A Strategic History of Quantum Technologies in the 20th & 21st Centuries: Assembled through the strategic lens championed by Brian Lenahan

by danikahannon696f7af778 with No Comment Brian Lenahan Danika Hannon Quantum Strategy

NOTE: Brian Lenahan, Founder & Chair of QSI, is known primarily for his contributions to quantum strategy, AI, and emerging technologies, especially in the 21st century. His work focuses on bridging the gap between business and quantum innovation, including through the Quantum Strategy Institute (QSI) which he founded. The following is a compilation that uses Lenahan’s themes—especially around commercialization, strategy, and future applications—to frame a history of quantum technologies in the 20th century.

Introduction: Framing Quantum’s History with Strategy in Mind

Brian Lenahan’s work consistently emphasizes the importance of translating quantum potential into real-world value. In retrospect, we can apply this lens to the 20th-century evolution of quantum technologies—not simply as a chronology of scientific breakthroughs, but as a strategic progression: from theoretical foundations to industrial interest.

1900s–1920s: The Quantum Awakening

Max Planck (1900) introduced the concept of quantized energy, setting the groundwork.
Albert Einstein (1905) explained the photoelectric effect using quantized light.
Niels Bohr and Werner Heisenberg advanced early quantum theory.

Strategic Insight: At this stage, quantum theory had no commercial strategy—it was pure science, but the seeds were planted. Lenahan views this as a foundational “discovery phase”, where key paradigms emerge but value extraction is undefined.

1930s–1950s: Quantum Theory Matures

Development of quantum electrodynamics (QED) and the formulation of the Copenhagen interpretation.
Early applications began to appear in nuclear physics, radar, and solid-state physics.
Bell’s Theorem and hidden variable debates surfaced.

Strategic Insight: Here we begin the “validation phase”—Lenahan highlights this as a time when theoretical quantum principles began influencing macro-level technologies (like nuclear energy), even though “quantum” was not yet a commercial term.

1960s–1980s: From Physics to Engineering

The laser and transistor—products of quantum physics—saw mass adoption.
Quantum chemistry matured with computational methods.
IBM and Bell Labs initiated early quantum research.
Feynman (1981) proposed quantum computers.

Strategic Insight: This era represents what Lenahan calls a “hidden quantum era”—quantum was under the hood of many emerging technologies, but not yet branded or understood by the business world. He would stress this as a missed opportunity to create narrative and economic momentum.

1990s: Quantum Information Science Emerges

Peter Shor (1994) demonstrated quantum algorithms that could revolutionize computing.
Quantum cryptography and entanglement experiments gained traction.
The term “quantum advantage” entered the discourse.

Strategic Insight: Lenahan’s strategic lens saw this decade as the birth of quantum value narratives—when investors and institutions first saw glimpses of how quantum could disrupt entire industries (e.g., finance, cybersecurity). He referred to this as the “awakening of commercialization potential”, though actual business models remained speculative.

Foundations for the Quantum Century

By the year 2000, the scientific groundwork was laid. The next step—where Lenahan’s real influence begins—is the translation of theory into strategy. He argued that the 20th century’s main quantum legacy was knowledge without vision, and that the 21st century must focus on vision with execution.

Strategic Rise of Quantum in the 21st Century

The 21st century marks the transition of quantum technologies from academic curiosity to commercial momentum. Through the strategic lens of Brian Lenahan, this period can be seen as the realization of potential laid during the 20th century-where governments, enterprises, and startups begin investing heavily in quantum futures.

2000s: Foundations of a Quantum Ecosystem

Early 21st-century research expanded quantum computing architectures-trapped ions, superconducting qubits, and photonic approaches gained attention. Governments launched major initiatives like the EU’s Quantum Flagship and DARPA’s quantum programs.

Strategic Insight: Lenahan categorizes this as the ‘infrastructure and exploration phase’, with industry observing but not yet acting decisively.

2010s: Momentum and Corporate Entry

Key developments include IBM’s quantum cloud access (2016), Google’s quantum supremacy claim (2019), and the formation of quantum startups like Rigetti, Xanadu, and IonQ. The rise of hybrid quantum-classical algorithms and increased funding put quantum on the business map.

Strategic Insight: This was the ‘commercial curiosity phase’, where strategic players began aligning roadmaps with quantum timelines. Lenahan emphasized education, awareness, and early ecosystem development.

2020s: Commercialization, Platforms, and Ecosystem Building

This decade sees explosive growth in quantum commercialization: IPOs (IonQ), cloud platforms (AWS Braket, Azure Quantum), and national initiatives (U.S. National Quantum Initiative, Canada’s NRC programs). Use cases in finance, pharma, and materials begin pilot testing.

Strategic Insight: Lenahan sees this as the ‘value extraction phase’. Strategy moves from observation to implementation. QSI and other cross-sector collaborations emerge to guide businesses on use cases, readiness, and ethical frameworks.

From Theory to Transformation

In the 21st century, quantum technology evolved from research labs into boardrooms. Brian Lenahan’s voice has been instrumental in helping organizations navigate uncertainty, define value, and take actionable steps. The strategic framing he champions turns a complex technology into a meaningful journey toward transformation.

Looking Ahead: 2030 and Beyond

As fault-tolerant quantum systems approach viability, the next decade will be about scalability, regulation, and societal integration. Strategy will focus on workforce development, responsible innovation, and hybrid architectures. Lenahan’s strategic foresight continues to inform these transitions.

How Brian Lenahan Extends This Legacy

Books like Quantum Boost and Quantum Strategy connect quantum science with practical applications.
His Quantum Strategy Institute (QSI) brings together cross-disciplinary experts to define roadmaps for quantum readiness and to unify scientists, entrepreneurs, and strategists.
Encouraged nations and organizations to prepare for the ‘Quantum Age’ with education.

