The Skynet is formed! Nvidia collaborates with Google to build an AI quantum supercomputer

In 2029, the artificial intelligence supercomputer Skynet suddenly awoke, developed self-awareness, and the Skynet system determined that the invention of the supercomputer by humans would threaten AI. Therefore, it sent the T-800 Terminator robot played by Arnold Schwarzenegger back in time to eliminate the future human resistance leader John Connor. This is the plot of the movie Terminator.

Interestingly, Google's AI quantum supercomputer also has a roadmap, planning to build an AI super quantum computer in five years, and the time will come to 2029. It is currently between the third and fourth milestones. The current stage is mainly to correct the errors of Quantum Computing. At this time, the power of Nvidia GPU has accelerated the evolution of AI super quantum computers, and the prototype of the "Skynet" in human society has already taken shape.

Nvidia recently announced a partnership with Google Quantum AI to accelerate quantum computer calculations using the Nvidia CUDA-QTM simulator. From CPU to GPU to the QPU (Quantum Process Units) developed in collaboration with Google, Nvidia aims to reduce errors and optimize AI system upgrades. With supercomputing simulations, supercomputers will not develop like those in science fiction, generating a misjudgment that AI poses a threat to humans and issuing execution instructions to exterminate humans. This collaboration can be said to be the most important milestone in the history of human technological civilization in the next five years.

What is Quantum Computing (Quantum Computing)

Quantum Computing is the use of quantum physics to solve mathematical problems that are difficult to solve on traditional supercomputers. The core of Quantum Computing is qubits, where classical bits only exist in 0 or 1, while qubits can exist in a superposition of these two states.

The superposition of N quantum bits contains information about the exponential (2N) binary configurations. These binary configurations collectively form Quantum State. When any operation is performed on N quantum bits, the entire Quantum State is controlled, indicating a huge superposition. However, this use of Computing Power has subtle differences, as the information read from the Quantum State can only be probabilistically measured through calculation of individual configurations. To effectively utilize quantum superposition, the application of Quantum Computing needs to leverage the characteristics of Quantum Entanglement and quantum interference.

How does Nvidia CUDA-QTM accelerate Google AI super quantum computer calculations

Nvidia launches the NVIDIA CUDA-Q hybrid quantum-classical computing platform, combining quantum computing with high-performance traditional computing, transforming the GPU, originally designed purely for graphics, into essential hardware for high-performance computing (HPC). Nvidia provides CUDA-QTM for 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 is high. Using CUDA-Q, Google can perform the world's largest and fastest Quantum Device Physics quantum device dynamic simulation at a very low cost with 1024 Nvidia H100 Tensor Core GPUs. With CUDA-Q and H100 GPUs, Google can perform comprehensive and realistic simulations of devices with 40 quantum bits. Software supporting accelerated dynamic simulations will be publicly available on the CUDA-Q platform, enabling quantum hardware engineers to quickly expand system designs.

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