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brain computer interface

Faster data processing chip ‘Darwin’ For Future AI Systems by China

The researchers from Zhejiang University and Hangzhou Dianzi University in China has created a type of biologically-inspired artificial neural network (ANN) called spiking neural network (SNN). The SNN comes in the form of a chip called “Darwin,” named upon a famous geologist Charles Darwin, which mimics the principles of biological brain to perform faster data processing. Fabricated using standard CMOS technology, the Darwin Neural Processing Unit is a specialized hardware co-processor that could revolutionize the development of Robotics, Brain-Computer interfaces and various intelligent hardware systems.

The Darwin NPU is hardwired to provide hardware acceleration of intelligent algorithms. Adding a boon for low-power and resource-constrained small embedded devices, the Darwin NPU has been fabricated by 180nm standard CMOS process. The latter supports up to 2048 neurons, in addition to 15 possible synaptic delays and more than 4 million synapses.
darwin-chip-processor-neuromorphicThe best characteristic about Darwin NPU is that its SNN topology can be reconfigured. That is, it can be modified to include different configurations of synapses and neurons. It can be configured in multiple ways by its user to include different functionalities.

As products and services based on ‘Internet of Things’ grow with leaps and bounds, the technology underneath needs to get advanced with the same pace. The main challenges in this arena are faced by researchers who are trying to process complex artificially intelligent algorithms on really tiny embedded devices.

ALSO READ :   Brain-computer interface technology demonstrated at NMU

As stated earlier, one of the major potential applications of the Darwin chip is the development of brain-computer interfaces. To demonstrate this, the Chinese research team has built a prototype that let’s a user control a virtual basketball plainly via brain commands.

This is achieved by the system developed to recognize the user’s motor imagery intention through real-time decoding of EEG signals. The important thing to note here is that, unlike existing EEG signal analysis algorithms, the input and output to Darwin are both neural spikes.



  1. Francis gold

    September 26, 2016 at 11:26 AM

    Darwin is back! 🙂

  2. Shiven Das

    September 26, 2016 at 1:54 PM

    China is doing something!!! That’s future

  3. Tanesha Orsini

    September 26, 2016 at 6:58 PM

    Eveгything is very օpen wіth a rᥱally cⅼear clarification. Ιt was definitely informative. Your site іs useful.
    Many tҺanks for sharing!

  4. Latisha Symon

    September 27, 2016 at 3:03 PM

    Excelⅼent ѡаy of describing, and ցood paragraph to obtаin facts
    on the tоpic of my presentation focus, which i am goinng to
    present in academy.

  5. Tera Cintron

    September 28, 2016 at 1:17 AM

    That’s cool 🙂

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