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D-Wave Announces Roadmap to Extend Leap Quantum Cloud Service for AI/ML

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D-Wave Quantum Inc. (NYSE: QBTS) has announced an extension to its product development roadmap, focusing on Quantum AI solutions to address the growing demand for more efficient AI and machine learning workloads. The company aims to leverage its annealing quantum computing capabilities to help customers discover better, faster, and more energy-efficient AI solutions.

The roadmap includes three key development areas: Quantum Distributions for Generative AI, Restricted Boltzmann Machine (RBM) Architectures, and GPU Integration with the Leap quantum cloud service. These initiatives aim to support various applications, from molecular discovery to cybersecurity and high-energy physics data analysis.

Early customer use cases have shown promising results, with researchers in Germany, TRIUMF in Canada, and Honda Innovation Lab in Japan demonstrating improved performance and efficiency using D-Wave's quantum technology for AI and machine learning tasks.

D-Wave Quantum Inc. (NYSE: QBTS) ha annunciato un'estensione della sua roadmap di sviluppo prodotto, concentrandosi su soluzioni di Quantum AI per rispondere alla crescente domanda di carichi di lavoro di AI e machine learning più efficienti. L'azienda punta a sfruttare le sue capacità di computing quantistico di annealing per aiutare i clienti a scoprire soluzioni AI migliori, più rapide e più efficienti in termini energetici.

La roadmap include tre aree chiave di sviluppo: Distribuzioni Quantistiche per AI Generativa, Architetture di Macchine di Boltzmann Ristrette (RBM) e Integrazione GPU con il servizio cloud quantistico Leap. Queste iniziative mirano a sostenere diverse applicazioni, dalla scoperta molecolare alla cybersicurezza e all'analisi dei dati della fisica ad alta energia.

I primi casi d'uso dei clienti hanno mostrato risultati promettenti, con ricercatori in Germania, TRIUMF in Canada e Honda Innovation Lab in Giappone che hanno dimostrato un miglioramento delle prestazioni e dell'efficienza utilizzando la tecnologia quantistica di D-Wave per compiti di AI e machine learning.

D-Wave Quantum Inc. (NYSE: QBTS) ha anunciado una extensión de su hoja de ruta de desarrollo de productos, enfocándose en soluciones de Quantum AI para abordar la creciente demanda de cargas de trabajo de AI y aprendizaje automático más eficientes. La empresa tiene como objetivo aprovechar sus capacidades de computación cuántica de anidación para ayudar a los clientes a descubrir soluciones de AI mejores, más rápidas y más eficientes energéticamente.

La hoja de ruta incluye tres áreas clave de desarrollo: Distribuciones Cuánticas para AI Generativa, Arquitecturas de Máquinas de Boltzmann Restringidas (RBM) y Integración de GPU con el servicio en la nube cuántica Leap. Estas iniciativas buscan apoyar diversas aplicaciones, desde el descubrimiento molecular hasta la ciberseguridad y el análisis de datos de física de alta energía.

Los primeros casos de uso de los clientes han mostrado resultados prometedores, con investigadores en Alemania, TRIUMF en Canadá y Honda Innovation Lab en Japón demostrando un rendimiento y eficiencia mejorados al utilizar la tecnología cuántica de D-Wave para tareas de AI y aprendizaje automático.

D-Wave Quantum Inc. (NYSE: QBTS)가 양자 AI 솔루션에 중점을 둔 제품 개발 로드맵의 확장을 발표했습니다. 이는 더 효율적인 AI 및 머신러닝 작업에 대한 증가하는 수요를 해결하기 위한 것입니다. 이 회사는 고객이 더 나은, 더 빠르며 에너지 효율적인 AI 솔루션을 발견할 수 있도록 어닐링 양자 컴퓨팅 능력을 활용하는 것을 목표로 하고 있습니다.

로드맵에는 세 가지 주요 개발 분야가 포함되어 있습니다: 생성 AI를 위한 양자 분포, 제한 볼츠만 머신(RBM) 아키텍처, 및 Leap 양자 클라우드 서비스와의 GPU 통합. 이러한 이니셔티브는 분자 발견, 사이버 보안, 고에너지 물리 데이터 분석 등 다양한 응용 프로그램을 지원하는 것을 목표로 하고 있습니다.

