ABOUT NEURALA

  • Neurala is the company behind The Neurala Brain—deep learning neural network software that makes smart products like cameras, robots, drones, toys and self-driving cars more autonomous and useful.

    Unlike traditional AI companies, which designed for super computers connected to the Internet, our first project was for NASA to be used for autonomous planetary exploration. Super computers were not available. Battery life was limited. Fast internet access was impossible. Our deep learning neural networks had to be lightweight and perform in real-time without ground intervention.

  • With our constraints, we modeled the Neurala Brain on animal brains because animal brains are highly efficient “computers” that do more in less space and with less power consumption than the computers we use today. The brain also knows how to use eyes (cameras) and ears (microphones).

    This approach worked and we are now bringing The Neurala Brain to market. Our smart, fast, anywhere brain works on systems from single board computers to large servers.

  • Magazines - Pioneering Research
  • Pioneering Research

    Neurala’s founders are recognized pioneers deep learning, neural networks, and artificial intelligence. Under the ambitious DARPA Synapse project, Drs. Versace, Gorshechnikov and Ames founded the Boston University Neuromorphics Lab, which was the first research group in the world to conceive and deploy large-scale functional artificial brain systems that leveraged GPUs as computing substrate.

    Their MoNETA model, which incorporated deep learning and neural models of perception and navigation, was featured in the cover page of the prestigious IEEE Spectrum and in other prestigious publications.

    A cornerstone of Neurala’s IP is a patent centered on running Artificial Neural Networks and Deep Networks on Graphic Processing Units, or GPUs (US 8,648,867, “Graphic Processor Based Accelerator System and Method”). Deep (Neural) Networks are algorithms whose execution and training methods are highly conducive to parallelism.

    The ultimate goal of this work is to produce software for robots, drones and intelligent devices that autonomously adapt to perform useful tasks. They will be able to be applied in products that solve key societal problems including intelligent healthcare diagnostic tools and autonomous navigation systems that can be used to explore hostile environments including disaster areas and war zones. They will also provide new ways for consumer electronics and toys to interact and entertain people.

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