Emphasis on SMEs and emerging markets, ensuring quantum is not just for tech giants.
He champions quantum education, preparing society for deep tech transitions through his Substack newsletter, Quantum’s Business

References:

Primary Quantum Science and History Sources

Planck, M. (1901). On the Law of Distribution of Energy in the Normal Spectrum. Annalen der Physik.
Einstein, A. (1905). On a Heuristic Viewpoint Concerning the Production and Transformation of Light.
Bohr, N. (1913). On the Constitution of Atoms and Molecules.
Heisenberg, W. (1927). The Physical Content of Quantum Kinematics and Mechanics.
Dirac, P. A. M. (1930). The Principles of Quantum Mechanics.
Feynman, R. P. (1982). Simulating Physics with Computers. International Journal of Theoretical Physics.
Shor, P. W. (1994). Algorithms for Quantum Computation: Discrete Logarithms and Factoring. Proceedings of the 35th Annual Symposium on Foundations of Computer Science.
Bell, J. S. (1964). On the Einstein Podolsky Rosen Paradox. Physics Physique.

Quantum Technology Development

Gilder, L. (2008). The Age of Entanglement: When Quantum Physics Was Reborn. Vintage.
Kumar, M. (2008). Quantum: Einstein, Bohr, and the Great Debate About the Nature of Reality.
Deutsch, D. (1997). The Fabric of Reality. Penguin Books.
Nielsen, M. A., & Chuang, I. L. (2000). Quantum Computation and Quantum Information. Cambridge University Press.

Brian Lenahan and Quantum Strategy

Lenahan, B. (2020). Quantum Boost: Using Quantum Computing to Supercharge Your Business.
Lenahan, B. (2021). Quantum Strategy: How to Realize Value from Quantum Computing.
Lenahan, B. (2022). Leadership for the Future of Quantum Technology.
Quantum Strategy Institute (QSI). Website: www.quantumstrategyinstitute.com
Quantum’s Business substack: brianlenahan.substack.com

Supporting Themes and Strategic Insight

Arute, F. et al. (2019). Quantum Supremacy Using a Programmable Superconducting Processor. Nature.

National Quantum Initiative Act (USA, 2018).
ETSI Industry Specification Group for Quantum Key Distribution (QKD).
McKinsey & Co. (2023). The Real Value of Quantum Computing for Business.

Export Controls & Quantum Technologies

by danikahannon696f7af778 with No Comment Brian Lenahan National Strategies Petra Soderling Quantum Risk Quantum Strategy

The Quantum Strategy Institute’s new report, by Petra Soderling and Brian Lenahan, analyzes the drivers and effects of introducing export controls in the quantum sector. As governments seek to safeguard national security and strategic economic interests, these policies can have far-reaching effects on global collaboration, innovation, and talent mobility.

The report explores the complex balance between protecting critical technologies and supporting a thriving, internationally connected quantum ecosystem, read it here: Export Controls & Quantum Technologies.

Report Authors

Petra Soderling

Petra Söderling, Head of Government and Consortium Relations at the Quantum Strategy Institute (QSI).

Petra Söderling has over 25 years of experience in the technology industry, having held key positions in standardization, open source, research, and product management at Nokia. She has an MBA from Helsinki University of Technology, and executive education from Harvard Business School and Stanford University.

Being Finnish-American, she has been instrumental in ramping up trans-Atlantic relationships in quantum since 2020. She is also a key contributor to EU’s quantum strategy, financing, standardization, and international relations. Petra Söderling is the author of Government and Innovation – the Economic Developer’s Guide to our Future.

Brian Lenahan

Brian Lenahan, Brian Lenahan is Founder & Chair of the Quantum Strategy Institute and the author of seven published books on quantum technologies and artificial intelligence.

He is a recognized speaker and moderator at conferences around the world and a global consultant on the strategy of road mapping quantum and AI tech adoption. He is the author of Quantum’s Business Substack, enjoyed by thousands of readers in over 90 countries.

Brian is a three-time LinkedIn Quantum Top Voice. He leverages all of his media platforms to augment the work of QSI in accelerating the adoption of quantum technologies worldwide.

Unlocking the Future: The Synergy of Generative AI and Quantum Computing

by brianlenahanqsichair with No Comment Joe Ghalbouni

What is generative AI?

Generative AI is a subset of artificial intelligence that focuses on creating new content, such as text, images, music, and even complex data sets, by learning patterns from existing data. It leverages deep learning models, particularly neural networks, to generate outputs that mimic the characteristics of the training data. For C-level executives, understanding generative AI is crucial as it is transforming numerous industries by automating creative and repetitive tasks, enhancing decision-making processes, and unlocking new revenue streams.

Generative AI is making significant impacts across various verticals:

Healthcare: Automating medical image analysis, creating personalized treatment plans, and generating synthetic data for research.
Finance: Enhancing fraud detection systems, creating financial models, and generating reports and insights.
Retail: Personalizing customer experiences, optimizing supply chain management, and generating product descriptions.
Entertainment: Creating realistic graphics, animations, and special effects, as well as generating music and scripts.
Manufacturing: Optimizing product designs, predictive maintenance, and quality control through synthetic data generation.

The ChatGPT moment

ChatGPT, developed by OpenAI and based on the GPT model, marked a significant milestone in making generative AI mainstream. Its ability to engage in coherent and contextually relevant conversations captured the public’s imagination and showcased the potential of AI in everyday applications. ChatGPT’s success demonstrated the feasibility of AI-powered chatbots in customer service, virtual assistance, and content creation.

Since its debut, generative AI has made considerable progress. The models have become more sophisticated, capable of handling complex tasks and generating more accurate and context-aware content. Below is a graph illustrating the evolution of large language models over the years.

Figure 1- Evolution of large language models over the years – Image courtesy of https://www.analyticsvidhya.com/blog/2023/07/beginners-guide-to-build-large-language-models-from-scratch/

Accelerating quantum with generative AI

Quantum computing, a field poised to revolutionize computation, faces challenges in algorithmic development particularly while scaling and taking into account the different backends to execute on. Due to its complexity, it also requires at the moment very advanced skills making it difficult for adoption. Generative AI can accelerate quantum computing development in several ways:

Training Models on Quantum Code: Generative models trained on quantum code can help automate the process of writing and optimizing quantum algorithms, speeding up research and development cycles. Most models today like GPT-4, Gemini Pro 1.5, Claude 3 Opus and Meta Llama 3 are capable of handling these tasks.
Fine-Tuning Models: Generative AI can fine-tune quantum computing models by simulating various scenarios and optimizing parameters, which is critical for advancing quantum research. An example is ketGPT, a generative AI model designed to assist in quantum computing benchmarks (reference: https://arxiv.org/abs/2402.13352).
Nvidia Quantum Cloud: Nvidia leverages generative AI in its Quantum Cloud platform to enhance quantum simulations and improve the efficiency of quantum hardware. This integration showcases how generative AI can support the development and application of quantum computing technologies (reference: https://nvidianews.nvidia.com/news/nvidia-launches-cloud-quantum-computer-simulation-microservices).