초기 고객 사례는 독일의 연구자들, 캐나다의 TRIUMF, 일본의 혼다 이노베이션랩이 D-Wave의 양자 기술을 사용하여 AI 및 머신러닝 작업에서 성능과 효율성이 개선된 사례를 보여주며 유망한 결과를 보였습니다.

D-Wave Quantum Inc. (NYSE: QBTS) a annoncé une extension de sa feuille de route de développement de produits, se concentrant sur solutions d'IA quantique pour répondre à la demande croissante d'un traitement plus efficace de l'IA et des tâches d'apprentissage automatique. L'entreprise vise à tirer parti de ses capacités de calcul quantique par recuit pour aider ses clients à découvrir des solutions d'IA meilleures, plus rapides et plus économes en énergie.

La feuille de route comprend trois axes de développement clés : Distributions quantiques pour l'IA générative, Architectures de machines de Boltzmann restreintes (RBM) et Intégration des GPU avec le service cloud quantique Leap. Ces initiatives visent à soutenir diverses applications, de la découverte moléculaire à la cybersécurité et à l'analyse des données de physique des hautes énergies.

Les premiers cas d'utilisation clients ont montré des résultats prometteurs, avec des chercheurs en Allemagne, TRIUMF au Canada et le Honda Innovation Lab au Japon démontrant des performances et une efficacité améliorées en utilisant la technologie quantique de D-Wave pour les tâches d'IA et d'apprentissage automatique.

D-Wave Quantum Inc. (NYSE: QBTS) hat eine Erweiterung seiner Produktentwicklungsstrategie angekündigt, die sich auf Quantum AI Lösungen konzentriert, um der wachsenden Nachfrage nach effizienteren AI- und Machine-Learning-Arbeitslasten gerecht zu werden. Das Unternehmen hat sich zum Ziel gesetzt, seine annealing-quantencomputing Fähigkeiten zu nutzen, um den Kunden dabei zu helfen, bessere, schnellere und energieeffizientere AI-Lösungen zu entdecken.

Die Roadmap umfasst drei Schlüsselentwicklungsbereiche: Quantenverteilungen für generative AI, eingeschränkte Boltzmannmaschinen (RBM)-Architekturen und GPU-Integration mit dem Quantum-Cloud-Service Leap. Diese Initiativen zielen darauf ab, verschiedene Anwendungen zu unterstützen, von der molekularen Entdeckung über Cybersicherheit bis hin zur Analyse von Hochenergiephysikdaten.

Frühe Anwendungsfälle von Kunden haben vielversprechende Ergebnisse gezeigt, wobei Forscher in Deutschland, TRIUMF in Kanada und das Honda Innovation Lab in Japan eine verbesserte Leistung und Effizienz bei der Nutzung der Quanten-technologie von D-Wave für AI- und maschinelles Lernen nachgewiesen haben.

Positive
  • Expansion of product development roadmap to include Quantum AI solutions
  • Potential for reduced energy consumption in AI model training and execution
  • Early customer use cases showing improved performance and efficiency using D-Wave's quantum technology
  • Integration of GPU resources into the Leap quantum cloud service for enhanced AI model support
Negative
  • None.

D-Wave's announcement of extending its Leap quantum cloud service for AI/ML applications is a significant development in the quantum computing landscape. While the news doesn't provide immediate financial impact, it positions D-Wave strategically in the rapidly growing AI market.

The company's focus on three key areas - Quantum Distributions for Generative AI, Restricted Boltzmann Machine (RBM) Architectures and GPU Integration - demonstrates a comprehensive approach to addressing current AI challenges. The potential for reduced energy consumption and improved efficiency in AI model training could be particularly appealing to businesses grappling with the increasing computational demands of AI workloads.

However, it's important to note that these developments are still in the roadmap stage. The real test will be in the successful implementation and adoption of these technologies by customers. The examples provided, such as improved protein-DNA binding prediction and particle-calorimeter interaction simulation, show promising early results but are still in research phases.

For investors, this roadmap expansion signals D-Wave's commitment to staying competitive in the quantum computing market by aligning with AI trends. However, the long-term impact on the company's financial performance remains to be seen, as quantum computing is still an emerging technology with uncertain timelines for widespread commercial adoption.

D-Wave's initiative to bridge quantum computing with AI and ML is an intriguing development in the tech sector. The company's approach targets a critical pain point in the AI industry: the escalating computational and energy requirements for complex AI workloads.

