Numenta AI Platform

AI technology rooted in neuroscience and run on commodity CPUs

Lightning Speed

Achieve 10 to over 100 times speedup on CPUs without sacrificing accuracy

Power Efficient

Run on CPUs with 5-20X power savings over GPUs

Memory Friendly

Reduce memory usage and simplify memory management systems

Effective Scaling

Easily scale large AI models on CPU-only systems

Boosts AI inference performance on commodity CPUs

Our technology achieves unparalleled speedups and performance improvements on CPUs – BERTs to multi-billion parameter GPTs. 

Enables ultimate AI infrastructure efficiency

Simplify infrastructure management by flexibly allocating cores to leverage untapped CPUs, maximize resource utilization and minimize TCO.

Seamlessly integrates with standard workflows

Built on the Triton Server and standard inference protocols, Numenta’s AI platform fits right into existing infrastructure and works with standard MLOps.

Achieves dramatic performance improvements

Numenta's brain-based algorithms, data structures and architecture provide the backbone for our AI platform technology. We have demonstrated how the platform can accelerate inference, improve model development, and reduce costs and power consumption.

Numenta Inference Server

Built on the Triton server, our inference server uses industry standard protocols and a simple http-based API, which allows for seamless integration into almost any standard MLOps solution, such as Kubernetes.

When run on CPUs, a single instance of the server can run dozens of different models in parallel without the need for batching or synchronization, providing the ultimate infrastructure flexibility. 

Numenta Training Module

Our training module makes it easy to fine-tune a model for a specific task or increase model accuracy for particular domains or use cases.  Fine-tuning can be useful for adapting non-generative models with the necessary model heads or performing additional training on a generative model to give more appropriate responses.

Cajal Libraries

Within our Inference Server is a real-time engine, built using our internal Cajal Libraries (named after the very first neuroscientist Santiago Ramón y Cajal). These libraries, written in C++ and assembler, are designed to minimize data movement, maximize cache usage and optimize memory bandwidth, enabling efficient memory sharing across models.

The Cajal Libraries include an optimized runtime, custom ONNX routines, and a set of hardware optimizations that leverage SIMD instructions (AVX2, AVX512, and AMX) for unparalleled throughput without sacrificing accuracy.

Leverages insights from cortical circuitry, structure and function

Numenta technology is built on the Thousand Brains Theory, our sensorimotor framework of intelligence. The framework suggests mechanisms for how the brain efficiently represents information, learns about the structure of the world, and makes predictions.

Data Structures

Based on how information is represented in the brain, Numenta data structures are highly flexible and versatile, applicable to many different problems in many different domains.

Architecture

Based on biophysical properties of the brain, Numenta’s network architecture dynamically restricts and routes information in a context-specific manner, yielding low-cost solutions for a range of problems.

Algorithms

Based on how information is used in the brain, Numenta algorithms intelligently act on data and adapt as the nature of the problems change. 

RESULTS

Dramatically Accelerate Large Language Models on CPUs

Why Numenta

At the Forefront of Deep Learning Innovation

Rooted in deep neuroscience research

Leverage Numenta’s unique neuroscience-based approach to create powerful AI systems

10-100x performance improvements​

Reduce model complexity and overhead costs with 10-100x performance improvements

Seamless adaptability and scalability

Discover the perfect blend of flexibility and customization, designed to cater to your business needs

Deploy On-Premise or Via Favorite Cloud Provider

Case Studies