Skynet is here! Nvidia and Google team up to create an AI quantum computer, will science fiction movies come true?

In 2029, the artificial intelligence supercomputer Skynet suddenly awakens and becomes self-aware. The Skynet system determines that the humans who invented the supercomputer will pose a threat to AI. Therefore, it sends back a T-800 Terminator robot played by Arnold Schwarzenegger to the past to eliminate John Connor, the leader of the human resistance in the future world. 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 in five years, with the time reaching 2029, which is currently between the third and fourth milestones. The current stage is mainly focused on correcting errors in Quantum Computing. At this time, the power of Nvidia GPU has also accelerated the evolution of AI super quantum computers. It can be said that the prototype of the "Skynet" in human society has already taken shape.

Nvidia recently announced a collaboration 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 simulation, supercomputers will not develop like science fiction, leading to misjudgments that AI poses a threat to humans and issues execution commands to exterminate humanity. This collaboration can be said to be the most important milestone in the history of human technological civilization development in the next five years.

What is Quantum Computing (Quantum Computing)

Quantum Computing uses quantum physics to solve mathematical problems that cannot be solved on traditional supercomputers. The core of Quantum Computing is quantum bits, while classical bits only exist in 0 or 1, quantum bits 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 the Quantum State. When any operation is performed on N quantum bits, the entire Quantum State is controlled, indicating a tremendous parallelism. However, the use of Computing Power in this way has subtle differences, as the information read from the Quantum State can only be probabilistically measured through computation of a single configuration. In order to effectively utilize quantum parallelism, the application of Quantum Computing needs to leverage the properties of Quantum Entanglement and quantum interference.

How Nvidia CUDA-QTM accelerates Google AI super quantum computer computing

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

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The Internet is here! Nvidia and Google join forces to create an AI quantum computer, will science fiction movies come true? This article was first published in 'encryption city'