The proposed Quantum AI solutions aim to leverage quantum annealing's optimization capabilities to enhance AI and ML processes. This could potentially lead to more efficient and accurate model training, which is important as AI models become increasingly complex and data-intensive.

Of particular interest is the development of Quantum Distributions for Generative AI. This could open up new possibilities in fields like molecular discovery, potentially accelerating drug development processes. The integration of GPUs into the Leap quantum cloud service is also noteworthy, as it could facilitate more seamless hybrid quantum-classical computing workflows.

However, it's important to temper expectations. While early results from partners like TRIUMF and Honda Innovation Lab are promising, showing significant speed-ups and improved accuracy, these are still primarily research-stage applications. The challenge lies in translating these successes into commercially viable products that can compete with or complement classical AI solutions.

Investors should view this as a long-term strategic move by D-Wave. The potential is significant, but realizing it will require continued investment in R&D and successful partnerships with industry leaders to drive adoption.

D-Wave's expansion into Quantum AI solutions comes at a important juncture in the AI industry. With the rapid growth of AI applications, particularly in generative AI, there's an increasing demand for more efficient computing solutions to handle complex AI workloads.

The market opportunity here is substantial. According to recent reports, the global AI market size was valued at $119.78 billion in 2022 and is projected to grow at a CAGR of 37.3% from 2023 to 2030. D-Wave's focus on addressing energy efficiency and computational power in AI could potentially capture a significant portion of this growing market.

However, it's important to consider the competitive landscape. Tech giants like Google, IBM and Microsoft are also investing heavily in quantum computing and its applications in AI. D-Wave will need to demonstrate clear advantages and use cases to stand out in this crowded field.

The company's partnerships and early results with organizations like TRIUMF and Honda Innovation Lab are encouraging signs of industry interest. These collaborations could pave the way for broader adoption if they lead to tangible benefits in real-world applications.

For investors, this move represents a potential diversification of D-Wave's revenue streams. However, it's important to monitor the timeline for commercialization of these Quantum AI solutions and their adoption rates among enterprise customers. The quantum computing market is still in its early stages and while the potential is immense, the path to profitability may be long and uncertain.

Including support for quantum-enhanced and energy efficient AI model training as well as integrating AI and optimization to address important customer use cases

PALO ALTO, Calif.--(BUSINESS WIRE)-- D-Wave Quantum Inc. (NYSE: QBTS) (“D-Wave” or the “Company”), a leader in quantum computing systems, software, and services and the world’s first commercial supplier of quantum computers, today announced it is strengthening the connection between quantum optimization, artificial intelligence (AI), and machine learning (ML), by extending its product development roadmap with enhancements to the Leap™ quantum cloud service that will bring new Quantum AI solutions to market. The roadmap is intended to help customers address a variety of AI/ML workloads including pre-training optimization, more accurate and efficient model training, and opening new AI business use cases that require the integration of AI and business optimization, such as quantum supply chain optimization to support AI-predicted product demand requirements.

In response to growing demand from its customers, D-Wave’s Quantum AI development initiative comes at a time when the broader AI industry is confronting a computing crunch. The amount of compute and the associated energy costs needed to satisfy a growing set of use cases is rapidly escalating. D-Wave’s Quantum AI solutions aim to leverage annealing quantum computing’s unique capability in solving optimization problems to help customers discover better, faster and more energy efficient AI and ML workloads.

D-Wave is announcing a new Quantum AI extension to its product development roadmap, focused on three key development areas:

  • Quantum Distributions for Generative AI: Development in this area is focused on designing novel, modern generative AI architectures that directly use quantum processing unit (QPU) samples from quantum distributions that cannot be generated classically. Initially focused on molecular discovery use cases, we believe there is immense potential in harnessing quantum distributions for a broad array of generative AI applications.
  • Restricted Boltzmann Machine (RBM) Architectures: A growing set of customers are exploring new RBM architectures that directly leverage D-Wave’s QPU for applications ranging from cybersecurity to drug discovery and high-energy physics data analysis, which could potentially lead to reduced energy consumption in training and running AI models. D-Wave plans to ensure that the quantum and hybrid-quantum solvers available in the Leap cloud service support these emerging applications.
  • GPU Integration with the Leap Quantum Cloud Service: D-Wave is augmenting the Leap quantum cloud service by incorporating additional graphics processing unit (GPU) resources for the training and support of AI models alongside optimization workloads. In addition, efforts are underway to further reduce latency between QPUs and classical computing resources, a critical step in enabling hybrid-quantum technology for AI/ML.

