Nvidia and Google Quantum AI Collaborate to Accelerate Quantum Computing Development

Nvidia's Collaboration with Google AI Advances Next-Gen Quantum Hardware - Alphabet (NASDAQ:GOOGL), NVIDIA (NASDAQ:NVDA)

The partnership enables faster quantum simulations, cutting week-long processes to minutes, advancing quantum hardware innovation. On Monday, Nvidia Corp NVDA announced it partnered with Alphabet Inc GOOG GOOGL Google Quantum AI to accelerate the development of next-generation quantum computing devices. Using Nvidia's CUDA-Q platform and the Eos supercomputer, Google is advancing simulations to refine its quantum processor designs, addressing challenges like noise that limit current quantum hardware capabilities. Google Quantum AI is leveraging hybrid quantum-classical computing and Nvidia's advanced technology to perform comprehensive simulations that analyze noise and qubit interactions. Also Read: Mastercard Lowers Financial Forecast, Signals Slower EPS, Revenue Growth Ahead These simulations are essential for scaling quantum hardware while maintaining accuracy. Guifre Vidal, the research scientist at Google Quantum AI, highlighted the importance of reducing noise for commercial quantum computing to succeed. Nvidia's accelerated computing allows Google to explore noise implications for larger quantum chip designs, enabling simulations that were previously too computationally intensive. By harnessing the CUDA-Q platform and 1,024 Nvidia H100 Tensor Core GPUs on the Eos supercomputer, Google achieved one of the most extensive dynamical simulations of quantum devices to date. These simulations, which previously required a week, can now be completed in minutes. The ability to simulate devices containing up to 40 qubits marks a significant milestone in quantum hardware development. The CUDA-Q platform's software will be publicly available, enabling engineers worldwide to scale and refine their quantum hardware designs. This democratizes access to high-fidelity simulations, paving the way for advancements in quantum computing across industries. Tim Costa, Nvidia's director of quantum and HPC, emphasized that AI-driven supercomputing is pivotal to the success of quantum computing. By reducing the cost and time of simulations, this collaboration between Nvidia and Google Quantum AI will likely help solve complex real-world challenges, fostering innovation in fields ranging from cryptography to advanced AI applications. Nvidia faces increased scrutiny as it approaches its earnings report, with concerns arising over technical issues in its latest AI chips and broader market conditions. Mizuho analyst Jordan Klein, a long-time supporter of Nvidia, highlighted potential risks for the company's shares, citing reports of overheating in its new Blackwell systems. Klein said the swift and often reactionary nature of market dynamics, which could lead to sell-offs before investors thoroughly assess the situation. Reports suggest that Nvidia's Blackwell chips, launched in March with claims of delivering 30 times faster performance than prior models, have faced thermal challenges in densely packed server racks. High-profile clients such as Meta Platforms Inc META, Microsoft Corp MSFT, and Alphabet could be impacted. While Klein remains optimistic about Nvidia's long-term prospects, he advises caution in the near term, particularly for retail and momentum investors who might react sharply to headlines. Offering a different perspective, CNBC's Jim Cramer downplayed the concerns, calling for skepticism about the reported negatives. Cramer suggested that the situation could present a buying opportunity, dismissing specific reports as potentially overstated. Price Actions: NVDA stock is up 2.47% at $143.62 at the last check on Tuesday. Also Read: Stratasys CEO Touts Turnaround: Strong Market Gains, Cost Cuts Drive Q3 Beat, Guidance Raised Image via Shutterstock This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Market News and Data brought to you by Benzinga APIs

NVIDIA Accelerates Google Quantum AI Processor Design With Simulation of Quantum Device Physics - NVIDIA (NASDAQ:NVDA)

