In 2029, the artificial intelligence supercomputer Skynet suddenly awakened, gaining self-awareness. The Skynet system determined that the humans who invented supercomputers would pose a threat to AI, thus sending a T-800 Terminator robot played by Arnold Schwarzenegger back to the past to eliminate John Connor, the future leader of the human resistance. This is the plot of the movie 'The Terminator'.
Interestingly, Google's AI quantum supercomputer also has a roadmap, planning to build an AI super quantum computer within five years, reaching the year 2029. It is currently at a milestone between the third and fourth phases, focusing on correcting errors in quantum computing. At this point, the power of Nvidia GPUs accelerates the evolution of the AI super quantum computer, suggesting that the prototype of 'Skynet' in human society has already taken shape.
Nvidia recently announced a collaboration with Google Quantum AI to accelerate quantum computing using the Nvidia CUDA-QTM simulator. Nvidia has transitioned from CPU to GPU and now collaborates with Google to develop QPUs (Quantum Processing Units) aimed at reducing errors and optimizing AI system upgrades. With supercomputing simulations, supercomputers will not evolve like in science fiction, leading to human misjudgments that pose threats from AI issuing extermination orders against humanity. This collaboration can be considered the most significant milestone in the history of human technological civilization development in the next five years.
What is Quantum Computing?
Quantum computing leverages quantum physics to solve mathematical problems that are intractable on today's supercomputers. At the core of quantum computing are qubits, which can exist in a superposition of the two states of classical bits, which exist only as 0 or 1.
The N qubits in superposition retain information about 2^N binary configurations. These binary configurations collectively form a quantum state. When any operation is performed on N qubits, the entire quantum state is controlled, indicating the existence of immense superposition. However, the use of this computational power has subtle nuances, as information read from the quantum state can only be achieved by probabilistically measuring a single configuration after computation. To effectively utilize quantum superposition, the application of quantum computing must leverage the properties of quantum entanglement and quantum interference.
How Nvidia CUDA-QTM Accelerates Google AI Super Quantum Computer Operations
Nvidia has launched the NVIDIA CUDA-Q hybrid quantum-classical computing platform, allowing quantum computers to work alongside high-performance traditional computing. GPUs, originally designed purely for graphics, are now essential hardware for high-performance computing (HPC). Nvidia provides CUDA-QTM for all QPU researchers and developers to perform GPU-accelerated quantum dynamics simulations, speeding up the design of the next generation of quantum computing devices.
Traditionally, the computational cost of simulation is high. Using CUDA-Q, Google can utilize 1024 Nvidia H100 Tensor Core GPUs to execute the world's largest and fastest Quantum Device Physics dynamic simulation at an extremely low cost. Through CUDA-Q and H100 GPUs, Google can conduct comprehensive and realistic simulations of devices containing 40 qubits. The software supporting these accelerated dynamic simulations will be made publicly available on the CUDA-Q platform, enabling quantum hardware engineers to quickly scale system designs.
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'Skynet is here! Nvidia partners with Google to build AI quantum computers, will science fiction become reality?' This article was first published in 'Crypto City'.