Even supercomputers fail in front of this Google system! 13,000 times faster, it will change the future of many things.

Google has developed an algorithm called Quantum Echoes on its Willow quantum computing chip, which is thousands of times faster than the world's most advanced supercomputers.

Google has achieved a major breakthrough in the field of quantum computing. The company has developed an algorithm called Quantum Echoes on its Willow quantum computing chip, which is thousands of times faster than classic supercomputers. Google CEO Sundar Pichai stated that this performance can be replicated. This algorithm will make drug discovery easier and faster, and will greatly help materials science. Let's learn more about it.

13,000 times faster than the most advanced supercomputer

According to a paper published in the journal Nature, Google stated that the new algorithm is 13,000 times faster than the world's most advanced supercomputer. Useful quantum technology will be available within the next five years and will transform the future of medicine and materials science. Sundar Pichai stated that the Willow chip has achieved the first verifiable quantum advantage. The Quantum Echoes algorithm running on this chip can explain the interactions between atoms using nuclear magnetic resonance. This will simplify drug discovery and materials science.

A major step towards real-world applications - Pichai

Pichai stated that this result can be verified, meaning similar results can be achieved on other quantum computers. He added that this achievement is a major step towards real-world applications of quantum computing. Following Google's announcement, shares of Alphabet, its parent company, jumped 2.4 percent.

What are quantum computers?

Quantum computers perform calculations using small circuits like traditional computers, but they do so in parallel rather than sequentially, resulting in significantly faster speeds. Several companies have claimed to have created quantum systems that can surpass traditional computers, but the real challenge lies in identifying their real-life applications.