Lower energy cost in operation. Across the industry that is potential savings of hundreds of billions of dollars in annual AI energy spend.
Of the training data conventional models require. Noetic keeps learning after deployment instead of freezing at training time.
Deployable on low-power edge hardware that operates, and continues to learn, without an internet connection.
LLMs cannot learn as part of autonomous physical AI on the edge. They need to continuously readjust their weights on remote servers.
Models cannot adjust to situations they were not trained for. Performance degrades the moment conditions drift from the training distribution.
Training and running today's models consumes massive energy. The IEA projects data center electricity to roughly double to 945 TWh by 2030, with AI the main driver.
“It is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility.”
The easy problems in AI are still the hardest. Noetic Machines is built to solve the Moravec paradox: perception, mobility, and learning in the real world.
Noetic's AI operates at a fraction of the power of backpropagation-based models. Across the industry that represents potential annual savings of hundreds of billions of dollars in AI energy costs.
Today's models require massive data sets for one-time training. Noetic learns from less than a fifth of that data, and continues to learn once deployed.
Even the best models are limited without connectivity. Noetic runs on low-power edge hardware that operates, and keeps learning, on the device itself.
Adaptive AI learns, recalls, and adapts in a way closer to how human brains work. Noetic Machines is a leading Adaptive AI platform, with patent protection dating back to 2008.
Classical control and small convolutional networks give the same answer. Hand-tuned control acquires no new behavior. A small network is frozen at deployment: it infers, it does not learn. An accelerator module is hardware, not autonomy, still running a frozen model. Noetic keeps learning in operation, on a conventional CPU, with no GPU and no accelerator.
Most AI models are trained once, by brute force, on massive data sets. The Noetic approach is closer to how our brains work.
Read the architectureWe license the autonomy stack onto our partners' hardware. We sell the brain, not the body: no device manufacturing, no inventory.
The manipulation and interaction gap is the last barrier to humanoid scale. Noetic has been tested on artificial muscles, an inverted pendulum in evolving conditions, and a robot with human-like degrees of freedom.
Autonomy that keeps working when communications do not. Proven across surveillance, target identification, and intelligent drone swarming in navigation- and communication-denied environments.
Freight no single drone can carry becomes liftable when many drones act as one aircraft. A shared load shifts constantly with wind, balance, and battery state, so cooperative lift demands continuous adaptation on every airframe.
Water blocks radio. Underwater is the one environment where cloud AI is physically impossible, and where adaptive onboard intelligence is the entire product.
Single airframes are capped by battery energy density and rotor scale. Distributing one load across a coordinated team removes that ceiling. Move the controls to see how team size changes effective lift per sortie.
Noetic wins where operation without connectivity, on-device learning, very low power, tolerance for scarce data, and peer coordination all matter at once. Each new line must clear a high bar: a named partner, a funded pilot, or a signed letter of intent.
Nearly all AI ideas incubate for a long period. Back-propagation, the basis of most models today, was created approximately fifty years ago.
World models and continual learning are now the named gap in frontier AI. Noetic has spent twenty years building exactly that, with patent protection dating back to 2008. The current investor briefing is available under NDA.
Request the investor briefingWe work with hardware-first OEMs that need an autonomy stack. Paid fine-tuning with your engineers, a per-unit license on every device shipped, and recurring support for updates and fleet learning.
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