What can we learn from the generative ai momentum?

The momentum behind generative AI offers valuable lessons for the adoption and integration of quantum computing technologies:

Resilience and Recovery: Despite experiencing periods of stagnation, AI has demonstrated resilience and the ability to recover, driven by innovative applications and user-friendly interfaces.
User-Friendly Applications: The popularity of AI surged because people could use it without needing in-depth technical knowledge of neural networks or deep learning. This ease of use is crucial for widespread adoption.
Seamless Integration: For quantum computing to gain similar traction, it must seamlessly integrate into existing workflows across various industries. Technologies should be designed to fit naturally into users’ processes, reducing the learning curve. Examples include:
- Finance:
  - Microsoft Excel: Widely used for financial modeling and analysis.
  - Bloomberg Terminal: Provides real-time market data and analytics.
  - QuantConnect: An algorithmic trading platform that supports quantitative finance research and trading strategies.
- Healthcare:
  - Epic Systems: A comprehensive EHR (Electronic Health Record) system used by healthcare providers.
  - Cerner: Another leading EHR platform that integrates various healthcare data.
  - IBM Watson Health: Utilizes AI to analyze large volumes of healthcare data for insights and decision-making.
- Logistics:
  - SAP Supply Chain Management: Software for managing and optimizing supply chain processes.
  - Oracle Transportation Management: A solution for managing and optimizing logistics and transportation operations.
  - Manhattan Associates: Provides supply chain and inventory management solutions.
- Energy:
  - Siemens EnergyIP: A smart grid analytics platform that helps utilities manage energy distribution.
  - GE Predix: An industrial IoT platform that enables data analysis for energy efficiency and operational optimization.
  - Schneider Electric EcoStruxure: Offers energy management and automation solutions for various energy sectors.
- Chemistry:
  - Schrödinger Suite: Software for molecular modeling and drug design.
  - Gaussian: A computational chemistry software used for electronic structure modeling.
  - ChemAxon: Provides cheminformatics solutions for chemical data analysis and visualization.

These real-life examples illustrate how quantum computing solutions can be integrated into widely used software across various industries, making the technology more accessible and practical for end-users. By following a similar approach, quantum computing can leverage the momentum of generative AI to achieve widespread adoption and impact.

Quantum Computing as a generative AI horizon?

Quantum generative AI, particularly through quantum neural networks (QNNs), has the potential to significantly enhance generative AI capabilities. QNNs can process and generate complex data sets more efficiently than classical neural networks, opening new horizons for AI applications.

Several peer-reviewed studies highlight the potential of quantum generative AI:

Quantum Neural Networks: Research indicates that a class of quantum neural networks (QNNs) can achieve a significantly better effective dimension than comparable classical feedforward networks, suggesting they may train faster and generalize better on new data. This advantage is highlighted by the effective dimension measure, which captures a model’s ability to generalize and train effectively. These findings have been demonstrated numerically and verified on real quantum hardware, suggesting potential benefits for quantum machine learning (reference: https://www.nature.com/articles/s43588-021-00084-1).
Generative Models: Studies indicate that quantum generative models can produce more accurate and diverse outputs compared to classical counterparts, particularly in high-dimensional data spaces (reference: https://zapata.ai/new-research-shows-how-quantum-generative-models-can-outperform-classical-models/).
Computational Efficiency: Research demonstrates that fault-tolerant quantum computing could significantly improve the efficiency of training large machine learning models, which are typically constrained by high computational costs, power consumption, and time requirements. By leveraging efficient quantum algorithms for stochastic gradient descent, quantum computing can potentially scale more efficiently with model size and iterations, especially for models that are sufficiently dissipative and sparse. Practical benchmarks of large machine learning models, ranging from 7 million to 103 million parameters, indicate that quantum enhancement is possible during the early stages of learning after model pruning. This suggests that quantum algorithms could contribute effectively to training large-scale machine learning models, offering a promising solution to current computational bottlenecks. (reference: https://www.nature.com/articles/s41467-023-43957-x) .

As we continue to explore the intersection of generative AI and quantum computing, it becomes evident that the synergy between these technologies could unlock unprecedented advancements in AI, driving innovation and efficiency across various sectors.

Conclusion

Drawing from my nearly 15 years of experience in the quantum computing ecosystem, I have witnessed firsthand the challenges and triumphs of transitioning cutting-edge technology from the lab to practical, industry-wide application. One critical lesson we can learn from the generative AI momentum is the importance of seamless integration and user-friendly interfaces. For quantum computing to achieve similar success, it must be designed to fit naturally into existing workflows and frameworks, providing robust support and ease of use without requiring deep technical knowledge of its inner mechanisms.

The success of generative AI, epitomized by models like ChatGPT, demonstrates that technology adoption accelerates when the user experience is prioritized. People can leverage powerful AI tools without needing to understand the complexities of neural networks or deep learning algorithms. Similarly, quantum computing solutions must be packaged in a way that abstracts away the complexities of entanglement and superposition. These fundamental properties, while fascinating, do not resonate with a broader audience who are not experts in quantum physics.

To sell a successful quantum solution, we need to focus on the tangible benefits and practical applications that directly impact business outcomes. Just as generative AI has done, quantum computing must offer intuitive interfaces and seamless integration into the tools and platforms already familiar to industry professionals. This approach not only simplifies adoption but also drives meaningful innovation and efficiency improvements across various sectors.In conclusion, the journey from laboratory to production for quantum computing hinges on our ability to learn from the success of generative AI. By prioritizing ease of use, seamless integration, and practical value, we can ensure that quantum computing becomes an indispensable tool for businesses, driving the next wave.

