Formation of SkyNet! Nvidia collaborates with Google to create AI Quantum Supercomputer
In 2029, the artificial intelligence supercomputer Skynet suddenly awakened and gained self-awareness. The Skynet system determined that the human creators of the supercomputer would pose a threat to AI, so it sent back a T-800 Terminator robot, played by Arnold Schwarzenegger, to the past to eliminate John Connor, the leader of the future human resistance. This is the plot of the movie “Terminator”.
Interestingly, Google’s AI quantum supercomputer also has a roadmap to build an AI super quantum computer within five years. The timeline will also reach 2029, currently between the third and fourth stages of development. The current stage focuses on correcting errors in quantum computing. At this time, the power of Nvidia GPU further accelerates the evolution of AI super quantum computers. It can be said that the prototype of the “Skynet” of human society has taken shape.
Nvidia recently announced a collaboration with Google Quantum AI to accelerate quantum computer calculations using the Nvidia CUDA-QTM simulator. Nvidia has been working with Google to develop QPU (Quantum Process Units), aiming to reduce errors and optimize the AI system. With supercomputing simulation, the supercomputer will not develop like in science fiction, where it mistakenly perceives humans as a threat to AI and issues an execution command to exterminate humanity. This collaboration can be seen as the most important milestone in the future five years of human technological civilization.
What is Quantum Computing?
Quantum computing uses quantum physics to solve the difficult problems in today’s mathematical calculations that cannot be solved by traditional supercomputers. The core of quantum computing is quantum bits. Classical bits exist only in 0 or 1, while quantum bits can exist in a state of superposition of these two states.
N quantum bits in superposition hold information about 2N binary configurations. These binary configurations collectively form a quantum state. When any operation is performed on N quantum bits, the entire quantum state is controlled, indicating the presence of immense parallelism. However, the use of this computational power has subtle differences because the information readout from the quantum state can only be probabilistically measured through computation of a single configuration. To effectively utilize quantum parallelism, the application of quantum computing requires the use of quantum entanglement and quantum interference.
How does Nvidia CUDA-QTM accelerate Google AI super quantum computer calculations?
Nvidia has launched the NVIDIA CUDA-Q hybrid quantum-classical computing platform, which combines quantum computing with high-performance traditional computing. GPUs, originally designed purely for graphics, have now become essential hardware for high-performance computing (HPC). Nvidia provides CUDA-QTM, which allows all QPU researchers and developers to perform GPU-accelerated quantum dynamics simulations, accelerating the design of next-generation quantum computing devices.
Traditionally, the cost of simulating computations is high. By using CUDA-Q, Google can execute highly cost-effective and realistic dynamic simulations of Quantum Device Physics, the largest and fastest in the world, using 1024 Nvidia H100 Tensor Core GPUs. Through CUDA-Q and H100 GPUs, Google can perform comprehensive, real-time simulations of devices with 40 quantum bits. Software supporting these accelerated dynamic simulations will be publicly available in the CUDA-Q platform, enabling quantum hardware engineers to rapidly expand system design.
