Quantum + AI – could their synergy spark machine thinking into consciousness?

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Can machines think?

Turing posed this question in his 1950 paper “Computing Machinery and Intelligence” while working at the University of Manchester. In his paper, Alan Turing introduced the world to The Turing test, which he originally called “The Imitation Game” – a test of a machine’s ability to exhibit intelligent behaviour equivalent to or indistinguishable from a human’s.

Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test.

When Turing posed the question in his paper, he had made a point to conjecture away the philosophical argument, which was perhaps more challenging to formulate than his technical outline, as he had to address the one key difference between humans and machines, consciousness.

Since then, Artificial Intelligence (AI) programmers have been trying to replicate this awareness or perception of surroundings, known as consciousness, in the machines we create to pass the Turing Test. Even to the point of following Turing’s proposed theoretical blueprint for creating machine learning bots that learn from punishment reward processes subject to mutation and natural selection over accelerated generations of iterations, which in our current AI-driven world has proven to be a relatively successful approach to obtaining perceived machine intelligence. But no one has returned to the philosophical argument and asked, should we even be trying?

We will revisit this question later, but just like Turing, first indulge me for a moment as we take the original thought experiment and logically evolve it into the Fourth Industrial Revolution (4IR).

Quantum and AI – a potent power pair

Quantum Computing and AI are two groundbreaking technologies that have independently reshaped industries.

Quantum computing excels in solving highly complex problems through parallel processing, whilst AI has revolutionised sectors such as healthcare, finance and manufacturing by leveraging machine learning, predictive analytics, and natural language processing.

As these two technologies converge, they hold the potential to create a new frontier of computational power and intelligence, one that could significantly accelerate our progress toward Artificial General Intelligence (AGI), the holy grail of machine consciousness.

Contemplating Quantum

Quantum computing is a paradigm shift in computing power that harnesses the laws of quantum mechanics to solve problems far too complex for today’s classical digital computers.

To understand what a quantum computer is, it is helpful to dwell on what it is not.

  • A quantum computer is NOT a more powerful supercomputer

Similarly, a SpaceX rocket isn’t simply a more powerful aeroplane. Rockets and aeroplanes are entirely different modes of transportation. If you want to travel from Johannesburg to London, an aeroplane would be the correct choice. However, an aeroplane falls short if you want to visit Mars, and a spaceship becomes the necessary option.

  • Quantum computers will NOT replace classical computers

If we continue the transportation analogy, just like SpaceX Starships won’t be replacing aeroplanes anytime soon, quantum computers won’t be replacing classical computers. They are simply achieving vastly different objectives.

  • Quantum computers are NOT Error-Free

They are highly sensitive to their environment, which can cause errors in calculations. This phenomenon, known as quantum decoherence, is a significant challenge in developing reliable quantum systems.

  • Quantum computers are NOT magic

While they leverage quantum mechanics principles such as quantum entanglement, which seems like magic, quantum computers are not magical devices that can solve every problem instantly. They have specific applications where they can provide significant advantages.

Now that we know what quantum computers are not, let’s unpack what they are.

A quantum computer uses the quantum mechanics principle of superposition (the power to be a wave and a particle simultaneously). It performs complex calculations in the form of waves that interact with each other and produce a new wave pattern, which can be observed as the solution.

Put more simply, a quantum computer is like a pond, and the quantum algorithm or calculation is you throwing pebbles into the pond at specific points and intervals. The solution is the resulting wave that reaches your feet on the pond’s edge. This analogy also explains why it is so difficult to have error-free quantum computers, as you would need a completely isolated pond to ensure that no other factors, even something as simple as a breeze, can affect the wave that reaches your feet.

Quantum computing is, therefore, fundamentally different to classical computing. Classical computing (or binary computing) relies on bits, which exist in one of two states at any point in time: 0 or 1. Quantum computing uses Qubits, which exist in multiple states simultaneously, being 0, 1 or any combination of probabilities in between. This probability state, or superposition, is the wave nature of a qubit that can interact with other qubits in the quantum computer, like waves in the pond, to produce an outcome that is a solution to your quantum calculation.