How Europe Prepares Itself Against Quantum Threats: Part Three in QSI’s Series on Global Cryptography Reports

by brianlenahanqsichair with No Comment Danika Hannon Petra Soderling Quantum Cryptography Quantum Risk Quantum Strategy

Introduction to QSI’s Post-Quantum Cryptography Series

Governments around the world are beginning to prepare themselves for the quantum threat. Even though quantum computers may not be prevalent in any commercial sense in years, national security requires for sensitive data and documents to be quantum proof well in advance. No one wants their opponents to get access to five-year-old, or even ten-year-old, sensitive material.

But how, exactly, are nations approaching post-quantum cryptography (PQC)?

In answering that question, QSI has released its third quantum cybersecurity report, titled How Europe Prepares Itself Against Quantum Threats: Part Three in QSI’s Series on Global Cryptography Reports.

Report Authors

Petra Soderling

Petra Söderling, Head of Government and Consortium Relations at the Quantum Strategy Institute (QSI).

Söderling is a Finnish American award-winning innovation leader who thinks that governments have an unrecognized role in creating new innovations, new industries even.

Söderling is currently an advisor with the World Bank on development and application of deep technologies. She is the author of Government and Innovation, a 2023 book that that looks at how local, regional, and national governments can use existing instruments to steer their economies to include more innovative industries that provide a higher economic value-add.

How Asian Countries are Addressing Post-Quantum Cryptography: Part Two in QSI’s Series on Global Cryptography Reports

by brianlenahanqsichair with No Comment Danika Hannon Petra Soderling Quantum Cryptography Quantum Risk Quantum Strategy

Introduction to QSI’s Post-Quantum Cryptography Series

But how, exactly, are nations approaching post-quantum cryptography (PQC)?

In answering that question, QSI has released its second quantum cybersecurity report, titled How Asian Countries are Addressing Post-Quantum Cryptography: Part Two in QSI’s Series of Global Cryptography Reports.

Report Authors

Petra Soderling

Petra Söderling, Head of Government and Consortium Relations at the Quantum Strategy Institute (QSI).

Söderling is a Finnish American award-winning innovation leader who thinks that governments have an unrecognized role in creating new innovations, new industries even.

Danika Hannon

Danika Hannon, Deputy Head and International Quantum Strategy Day Chair of QSI.

In her role with QSI, Hannon writes thought leadership on quantum computing and business development, plus she leads International Quantum Strategy Day, which features a global strategy competition.

Hannon was in the top 10 Top Quantum Voices in the 2024 international thought leadership ranking from Barcelona bqb. In addition, Hannon’s earning a Cybersecurity Master’s degree and will be graduating from the University of North Dakota in December 2024.

Featured Image - QSI's Report on Cryptography

QSI’s Report on Cryptography: Taking a Data-Driven Approach to the Quantum Computing Threat

by brianlenahanqsichair with No Comment Danika Hannon Quantum Cryptography Quantum Risk Quantum Strategy

New Year, New Perspectives

Reactions to the idea of quantum computing breaking encryption range from uncertainty (at best) to fear (at worst). Given how harmful that is to businesses, QSI’s Report on Cryptography breaks down the quantum computing threat from a US standpoint and explores these critical questions:

What types of encryption are at risk?
Where will the attacks come from and what will the targets be?
What are the timelines for this threat arriving?
How can my business prepare for this?

A data-driven approach is used to explore each of those areas.

Because if you’re going to face the changing landscape with confidence, then you’ll need fact-based guidance.

Report Authored by Danika Hannon

Danika Hannon is the Deputy Head and International Quantum Strategy Day Chair of QSI.

In her role with QSI, Hannon writes thought leadership on quantum computing and business development, plus she leads International Quantum Strategy Day, which features a global strategy competition. In addition to her work with QSI, Hannon’s earning a Cybersecurity Master’s degree and will be graduating from the University of North Dakota in December 2024.

Hannon also focuses on giving back to the tech community as both a speaker and a mentor. In 2024, she’ll be speaking at the Quantum Innovation Summit and South by Southwest. She’s recently been nominated for a Femtum Leap Award in Quantum Leadership and in 2022, she was nominated for VentureBeat’s Women in AI Awards in the Mentorship category. Added to that, she’s served as a mentor with Women in Quantum and Girls in Quantum.

Afterword by Chuck Brooks

Chuck Brooks has been named the “Top Tech Person to Follow” by LinkedIn, Voted “Cybersecurity Person of the Year”, Cited Top 10 Global Tech & Cyber Expert & Influencer, Georgetown University Professor, Two Time Presidential Appointee, FORBES writer, 113k LinkedIn Followers.

Brooks is the President of Brooks Consulting International and a Consultant with over 25 years of experience in cybersecurity, emerging technologies, marketing, business development, and government relations. He helps Fortune 1000 clients, organizations, small businesses, and start-ups achieve their strategic goals and grow their market share.

Brooks also serves as an Adjunct Professor at Georgetown University, where he teaches graduate courses on risk management, homeland security, and cybersecurity, and designed a certificate course on Blockchain technologies.

Exploring Quantum Industry Consortiums: Q-STAR

by brianlenahanqsichair with No Comment Petra Soderling Quantum Industry Relations Quantum Strategy

The Quantum Strategy Institute (QSI) is an international network of cross-domain experts with a rich and varied expertise. Tasked to accelerate the market adoption of quantum technologies, QSI looks at both enablers and hurdles businesses face in making these complex, forward looking decisions. We drive the exploration and further the understanding of the practical applications of quantum computing across industries and to help bridge the white space between potential and practicality.

For an industry that is on the verge of commercial expansion, this includes forming new industry consortiums, adding new working groups to existing consortiums, and forming interactive industry relationships with the policy making governments.

In this series of papers under QSI’s Government and Consortium Relations pillar, we’ll explore the global landscape of these initiatives. This paper, third in the series, introduces Q-STAR, Quantum Strategic Industry Alliance for Revolution. Q-STAR gathers Japanese companies and academic organizations under one roof to steer Japanese quantum research, development, and commercialization of quantum technologies into the future.