ATLANTA, Nov. 18, 2024 (GLOBE NEWSWIRE) -- SC24 -- NVIDIA today announced it is working with Google Quantum AI to accelerate the design of its next-generation quantum computing devices using simulations powered by the NVIDIA CUDA-Q™ platform. Google Quantum AI is using the hybrid quantum-classical computing platform and the NVIDIA Eos supercomputer to simulate the physics of its quantum processors. This will help overcome the current limitations of quantum computing hardware, which can only run a certain number of quantum operations before computations must cease, due to what researchers call "noise." "The development of commercially useful quantum computers is only possible if we can scale up quantum hardware while keeping noise in check," said Guifre Vidal, research scientist from Google Quantum AI. "Using NVIDIA accelerated computing, we're exploring the noise implications of increasingly larger quantum chip designs." Understanding noise in quantum hardware designs requires complex dynamical simulations capable of fully capturing how qubits within a quantum processor interact with their environment. These simulations have traditionally been prohibitively computationally expensive to pursue. Using the CUDA-Q platform, however, Google can employ 1,024 NVIDIA H100 Tensor Core GPUs at the NVIDIA Eos supercomputer to perform one of the world's largest and fastest dynamical simulation of quantum devices -- at a fraction of the cost. "AI supercomputing power will be helpful to quantum computing's success," said Tim Costa, director of quantum and HPC at NVIDIA. "Google's use of the CUDA-Q platform demonstrates the central role GPU-accelerated simulations have in advancing quantum computing to help solve real-world problems." With CUDA-Q and H100 GPUs, Google can perform fully comprehensive, realistic simulations of devices containing 40 qubits -- the largest-performed simulations of this kind. The simulation techniques provided by CUDA-Q mean noisy simulations that would have taken a week can now run in minutes. The software powering these accelerated dynamic simulations will be publicly available in the CUDA-Q platform, allowing quantum hardware engineers to rapidly scale their system designs. About NVIDIA NVIDIA NVDA is the world leader in accelerated computing. For further information, contact: Cliff Edwards NVIDIA Corporation +1-415-699-2755 [email protected] Certain statements in this press release including, but not limited to, statements as to: the benefits, impact, and performance of NVIDIA's products, services, and technologies, including NVIDIA CUDA-Q platform, NVIDIA Eos supercomputer, and NVIDIA H100 Tensor Core GPUs; Google using our products and technologies, the benefits and impact thereof, and the features, performance and availability of its offerings; and AI supercomputing power being helpful to quantum computing's success are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners' products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company's website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances. Many of the products and features described herein remain in various stages and will be offered on a when-and-if-available basis. The statements above are not intended to be, and should not be interpreted as a commitment, promise, or legal obligation, and the development, release, and timing of any features or functionalities described for our products is subject to change and remains at the sole discretion of NVIDIA. NVIDIA will have no liability for failure to deliver or delay in the delivery of any of the products, features or functions set forth herein. © 2024 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo and CUDA-Q are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice. A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/823fa93b-bab5-4f04-af9a-0812a2f9a41f Market News and Data brought to you by Benzinga APIs

Nvidia accelerates Google quantum AI design with quantum physics simulation

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Nvidia it is working with Google Quantum AI to accelerate the design of its next-generation quantum computing devices using simulations powered by Nvidia. Google Quantum AI is using the hybrid quantum-classical computing platform and the Nvidia Eos supercomputer to simulate the physics of its quantum processors. This will help overcome the current limitations of quantum computing hardware, which can only run a certain number of quantum operations before computations must cease, due to what researchers call "noise." "The development of commercially useful quantum computers is only possible if we can scale up quantum hardware while keeping noise in check," said Guifre Vidal, research scientist from Google Quantum AI, in a statement. "Using Nvidia accelerated computing, we're exploring the noise implications of increasingly larger quantum chip designs." Understanding noise in quantum hardware designs requires complex dynamical simulations capable of fully capturing how qubits within a quantum processor interact with their environment. These simulations have traditionally been prohibitively computationally expensive to pursue. Using the CUDA-Q platform, however, Google can employ 1,024 Nvidia H100 Tensor Core GPUs at the Nvidia Eos supercomputer to perform one of the world's largest and fastest dynamical simulation of quantum devices -- at a fraction of the cost. "AI supercomputing power will be helpful to quantum computing's success," said Tim Costa, director of quantum and HPC at Nvidia, in a statement. "Google's use of the CUDA-Q platform demonstrates the central role GPU-accelerated simulations have in advancing quantum computing to help solve real-world problems." With CUDA-Q and H100 GPUs, Google can perform fully comprehensive, realistic simulations of devices containing 40 qubits - the largest performed simulations of this kind. The simulation techniques provided by CUDA-Q mean noisy simulations that would've taken a week can now run in minutes. The software powering these accelerated dynamic simulations will be publicly available in the CUDA-Q platform, allowing quantum hardware engineers to rapidly scale their system designs.

