility traces, BCM metaplasticity, neuromodulation, homeostatic scaling, and reward-modulated learning. All running simultaneously, every step.

7 months

training continuously

Started as a blank slate. Watching video, listening to audio. Forming associations through temporal correlation. Growing through developmental phases.

Patent pending

US 63/986,737

Filed February 20, 2026. 6 core claims covering the complete architecture. 258 prior art patents searched, zero overlap. 20 continuation patents planned.

Patent details →

Training continuously on dedicated infrastructure

Vision

The brain for
every robot.

◎

Any intelligence

+

From 1 million neurons today to 100 million. From baby videos to embodied manipulation. From one brain to a fleet sharing learned experiences.

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Any hardware

+

Software simulation today. Neuromorphic silicon tomorrow. The architecture maps directly to chips like Intel Loihi for 1000× energy reduction. The hardware wave is coming.

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