History

The alliance for officially formed in September 2021 as a voluntary organization by members of the Japanese high-tech industry. The founding meeting included a Japanese all-star team of Canon, Fujitsu, Hitachi, Mitsubishi Electric Corporation, Mitsui Sumitomo Insurance Company, Mizuho Financial Group, NEC, Nippon Telegraph and Telephone Corporation, Sumitomo Corporation, Toshiba, and Toyota Motor Corporation.

Japan has a long, successful history in creating and launching technological inventions. Many of the founding companies of Q-STAR have developed high tech products and services for decades. It was time to ensure this Japanese tradition also carries forward in the quantum era. The anticipation and expectation for quantum-led, or quantum adjacent technologies also brings upon as the realization that we all need to work together to create a safe and secure living environment for countries around the world. Japan’s innovation thread is tightly woven into this international fabric, so the Japanese industry is a natural party to take leadership in developments in and around quantum.

The goal for the alliance from the get-go was to leverage Japan’s technological superiority in materials, devices, measurement technology, computers, communications, simulations, and so on, and to create new industries through the provision of services that take advantage of these enablers. With the help of the alliance, Japan aims to become a firmly established “quantum technology innovation nation” on a global scale.

By demonstrating global leadership and promoting activities that contribute to the development of science and technology, Q-STAR will contribute to the realization of this “quantum technology innovation nation,” while promoting Japanese industry and strengthening its international competitiveness.

Since its founding meeting in September 2021, Q-STAR held monthly executive committee meetings quickly ramping up the organization and operations. By February 2022, the Alliance already had over 50 members, and on the World Quantum Day in April 2022, Q-STAR joined a global announcement with its peer organizations Quantum Industry Canada (QIC), Quantum Economic Development Consortium (QED-C), and European Quantum Industry Consortium (QuIC). Q-STAR’s establishment was already internationally recognized, although it only became a general incorporated association in May 2022 with full scale activities.

As said Mr. Taro Shimada, Representative Director, Association for Creation of New Industries by Quantum Technology (President and CEO, Toshiba Corporation):

“We aim to build a society that can use quantum technology without being conscious of it. In addition, we will accelerate the transition to quantum technology through industry-government-academia integration. Furthermore, in line with economic globalization, we will promote the globalization of quantum technology in order to accelerate the progress and practical application of quantum technology through international cooperation. Q-STAR aims to be a council that can contribute to the development of society by actively promoting cooperation with quantum-related organizations not only in Japan but also overseas, for the development of quantum technology and future social implementation.”

Since the official incorporation, the alliance has held three board meetings, spoken in a number of conferences, webinars, given academic lectures, and participated in international activities.

Organizational Structure

As a voluntary industry association, Q-STAR operates with the principle of rotating responsibility.

The organizational structure includes a Chairman, Vice Chairman, Board of Directors, and Executive Officers. The Chairman is at the top of the structure and oversees the alliance’s operations and strategic direction. The Vice Chairman supports the Chairman and may assume their responsibilities when necessary. The Board of Directors is responsible for making key decisions and setting policies. Executive Officers manage specific functional areas and implement the alliance’s strategies.

Industry Focus

Objectives

The strategy of Q-STAR is organized around a number of activities that support Japan’s overarching goal to become a quantum technology innovation nation. The alliance is to investigate and research general trends in quantum technology, including devices and materials, and share information among top management within industry so they stay informed and can take appropriate action. Similarly, the alliance conducts research and proposes where quantum technology can be applied to other industries in multiple fields.

Q-STAR is also the Japanese industry’s top resource when it comes to studying and understanding the needs to develop human resources in the country in order to make the most of its quantum technology advancements. Equally, this group will study and suggest systems and principles for intellectual property and standardization, ethics and trust required for the implementation of quantum technology.

The alliance is also tasked to cooperate with other organizations, both domestic and overseas, working in quantum-related areas, in order to promote Q-STAR’s objectives, raise public awareness, and make policy recommendations.

Subcommittees and Working Groups

The work that supports Q-STAR’s objectives is divided into subcommittees and working groups. All technical work resides in one of the five subcommittees, and non-technical work is within one of the eight working groups.

Each subcommittee is led by industry experts from that field.

Subcommittee on Quantum Wave and Quantum Probability Theory Applications

Tasked with exploring the creation of new industries using quantum amplitude estimation and optimization. The objective is to create industries with the potential to become mainstays in various areas while also spanning multiple industries, including the financial sector, which has a close affinity with these technologies.

Subcommittee on Quantum Superposition Applications

Tasked with taking a broad view of the systems, services, and businesses created by the application of quantum superposition, the most important capability of quantum computers. It will also examine changes in existing industries and industry structures that will result. By collaborating with users and vendors to draw a new image of society, the aim is to create new industries that will become future pillars and mainstays of industry, and that span multiple industries.

Subcommittee on Optimization and Combinatorial Problems

Tasked with using quantum-inspired computing technology (Ising Machine) that almost instantaneously selects the optimum solution from among an enormous number of combinations to solve diverse problems facing industry in areas including real-time prediction, efficiency, and optimization.

4. Subcommittee on Quantum Cryptography and Quantum Communications

Tasked with examining business use of quantum cryptography communication, a technology already available, and aim to open up a future pioneered by communications that guarantee information-theoretically security.

5. Quantum City Promotion Committee

This committee deepens use cases related to social infrastructure development that can be used to try the social implementation of quantum technology from various angles, create new industries through demonstration experiments, and aim for social implementation in Japan and overseas.

The supporting working groups are:

Policy Recommendation Working Group
Standardization Coordination and Proposal Working Group
Testbed Collaboration Working Group
R&D Collaboration Working Group
Overseas Industry Collaboration Working Group
Long-Term Roadmap Formulation Working Group
Legal and Compliance Working Group
Human Resource Development Working Group

International Collaboration

As the working language of Q-STAR is Japanese, there is a dedicated working group to ensure all members of the alliance will have a chance to network with their international colleagues. This is the Overseas Industry Collaboration Working Group.

