Quantum Computing

Key Takeaway:

Although quantum technology is still in its infancy, colossal government and industry investment means we are likely to see rapid progress in hardware and software in 2023 and quantum products starting to come onto the market. Computationally intensive processes are ideal candidates for quantum applications with several use cases, such as speeding pharmaceutical drug discovery or challenging conventionally encrypted computers.

Trend Type: Technology

Sub-trends: Quantum computing R&D

Quantum computing, which uses subatomic particles to create new ways of processing and storing information, vows to be the future of computing. With the promise of operating in orders of magnitude faster than the best processors available today, quantum technology will help to solve complex problems in a fraction of the time. Although quantum technology is still in its infancy, colossal government and industry investment means we will likely see rapid progress in hardware and software in 2023 and quantum products coming onto the market. According to Forrester’s Priorities Survey, 2022, 46% of business and technology decision-makers and influencers worldwide have some knowledge about emerging QC solutions, and 65% of them consider that QC will be necessary to their organizations. An example of its growth is IBM’s Quantum Network, which had only 40 members in 2019, and in 2023 has over 210 Fortune 500 companies, universities, labs, and startups that are pulling together toward the quantum future. Or Baidu’s Paddle Quantum has not only formed a most active open source ecosystem for deep learning around its portfolio, serving over 5 million developers, but it has also published more than 600 open sources of AI models, and a dozen of them are quantum Machine Learning (ML) models for a range of business scenarios.
On the one hand, business and government leaders will step up efforts to understand and mitigate the technology’s-technology’s risks, according to the World Economic Forum – from crippling prevailing cryptography to the transformation of warfare. For instance, quantum computers can break into any conventionally encrypted computer. That is why governments and companies must monitor the consequences of post-quantum cryptography to keep data and secrets secure.
On the other hand, computationally intensive processes are ideal candidates for quantum applications. By utilizing quantum to perform Monte Carlo methods, researchers can include more random values in the simulation—thus improving accuracy without compromising speed. For example, a foreseeable use case is quantum computers simulating molecule behaviors, drastically speeding pharmaceutical drug discovery and development.
While it’s still far from realizing a genuinely universal quantum computer, all this will bring us one step closer to revolutionary business outcomes. In most cases, QCs are still just engines for learning and experimentation, and achieving practical quantum advantage is still a coin toss — it could be in 2023 or 2033.

Use Cases

Quantum Computing R&D: IBM aims to achieve quantum advantage, where a quantum computer can solve problems that traditional computers cannot, by 2026. To do so, IBM focuses on error mitigation, a technique that reduces errors in quantum computing by combining hardware and software solutions. The company announced in November 2022 the largest and most powerful quantum computer to date – “Osprey,” with 433 quantum bits, more than triple the size of the company’s previously record-breaking 127-qubit computer and more than eight times larger than Google’s 53-qubit computer Sycamore.Centre.

Use Cases

Quantum Computing R&D:

Quantum Computing R&D:

Sub-Trend Sources
Quantum computing R&D: WEF Trends To Watch 2023