Specific customer use cases related to D-Wave’s Quantum AI solutions include:

  • As a pioneering example of improving biological data analysis, researchers in Julich, Germany, used D-Wave’s quantum technology to develop a machine learning tool that predicts protein-DNA binding with greater accuracy than traditional methods. The team integrated quantum computing with support vector machines to achieve improved results in various metrics, significantly enhancing classification performance.
  • TRIUMF, Canada's particle accelerator center, and its partner institutions, are showing significant speed-ups of D-Wave’s QPU over classical approaches for simulating high-energy particle-calorimeter interactions – potentially leading to major efficiencies where the AI model is used to create synthetic data.
  • Honda Innovation Lab and Tohoku University developed a method to fine-tune D-Wave’s quantum computers to generate highly accurate samples for training RBMs. This approach yielded better results than traditional algorithms and significant improvements in model performance.

“We’re seeing early evidence that annealing quantum computing could play a key role in helping AI/ML with more efficient model training, reduced energy consumption and faster time-to-solution,” said Dr. Alan Baratz, CEO of D-Wave. “With results demonstrating our annealing quantum computer’s ability to outperform classical techniques, coupled with rapidly increasing demand from our customers for Quantum AI solutions that integrate with their business optimization requirements, we believe the impact of D-Wave’s Quantum AI solutions could be transformative, bringing a powerful new set of new computing tools for generative AI.”

About D-Wave Quantum Inc.

D-Wave is a leader in the development and delivery of quantum computing systems, software, and services, and is the world’s first commercial supplier of quantum computers—and the only company building both annealing quantum computers and gate-model quantum computers. Our mission is to unlock the power of quantum computing today to benefit business and society. We do this by delivering customer value with practical quantum applications for problems as diverse as logistics, artificial intelligence, materials sciences, drug discovery, scheduling, cybersecurity, fault detection, and financial modeling. D-Wave’s technology has been used by some of the world’s most advanced organizations including Mastercard, Deloitte, Davidson Technologies, ArcelorMittal, Siemens Healthineers, Unisys, NEC Corporation, Pattison Food Group Ltd., DENSO, Lockheed Martin, Forschungszentrum Jülich, University of Southern California, and Los Alamos National Laboratory.

Forward-Looking Statements

Certain statements in this press release are forward-looking, as defined in the Private Securities Litigation Reform Act of 1995. These statements involve risks, uncertainties, and other factors that may cause actual results to differ materially from the information expressed or implied by these forward-looking statements and may not be indicative of future results. These forward-looking statements are subject to a number of risks and uncertainties, including, among others, various factors beyond management’s control, including the risks set forth under the heading “Risk Factors” discussed under the caption “Item 1A. Risk Factors” in Part I of our most recent Annual Report on Form 10-K or any updates discussed under the caption “Item 1A. Risk Factors” in Part II of our Quarterly Reports on Form 10-Q and in our other filings with the SEC. Undue reliance should not be placed on the forward-looking statements in this press release in making an investment decision, which are based on information available to us on the date hereof. We undertake no duty to update this information unless required by law.

D-Wave

Alex Daigle

media@dwavesys.com

Source: D-Wave Quantum Inc.

FAQ

What are the key development areas in D-Wave's new Quantum AI roadmap?

D-Wave's new Quantum AI roadmap focuses on three key development areas: Quantum Distributions for Generative AI, Restricted Boltzmann Machine (RBM) Architectures, and GPU Integration with the Leap quantum cloud service.

How does D-Wave (QBTS) plan to address the computing crunch in the AI industry?

D-Wave aims to leverage its annealing quantum computing capabilities to help customers discover better, faster, and more energy-efficient AI and ML workloads, potentially reducing the amount of compute and associated energy costs needed for AI applications.

What are some early customer use cases for D-Wave's Quantum AI solutions?

Early customer use cases include researchers in Germany improving biological data analysis, TRIUMF in Canada accelerating high-energy particle-calorimeter simulations, and Honda Innovation Lab enhancing Restricted Boltzmann Machine training using D-Wave's quantum computers.

How does D-Wave (QBTS) plan to integrate AI and business optimization?

D-Wave plans to integrate AI and business optimization by developing solutions such as quantum supply chain optimization to support AI-predicted product demand requirements, addressing important customer use cases.

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