Quantum AI: solving the unsolvable



According to S&P Global, quantum computing’s ability to solve complex problems, combined with AI’s data analysis power, could drive major advancements in various sectors, while also raising ethical concerns.Quantum computing is a new kind of technology that works differently from everyday computers. Traditional computers use ‘bits,’ which can be either 0 or 1. Everything we see on a screen comes from these bits performing calculations and running applications extremely fast. However, there are limits to how fast even the most powerful traditional computers can compute.

Let’s use chess as an example. If a player can consider 16 possible moves at each turn, planning 10 moves ahead means a traditional computer has to evaluate around 1.1bn possible positions. If the computer can process 1m calculations per second, it would take about 12.75 days to explore all these possibilities.


                                       


Quantum computers, on the other hand, use quantum bits or ‘qubits,’ which are more flexible than regular bits. Unlike a regular bit that can exist as either 0 or 1, a qubit can be both at once, thanks to a feature called ‘superposition.’ This ability allows quantum computers to evaluate many possibilities at the same time.

So, for the chess problem, a quantum computer would need to perform about 1.05m calculations to evaluate 1.1bn possibilities, thanks to qubits working in superposition. If it also processes 1m evaluations per second, it would only take about 1.05 seconds, compared to the 12.75 days needed by a traditional computer.

Quantum computing and AI

The financial data firm S&P Global, in an editorial post on 10 September 2024, forecasted the significant potential of combining quantum computing with artificial intelligence (AI). The synergy between these technologies could revolutionise computational capabilities, presenting both unprecedented opportunities and significant challenges.

Potential

Theoretically, quantum computing’s supercharged processing power, combined with AI’s ability to analyse vast datasets, offers groundbreaking advancements. In healthcare, quantum-enabled simulations could enhance drug discovery by providing more accurate predictions of drug efficacy and safety. Financial services may benefit from quantum algorithms that optimise portfolio management and trading strategies, while supply chain management could see improvements in inventory optimisation and route planning. Energy production, distribution and consumption could be optimised through advanced algorithms, among other immediate opportunities.

Challenges and risks

Despite its potential, the development and widespread adoption of quantum AI face significant hurdles. Currently, the field is constrained by the need for specialised hardware and algorithms, in addition to skilled professionals. S&P Global noted that commercial adoption is unlikely within the next decade.

Secured communications is the biggest challenge though. Returning to the chess problem, if the game must be concluded within 10 seconds and maximum of 10 moves or no one wins, a traditional computer would likely never win against a quantum computer. In the context of a banking transaction, a secure system uses a ‘public key’ to encrypt data, which can only be decrypted by the corresponding ‘private key.’ This process ensures that the data remains confidential and tamper-proof. Currently, traditional computers would struggle to decrypt the public key within a reasonable time frame. However, a quantum computer, especially when combined with AI, could potentially decrypt the keys quickly enough to compromise the transaction’s security. This risk extends to other areas such as secure communications, stock markets, etc., where secure transaction is paramount. Additionally, AI could rapidly discover and exploit network vulnerabilities, increasing the likelihood of cyberattacks. The combination of AI and quantum computing also raises concerns about more advanced phishing attacks, sophisticated deepfakes and the potential for invasive surveillance and digital repression.

Key trends

Looking forward, several trends are likely to shape the future of quantum computing and AI, according to S&P Global. Hybrid classical-quantum systems, which combine traditional computing with quantum processing, are expected to improve efficiency and scalability. Quantum machine learning could revolutionise fields such as image and speech recognition by leveraging both quantum computing and AI principles. Enhanced cybersecurity measures will be crucial to address the new threats and opportunities presented by these technologies.

Martin Whitworth, S&P Global Ratings’ lead cyber risk expert, said in the report, “Over the next five years, we’re watching for the development of hybrid classical-quantum systems, advancements in quantum machine learning and enhanced cybersecurity measures. Ethical and societal considerations will be crucial as these technologies evolve.”

Ethical and societal considerations

The report emphasised that the integration of AI and quantum computing raises important ethical and societal questions. Issues related to data privacy, trust, algorithmic bias and employment need to be addressed as these technologies become more pervasive. Establishing ethical frameworks and regulatory guidelines will be essential to ensure responsible and equitable use, helping to maximise the benefits while mitigating potential risks.


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