Recently, Alibaba's quantum computer team disbanded. On the one hand, it shows that in the context of deleveraging, the landlords have no more food. On the other hand, does it mean that all current quantum computers are useless?
It is certain that the G-spot of quantum computers has not yet appeared, similar to the G-spot of GPT in artificial intelligence.
So, how did Google's Sycamore beat the world record?
Google's quantum computer is called Sycamore. In a complex benchmark test, it took only 6 seconds to complete a calculation task that would take the world's fastest supercomputer Frontier 47 years to complete. This is an astonishing progress that shows the infinite possibilities of quantum computing technology. Google's quantum computer has 70 superconducting qubits. In a complex benchmark test, it successfully completed a calculation task that would take the world's first supercomputer 47 years to complete. This benchmark is called random circuit sampling, which is a method of extracting data from randomly generated quantum processes. This method can reduce the interference of external noise on calculations and can also verify the performance and correctness of quantum computers.
Google's quantum computer demonstrated amazing speed and accuracy in this test, completing a sample in just 6 seconds, while the world's fastest supercomputer Frontier took 47 years to complete the same task, illustrating the huge acceleration potential of quantum computers.
Of course, this does not mean that Google's quantum computer can solve any problem. In fact, this test is just a specific, non-programmable task with no practical application value. To realize a universal programmable quantum computer, there are still many technical challenges to be overcome, such as how to reduce the error rate of quantum bits, how to make more quantum bits, and how to achieve quantum error correction.
But it is also an important milestone, demonstrating the feasibility and advantages of superconducting quantum computers.
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The basis for the pessimists' judgment comes from competition in artificial intelligence.
Market research firm IDC released a report that due to slower-than-expected hardware development, the estimated customer expenditures for quantum computers have been significantly reduced. The agency also said that new technologies with greater short-term value, including generative AI, are swallowing up the funds originally used for quantum computers. IDC released its first quantum computer industry report in 2021, estimating that expenditures will increase from US$412 million in 2020 to US$8.6 billion in 2027 (Note: currently about RMB 62.78 billion), with a six-year compound annual growth rate (CAGR) of 50.9%. In the latest report, IDC said that quantum computing expenditures will be US$1.1 billion in 2022 and will grow to US$7.6 billion in 2027 (currently about RMB 55.48 billion), with a five-year compound annual growth rate (CAGR) of 48.1%. IDC stated in the report that quantum computing is currently only applicable to small-scale experiments. Although there are obvious advantages, many current applications remain in the hype stage. The basis for optimists' judgment comes from the fact that the public sector continues to invest in quantum technology. In 2022, the United States pledged an additional $1.8 billion in funding, the European Union pledged an additional $1.2 billion, and Canada pledged an additional $100 million.
According to McKinsey's latest quantum technology report, quantum technology companies attracted more than $2.35 billion (about 16.275 billion yuan) in private investment last year, breaking the record set in 2021. The report shows that automobiles, chemicals, financial services and life sciences may be the first four industries to see the economic impact of quantum computing, with the potential to gain up to $1.3 trillion in value by 2035.
At present, global talent is unevenly distributed. The EU and the UK are the preferred destinations for graduates in quantum technology-related fields. Data shows that in 2020, 303 new master's graduates per million EU residents were in quantum technology-related fields, and 217 new master's graduates per million UK residents were in quantum technology-related fields.
In addition, the global pool of incumbent talent with knowledge relevant to quantum technology could be increased to meet industry demand. For example, system architects, AI and machine learning algorithm developers, and others with traditional coding and AI skills could be upskilled in as little as six months to code and improve quantum algorithms. Yet, even at a time when tech companies are laying off employees, such talent is already in high demand.
The quantum industry is “in a growth phase,” which makes it challenging to find talent with the necessary skills across a range of technologies and services, said Ekaterina Almasque, a partner at venture capital fund OpenOcean. Most people in the industry today are exposed to the concept of quantum computing at a relatively late stage. While this will improve as the industry matures, there is still a need for more talent to fill this gap.