US Economy & Quantum Computing Header Image

The US Economy & Quantum Computing: Short-Term Headwinds, Long-Term Opportunities

by brianlenahanqsichair with No Comment Danika Hannon Quantum Strategy

Selling quantum computing proofs of concept is hard under good economic conditions. As the US (which is currently the largest market for quantum computing¹) stares down a potential recession in quarter three or four of this year, the job of business development (BD) professionals in our industry is going to get harder.

But all things will pass with time. And while there are short-term headwinds facing the US market, long-term opportunities are already emerging.

We’ll explore both of those areas, starting with what’s near-term.

Short-Term Headwind One: Layoffs

The US tech sector has been hard-hit by layoffs in recent months. As of late June, 794 tech companies, including major employers like Google and Amazon, went through layoffs².

The quantum computing industry can’t afford to ignore the impacts this will likely have on our industry. Because according to the New York Times, teams that are working on bleeding edge, non-revenue generating projects are the ones who are getting laid off first.

“The shifting economy and executive transitions away from founders have ushered in a new era, and employees wonder: Is their leader marching them to make their mark on the future, or right off a cliff?” – The Perils of Working on a C.E.O.’s Pet Project, New York Times³.

Image Credit: The New York Times

Getting laid off is a painful life event that’s linked to negative health outcomes⁴. In all likelihood, these lay-offs will have a chilling effect on the risk appetites of both the people who lead innovation efforts and those around them.

If you’re not sure if the company you’re targeting has been impacted by layoffs, check the Worker Adjustment and Retraining Notification (WARN) Tracker database⁵ to see if the company has reported that they’re going to layoff employees within the next two months or if they’ve already laid off employees. (Enacted in 1988, the WARN Act is a US, federal law⁶ mandating that businesses with more than 100 employees must notify the government 60 days before they’re going to have mass layoffs.)

Short-Term Headwind Two: Increased Interest in AI, which is Taking Resources Away from Quantum Computing

In a LinkedIn post from May⁷, Sergio Gago (Managing Director of AI/ML and Quantum at Moody’s Analytics) was one of the first people to call out how AI is getting increased attention compared to quantum computing.

In expanding on his LinkedIn post, Gago said:

“From our position in the financial industry we see how many corporates are switching their efforts to this new shiny toy, Generative AI. This is not a surprise since the vast majority of companies did not have relevant budgets for Quantum to start with as we found in our recent report, or they have not seen bottlenecks in their processes. Generative AI provides tangible results today so we see how innovation teams are pivoting towards that.

At the same time, the question arises whether Quantum can do anything with Generative AI. We believe the answer is NO. These two technologies are in two completely separate horizons, and while it is possible that in the far future they could complement each other, today they belong to different fields.”

Note: Gagos’ quote referred to the Moody’s Analytics report on “Quantum Computing in Financial Services: A Business Leader’s Guide,” which you can download here⁸.

In digging into the data, Gago’s right.

For instance, take a look at findings from Google Trends⁹ and IOT Analytics_¹⁰:

Here’s data from Google⁹ comparing interest in quantum computing vs. AI between April and June of this year.

Image Credit: Google Trends

Among the US population, interest in AI surged in April and, even though it’s cycled up and down since then, the interest in AI is far higher than quantum computing. From a business leader standpoint, right now it makes more sense to invest in less risky projects, which gives AI an edge over quantum computing.

And in looking at data from a C-Suite perspective, IOT Analytics found a similar theme. After analyzing roughly 5,800 earnings calls and 3,000 public companies in Q4 2022 and Q1 2023, IOT Analytics found that quantum computing isn’t being talked about by CEOs¹⁰.

Image Credit: IOT Analytics Research

Short-Term Headwind Three: The Likelihood of a Recession in 2023

The Federal Reserve sets economic policy for the US and they’re intentional about what they say and how they say it, because the language Fed officials use has an immediate impact on markets. And they’re aware of their impact – in fact, the Federal Reserve Bank of Kansas wrote a report about how communications from the Federal Open Markets Committee are analyzed with natural language processing¹¹.

With that in mind, ING looked at guidance from the Federal Reserve and their prediction is that, “recessionary forces are building rapidly, which will lead to rising unemployment and inflation falling quickly through late 2023 into 2024.”¹²

If a recession hits, it’ll have wide-reaching impacts and decrease the appetite for quantum computing proofs of concept because of their high costs. (As a note for quantum computing startup leaders, here’s a LinkedIn post with industry-specific guidance on how to weather a recession¹³.)

Shifting Gears

The short-term outlook is bumpy, yet at the same time, layoffs and increasing interest in AI could create opportunities for quantum in the long-run.

Long-Term Opportunity One: Talent is Getting Redistributed

In an article from April, the Wall Street Journal reported that laid-off workers from large companies are changing their priorities; instead of looking for jobs with prestigious, brand-name businesses, those workers are now finding jobs with small to medium-sized companies because they offer more stability¹⁴.

The redistribution of highly skilled workers in new areas will mean that, as demand for quantum computing eventually grows, there’ll be more companies who have the in-house talent needed to tackle a quantum computing proof of concept.

Image Credit: The Wall Street Journal

Long-Term Opportunity Two: AI Will Open Doors for Quantum

In the World Economic Forum’s most recent Future of Jobs Report, one of their top five key findings was: “Within technology adoption, big data, cloud computing and AI feature highly on the likelihood of adoption.”¹⁵

As companies build out new capabilities, like AI, they’ll lay the ground work (such as upskilling their workforce¹⁶ and navigating change management¹⁷) that they’ll need to one day take on a quantum computing proof of concept.

Image Credit: World Economic Forum

Long-Term Opportunity Three: Quantum-Inspired Algorithms

Powered by AI chips, quantum-inspired algorithms are gaining consumer interest because of how they deliver increased performance without needing to be run on a quantum computer.

In a recent article for Reuters, industry leaders from SandBoxAQ and QCWare commented on how they’re using quantum-inspired algorithms to tackle chemistry problems on classical computers. In doing this, they’re bridging the gap between the promise of scalable, fault-tolerant quantum computers and the performance that’s available today¹⁸.