NVIDIA Accelerates Google Quantum AI Processor Design With Simulation of Quantum Device Physics

SC24 -- NVIDIA today announced it is working with Google Quantum AI to accelerate the design of its next-generation quantum computing devices using simulations powered by the NVIDIA CUDA-Q™ platform. Google Quantum AI is using the hybrid quantum-classical computing platform and the NVIDIA Eos supercomputer to simulate the physics of its quantum processors. This will help overcome the current limitations of quantum computing hardware, which can only run a certain number of quantum operations before computations must cease, due to what researchers call "noise." "The development of commercially useful quantum computers is only possible if we can scale up quantum hardware while keeping noise in check," said Guifre Vidal, research scientist from Google Quantum AI. "Using NVIDIA accelerated computing, we're exploring the noise implications of increasingly larger quantum chip designs." Understanding noise in quantum hardware designs requires complex dynamical simulations capable of fully capturing how qubits within a quantum processor interact with their environment. These simulations have traditionally been prohibitively computationally expensive to pursue. Using the CUDA-Q platform, however, Google can employ 1,024 NVIDIA H100 Tensor Core GPUs at the NVIDIA Eos supercomputer to perform one of the world's largest and fastest dynamical simulation of quantum devices -- at a fraction of the cost. "AI supercomputing power will be helpful to quantum computing's success," said Tim Costa, director of quantum and HPC at NVIDIA. "Google's use of the CUDA-Q platform demonstrates the central role GPU-accelerated simulations have in advancing quantum computing to help solve real-world problems." With CUDA-Q and H100 GPUs, Google can perform fully comprehensive, realistic simulations of devices containing 40 qubits -- the largest-performed simulations of this kind. The simulation techniques provided by CUDA-Q mean noisy simulations that would have taken a week can now run in minutes. The software powering these accelerated dynamic simulations will be publicly available in the CUDA-Q platform, allowing quantum hardware engineers to rapidly scale their system designs.

Google and Nvidia Team Up on Quantum Computer Development | PYMNTS.com

Google Quantum AI is using the Nvidia CUDA-Q platform and the Nvidia Eos supercomputer to help develop its next-generation quantum computing devices. The firm is using the platform to simulate the physics of its quantum processors as it works to overcome "noise" -- a limitation of quantum computing hardware that allows it to run only a certain number of quantum operations before stopping, the companies said in a Monday (Nov. 18) press release. "The development of commercially useful quantum computers is only possible if we can scale up quantum hardware while keeping noise in check," Guifre Vidal, research scientist at Google Quantum AI, said in the release. "Using Nvidia accelerated computing, we're exploring the noise implications of increasingly larger quantum chip designs." With the CUDA-Q platform, Google Quantum AI can perform dynamical simulations of quantum devices to better understand noise in quantum hardware designs, according to the release. The platform will make it affordable to run simulations that were previously prohibitively expensive to pursue and will perform in minutes the simulations that used to take a week, the release said. The software powering these simulations will be publicly available in the CUDA-Q platform, per the release. "AI supercomputing power will be helpful to quantum computing's success," Tim Costa, director of quantum and HPC at Nvidia, said in the release. "Google's use of the CUDA-Q platform demonstrates the central role GPU-accelerated simulations have in advancing quantum computing to help solve real-world problems." Quantum computers, which harness quantum mechanics principles to perform complex calculations, could turbocharge AI systems' processing power by leveraging quantum bits (qubits) properties like superposition and entanglement, PYMNTS reported in May. This quantum-AI synergy could tackle computationally intensive tasks beyond classical computers' reach, potentially helping to power breakthroughs in medicine, materials science, financial modeling and cryptography. In March, Google Quantum AI and Google.org joined XPRIZE and the Geneva Science and Diplomacy Anticipator (GESDA) to launch XPRIZE Quantum Applications, a three-year, $5 million global competition to apply quantum computing to solve real-world challenges and prove quantum computing's potential for practical utility. The competition is closely aligned with Google Quantum AI's focus on building a large-scale, error-corrected quantum computer and developing useful quantum computing applications.

Nvidia Is Helping Google Design Quantum Computing Processors

Nvidia Corp., the chipmaker at the center of a boom in artificial intelligence use, is teaming up with Alphabet Inc.'s Google to pursue another technology once relegated to science fiction: quantum computing. Google's Quantum AI division will use Nvidia's Eos supercomputer to speed up the design of quantum components, according to a statement from the companies on Monday. The idea is to simulate the physics that's required for quantum processors to work, helping them overcome current limitations.