Google announced Willow on Monday, its latest quantum computing chip, showcasing impressive claims about its speed and reliability. While these achievements were significant, what truly drew the attention of the tech community was an even more extraordinary statement in the blog post.
Hartmut Neven, founder of Google Quantum AI, wrote that the chip’s performance was so extraordinarily fast that it “must have borrowed computational power from other universes.” He further suggested that this remarkable performance points to the existence of parallel universes and that “we live in a multiverse.”
Here’s the passage:
Willow’s performance on this benchmark is astonishing: It performed a computation in under five minutes that would take one of today’s fastest supercomputers 1025 or 10 septillion years. If you want to write it out, it’s 10,000,000,000,000,000,000,000,000 years. This mind-boggling number exceeds known timescales in physics and vastly exceeds the age of the universe. It lends credence to the notion that quantum computation occurs in many parallel universes, in line with the idea that we live in a multiverse, a prediction first made by David Deutsch.
What is Quantum Computing?
Unlike traditional digital computers, which function based on binary bits (0 or 1, on or off), quantum computers use extremely small units called qubits. These can exist in states of 0, 1, or both at the same time, and they can also utilize quantum entanglement—a mysterious phenomenon at the most fundamental levels of the universe, where the states of two or more particles are linked, regardless of the distance between them.
Quantum computers leverage these principles of quantum mechanics to solve highly complex problems that current classical computers cannot handle.
The challenge, however, is that the more qubits are used in a quantum computer, the more susceptible it becomes to errors. As such, it remains uncertain whether quantum computers will ever become reliable and powerful enough to meet the expectations placed on them. Google’s goal with Willow was to minimize these errors, and Neven asserts that it has achieved this goal.
How Could Quantum Computing Affect AI?
Quantum computing has the potential to revolutionize artificial intelligence (AI) by introducing unprecedented computational capabilities. Many AI tasks, such as training neural networks and solving optimization problems, require immense processing power. Quantum computers, with their ability to explore multiple solutions simultaneously, could drastically reduce the time needed for such tasks. Algorithms like Grover’s search or quantum annealing could accelerate optimization and make AI systems more efficient and powerful.
Moreover, quantum machine learning (QML) offers entirely new methods for analyzing data. By leveraging quantum states, QML algorithms can process and identify patterns in complex datasets far beyond the capabilities of classical systems. This could be a game-changer for fields like image recognition, natural language processing, and predictive modeling, where the scale and complexity of data continue to grow. Quantum computers are also well-suited for simulating complex systems, which could enhance AI applications in drug discovery, materials science, and climate modeling by generating better training data and more accurate predictions.
The intersection of quantum computing and AI could unlock solutions to problems that are currently infeasible. For instance, quantum-enhanced optimization could reshape financial market predictions or supply chain management, while quantum neural networks might achieve better generalization with less training data. Additionally, quantum systems could improve feature selection and preprocessing in machine learning, speeding up workflows and enhancing model accuracy.