Moving Through the Changing BD Landscape

Closing a deal in the quantum computing industry has never been easy. In the coming months, it’s likely going to get harder and finding deals to close will be like finding diamonds in the rough: it can be done, but an even more thoughtful approach will be needed to close sales opportunities.

As a parting thought, how can the health of the industry be measured?

From a BD standpoint, the best way to gauge how companies are responding is to look at their financials.

Take financial reporting from Quantinuum¹⁹, Rigetti^{20, 21}, and IonQ^{22, 23}, for instance. All three companies have publicly available financial information, as shown in the graph below where all the figures are in the millions.

Between 2021 and 2022, all three companies had steady or increasing revenues. With that baseline data in mind, the most successful companies will refine their go-forward strategies to optimize resources, while finding short-term, revenue opportunities to weather impending storms. When quarterly reports for Q3 and Q4 2023 and annual reports for 2023 come out, quantitative and qualitative analysis can be done to see how each company has navigated the uncertainty of 2023 and how they’re positioning themselves to take advantage of emerging opportunities in the years to come.

References

Zion Market Research. Quantum Computing Market Size, Share, Growth Report 2030. January 16, 2023. https://www.zionmarketresearch.com/report/quantum-computing-market
NerdWallet. Tech Layoffs Really Are Rising, and Here’s Why. June 23, 2023. https://www.nerdwallet.com/article/finance/tech-layoffs
The New York Times. The Perils of Working on a C.E.O.’s Pet Project. March 8, 2023. https://www.nytimes.com/2023/03/08/technology/tech-big-bets-layoffs.html?unlocked_article_code=LwQZ2kYmrOwCJ2QczDL_l0I-uegF_CKVbRBe43LpO3obV1LSniDgGH_iPzPogfkbokXtUmqXcfqdmiFT0eHlNoxjbmuT7zivSi0HPRV_CZ0b9Wi3nkr7c2HZdPuULxfovzQS2T2PwsHMU7pzBVatWeP6P8EmVzzgNkOY7o_6clKWQOpHozkEHApiJgQkHvW7OPP2l9fDzdp13HRdQ7yK-Epq1UyaXgFMI2MJSrKeQ5wrV4qOFFPs4ll-XTzHnr3i1pDjv82_DDGcLry2T-xVjG513uW_ltmfYGfCQLcU8H7KvQS_W1dY21uqKwai2-unzCctEf1W1miWW0f51TxUMF_a&smid=url-share
American Psychological Association. The Toll of Job Loss. October 1, 2020. https://www.apa.org/monitor/2020/10/toll-job-loss
WARN Tracker. Layoff Insights from Public Records. https://www.warntracker.com/
U.S. Department of Labor Employment and Training Administration Fact Sheet. The Worker Adjustment and Retraining Notification Act. March 6, 2019. https://www.doleta.gov/programs/factsht/WARN_Fact_sheet_updated_03.06.2019.pdf
LinkedIn. Sergio Gago’s LinkedIn post. May 2023. https://www.linkedin.com/posts/sergiogh_quantumcomputing-artificialintelligence-activity-7048259482149150721-LI6O?utm_source=share&utm_medium=member_desktop
Moody’s Analytics. Quantum Computing in Financial Services: A Business Leader’s Guide. 2023. https://www.moodys.com/web/en/us/about/what-we-do/quantum-computing/quantum-survey-report.html
Google Trends. https://trends.google.com/trends/explore?date=2023-04-01%202023-06-30&geo=US&q=%2Fm%2F069kd,%2Fm%2F0mkz&hl=en
IOT Analytics. What CEOs Talked About in Q1/2023: Economic Uncertainty, Layoffs, and the Rise of ChatGPT. April 5, 2023. https://iot-analytics.com/what-ceos-talked-about-in-q1-2023/
Kansas City Federal Reserve. How You Say It Matters: Text Analysis of FOMC Statements Using Natural Language Processing. https://www.kansascityfed.org/Economic%20Review/documents/7577/erv106n1dohkimyang.pdf
ING. Federal Reserve Preview: A Final Hike as US Recession Fears Mount. April 23, 2023. https://think.ing.com/articles/federal-reserve-preview-a-final-hike-as-us-recession-fears-mount#a8
LinkedIn. Danika Hannon’s LinkedIn post. November 2022. https://www.linkedin.com/posts/danikahannon_futurefocused-resilient-quantumcomputing-activity-6988111501815332864-SVDB?utm_source=share&utm_medium=member_desktop
The Wall Street Journal. As Tech Jobs Disappear, Silicon Valley Veterans Reset Their Careers: Laid-Off Workers from Companies Such as Meta and Amazon Choose Stability Over Status. https://www.wsj.com/articles/as-tech-jobs-disappear-silicon-valley-veterans-reset-their-careers-dbdb983?st=2hix38tl7slrzpt&reflink=desktopwebshare_permalink
World Economic Forum. Future of Jobs Report 2023. May 2023. https://www3.weforum.org/docs/WEF_Future_of_Jobs_2023.pdf
Quantum Strategy Institute. Quantum Machine Learning: A Roadmap for Technologists. February 28, 2022. https://quantumstrategyinstitute.com/2022/02/28/quantum-machine-learning-a-roadmap-for-technologists/
Quantum Strategy Institute. Becoming a Quantum Company: A Change Management Approach for Quantum Technologies & the Quantum Mindset. November 11, 2021. https://quantumstrategyinstitute.com/2021/11/11/becoming-a-quantum-company/
Reuters. Waiting for Quantum Computers to Arrive, Software Engineers Get Creative. April 17, 2023. https://www.reuters.com/technology/waiting-quantum-computers-arrive-software-engineers-get-creative-2023-04-17/
Honeywell. Q4 2022 Earnings Release. February 2, 2023. https://honeywell.gcs-web.com/static-files/efecdfab-e5a6-4702-b837-606f4a82788f
Rigetti. Rigetti Computing Announces Financial Results for Fiscal Year 2021; Delivers 48% Year-over-Year Revenue Growth and Further Accelerates Business Momentum Through Technology Leadership. March 10, 2022. https://investors.rigetti.com/news-releases/news-release-details/rigetti-computing-announces-financial-results-fiscal-year-2021#:~:text=Financial%20Results%20for%20the%20Fiscal,for%20the%20fiscal%20year%202020
Rigetti. Rigetti Computing Reports Fourth-Quarter and Full-Year 2022 Results. March 27, 2023. https://investors.rigetti.com/news-releases/news-release-details/rigetti-computing-reports-fourth-quarter-and-full-year-2022
IonQ. IonQ Announces Full Year 2021 Financial Results and Provides Business Update. March 28, 2022. https://investors.ionq.com/news/news-details/2022/IonQ-Announces-Full-Year-2021-Financial-Results-and-Provides-Business-Update/#:~:text=2021%20Financial%20Highlights&text=IonQ%20achieved%20revenue%20of%20%242.1,as%20of%20December%2031%2C%202021
IonQ. IonQ Announces Fourth Quarter and Full Year 2022 Financial Results and Provides Business Update. March 30, 2023. https://investors.ionq.com/news/news-details/2023/IonQ-Announces-Fourth-Quarter-and-Full-Year-2022-Financial-Results-and-Provides-Business-Update/default.aspx

