Scientists from the Dresden University of Technology claim that a neuromorphic chip they’ve developed could potentially improve the efficiency of blockchain technology and artificial intelligence.
The study by a group of scientists from the Dresden University of Technology in Germany demonstrates the revolutionary potential of neuromorphic computing for both the blockchain industry and the development of artificial intelligence (AI) technologies.
Using the “reservoir computing” method, the researchers developed a way of pattern recognition that uses a vortex of magnons to perform algorithmic functions almost instantly. In their study, the authors emphasize that neuromorphic computing can mimic the activity of the organic brain using programmable artificial neurons. Therefore, instead of processing binary data, these systems can send signals through neural patterns.
The technological features of neuromorphic computing can enhance the efficiency of blockchain networks and AI-based projects, as they’re well suited for pattern recognition and machine learning algorithms.
The scientists also highlighted that the main advantage of neuromorphic computing is the energy savings compared to classical and quantum computing. This means that neuromorphic computing can significantly reduce the time and energy required to compute new blocks and maintain other aspects of blockchain networks.
Scientists recently proved that the energy efficiency of crypto mining can be improved with the help of quantum machines. Moreover, quantum computing methods can boost the energy efficiency of the PoW algorithm.