Analysing AI

AI is the development of systems that can perform tasks typically requiring human intelligence. These tasks range from data analysis and pattern recognition to decision-making and natural language understanding. AI has advanced rapidly in recent years, transitioning from rule-based systems to more complex machine learning models and, more recently, Generative AI.

Generative AI, unlike earlier forms of AI, does not just process and analyse existing data – it has creative agency in generating new data, further stepping into that uncomfortable place of potentially mimicking human conciseness. However, it is easy to ignore those warning signs when we look at how this Generative AI offering has taken so many industries by storm in recent years with innovative and novel solutions that were previously unimaginable.

As AI continues to evolve, its journey towards Artificial General Intelligence (AGI) becomes more pronounced. While AGI, or true human-level AI, has not yet been achieved, the capabilities of Generative AI are beginning to fulfil parts of Turing’s vision. They are starting to push the boundaries of the Turing Test.

Generative AI is already transitioning AI from narrow applications to broader, more creative, and human-like functions. It powers chatbots capable of context-aware, empathetic communication, enhances creative processes through content generation, and even personalises customer experiences in real time.

According to KPMG’s 2024 Global Tech Report, 52% of global CEOs see AI as the critical technology to achieve strategic goals in the next three years. The generative capabilities of AI are moving us closer to AGI, where machines could exhibit reasoning and creativity like human intelligence.

Quantum AI – the holy grail

Quantum computing holds the potential to revolutionise AI by exponentially increasing the processing power of AI models

Darren Lentz | Senior Manager | mail me |

Faheem Ballim | Manager | mail me |


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Read the full article by Darren Lentz and Faheem Ballim, KPMG South Africa, as well as a host of other topical management articles written by professionals, consultants and academics in the October/November 2024 edition of BusinessBrief.


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Related FAQs: Quantum computing and Artificial Intelligence (AI)

Q: What is the synergy between quantum computing and artificial intelligence?

A: The synergy between quantum computing and artificial intelligence lies in the ability of quantum computers to process vast amounts of data and perform complex calculations much faster than traditional computing. This can significantly enhance machine learning algorithms, allowing AI systems to achieve better performance and efficiency.

Q: How does quantum machine learning differ from traditional machine learning?

A: Quantum machine learning utilises the principles of quantum mechanics to process information in ways that traditional machine learning cannot. Unlike classical bits, quantum bits or qubits can exist in a superposition of states, enabling quantum computers to perform multiple calculations simultaneously, which can lead to faster and more powerful AI applications.

Q: What are the unique capabilities of quantum computing that set it apart from traditional computing?

A: Quantum computing is set apart by its use of quantum bits, which can exist in multiple states at once, allowing for parallel computation. This capability enables quantum computers to tackle complex problems and datasets that would be infeasible for classical systems, potentially revolutionising fields such as machine learning and AI.

Q: Can quantum computers enhance machine learning algorithms?

A: Yes, quantum computers can enhance machine learning algorithms by providing faster processing speeds and the ability to analyse large datasets more efficiently. This quantum advantage could lead to breakthroughs in AI applications and a deeper understanding of data patterns.

Q: What role does quantum error correction play in quantum computing?

A: Quantum error correction is a crucial aspect of quantum computing that helps maintain the integrity of quantum bits during computation. Since qubits are susceptible to errors due to their delicate state, effective error correction is essential for reliable quantum machine learning and ensuring that quantum software performs accurately.

Q: How does understanding quantum computing contribute to advancements in AI?

A: Understanding quantum computing is vital for leveraging its capabilities in AI. As researchers explore the intersection of quantum computing and artificial intelligence, insights gained can lead to the development of more sophisticated machine learning algorithms and improved AI systems that can solve complex problems more effectively.

Q: What is the potential impact of quantum technology on future AI applications?

A: The potential impact of quantum technology on future AI applications is significant, as it promises to deliver powerful computational capabilities that can accelerate AI development. Quantum computing can enable AI systems to process and analyse data at unprecedented speeds, ultimately leading to more intelligent and capable machines.

Q: What challenges exist in harnessing the synergy between AI and quantum computing?

A: One of the main challenges in harnessing the synergy between AI and quantum computing is the current state of quantum hardware and software. While quantum computing has great potential, developing scalable quantum systems and effective quantum algorithms remains a significant hurdle that researchers are actively working to overcome.





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