Powering AI/Compute with
Nature's Efficiency
OpenGPU™ is an AI/compute-first open-standards initiative transforming the future of computing with nature-inspired, open-standard hardware that scales from IoT to data centers, with 100x efficiency gains.
What is
Neuromorphic Computing?
Inspired by nature and modeled after the way insect & animal brains work, neuromorphic computing offers a leap forward in adaptability, speed, and energy efficiency by applying key lessons from the structure and function of biological neural systems. This includes: leveraging time (e.g., temporal computing), randomness & noise (e.g., stochastic computing), and enormous interconnectivity (e.g., multi-dimensional neural connectivity fabrics).
Chart: Sandia Lab
How does OpenGPU approach
Neuromorphic Computing?
Whether analog, Josephson junction, or plain-old digital CMOS, OpenGPU supports fundamental improvements in AI/Compute-first architectural advances that can also handle graphics (and importantly, not the other way around).
OpenGPU funds research, development, prototyping works, and sponsored labor that are readily manufacturable and have/will have tangible benefits, as well as advance the field of neuromorphic computing. The only proviso being that the work must contribute back into the open standard, helping "raise the tide for all boats" through interoperable hardware/software interfaces that can be readily adopted by the ecosystem and future developers.
Why do Biological Systems inspire?
Edge-friendly. Low power. Self-learning. Enormously powerful. Biological brains show us how to achieve all four—processing locally, adapting on the fly, and doing more with less.
bee Brain
- Neurons
- ~1 million
- Training
- Bees training bees
- Power Budget
- 1 sip of sugar-water* (<21 microwatts**)
dog Brain
- Neurons
- 530 million
- Training
- Operant conditioning
- Power Budget
- 1 dog biscuit (3~8 watts*)
human Brain
- Neurons
- 86 billion
- Training
- Parental conditioning, education & experience
- Power Budget
- 13~25 watts*
Training Compute Requirements Are Increasing Exponentially
Model complexity and parameter memory are growing exponentially. Traditional computing can't keep up. Biology shows us a better way.
Source: Veronika Samborska (2025) - "Scaling up: how increasing inputs has made artificial intelligence more capable" Published online at OurWorldinData.org
Annual Energy Consumption
Environmental Cost
Nuclear Power Needed
Our Values
We bridge cutting-edge neuroscience, research institutions, universities, and disruptive startups with industry demand for scalable, manufacturable solution, driving the next generation of AI and computing.
Disruptive
We challenge legacy architectures with all-digital, nature-inspired hardware capable of 100x efficiency gains.
Interoperable
We build on extensible, open standards to ensure collaboration and long-term compatibility.
Transformative
Our AI-first architecture is designed to scale seamlessly across the entire stack, from IoT devices to data centers.
Sustainable
Nature does more with less. We apply these lessons to computing to reduce waste and environmental impact.
Scalable & Resilient
By fostering an open ecosystem, OpenGPU thrives independently of any single chipmaker or vendor.
Empowering
We believe in democratizing access to advanced AI compute, fueling innovation for all.
Real-World Applications
From insect-inspired drones to edge AI devices, OpenGPU technology enables applications that were previously impossible due to power constraints.