Finding Your Product Market Fit: Adding Unique Value in a Crowded Market

by brianlenahanqsichair with No Comment Danika Hannon Quantum Strategy

Have you ever attended a quantum computing conference and noticed that the vendor pitches sound … similar?

Broadly speaking, quantum computing companies with software offerings have the same business model of creating a solution to a challenging R&D problem that’s focused on quantum machine learning, optimization, or quantum chemistry.

Overall, this works well.

But put yourself in a consumer’s shoes and imagine that you’re at a quantum computing conference talking to vendors for the first time. If each vendor walked you through the same business model, it wouldn’t take long for them to start blurring together.

I speak from experience here. At one of my first quantum computing conferences, I made a point to talk with as many quantum computing vendors as I could and (even though I worked for a quantum computing company at the time) I had the gut-sinking realization that we all sounded the same.

Plus, with nearly 100 quantum computing companies listed on the Quantum Insider’s Market Intelligence Platform, it’s important to find a way to break through the noise.

As a vendor, you have two chances to stand out from the crowd when you’re talking to a new prospect. You can either already have a great product-market fit that’s uniquely suited for your prospect, or you can listen to your prospect’s ideas and turn them into products.

One Company, in Particular, is Excelling in this Area: D-Wave

Granted, their Launch Program business model follows the same key steps that many other software vendors do.

But since their launch in 1999, they’ve made 250+ early quantum applications for their clients. Essentially, each use case is a separate product that they offer.

When asked about what sets D-Wave’s products apart, they shared that:

“We bring a relentless customer focus to everything we do,” said Murray Thom, vice president of quantum business innovation at D-Wave. “Our motivation stems from the opportunity to harness powerful quantum computing technology to help customers find solutions to problems they’ve been unable to address. We’re not creating quantum products simply for the sake of innovation. We’re building quantum solutions that have real enterprise applicability and impact today. Together with our customers, we’ve produced quantum-hybrid applications that address a multitude of optimization challenges that cut across industries, including cost reduction, revenue growth, and operational effectiveness. Our quantum technology is being used to optimize supply chains, employee scheduling, e-commerce delivery, protein folding, fraud detection, and industrial manufacturing, just to name a few.”

To better understand D-Wave’s approach, look at their work with Save on Foods. It’s particularly striking because it’s clear that they deeply understood the challenges of the grocery industry, what mattered to the Save on Foods team, and how to prioritize what they cared about.

On YouTube, there’s a 15-minute video where an executive from Save on Foods, plus one of their data scientists, talked about what made this application so impactful for them. It’s an excellent guide on how to build a product from consumer insights and well-worth watching.

Building Your Own Product Expertise

To get a subject matter expert’s perspective on how to build products, I interviewed Tina Nguyễn, Senior Vice President, Director of Digital Transformation at Truist.

Her immediate advice was that innovators should follow the CIRCLES Method™ of product creation. While the online example walks through how to use this process during an interview, anyone can use this to bring a new product to market. And, as shown in the graphic below, this is an iterative process that’s entirely focused on your end customer.

*Image Source: the Impact Interview website*

During this seven step process, you should:

Comprehend the situation – what are the hardest problems to solve? How much does that problem cost on an annual basis? How is it affecting other areas of the business?
Identify your customer – look for one customer segment that your product would impact. Put yourself in their shoes, learn about what’s most important to them and how they view their business.
Report customer needs – after you’ve spoken to your customer segment, take your voice of the customer notes and boil them down into a single sentence user story. A template you can follow is: “As a <role>, I want <goal/desire> so that <benefit>.
Cut, through prioritization – tease out what’s a “must have” vs. a “nice to have” for your customer.
List solutions – as tempting as it may be to build a product based on your first idea, get creative and list at least two to three ideas.
Evaluate tradeoffs – consider what your product needs to address and what matters to your end user. For instance, it’d take more resources to develop, but would your client be willing to pay more if your product had a seamless user interface?
Summarize recommendations – analyze what you’ve learned, then get ready to go through the process again. As you continue learning about your end customer and the industry you’re serving, keep using the CIRCLES Method^TM to guide your roadmap.

Common Pitfalls to Avoid on Your Journey

Tina shared three, common mistakes that are made with the CIRCLES Method^TM.

People have a tendency to be too focused on what they’re good at because they spent so much time building those skills. By committing to one path, they restrict themselves from innovation.
Inventors who don’t empathize with their end users. A sign of this is when something amazing is built, but it doesn’t have much market adoption.
Not speaking the same language as your end customer. If you can’t put things into layman’s terms, in a way that your customer will understand, that shows you don’t understand the business impact.

Here’s a Challenge for You

Have you ever heard the joke about how to get to Carnegie music hall?

The joke is, “a fellow goes to New York to attend a concert, but gets lost. He spots a musician who’s carrying a violin case and asks, ‘Sir, can you tell me how to get to Carnegie Hall?’ The musician smiles and says, ‘Practice, man, practice.'”

Just like you’d need to practice to become an expert musician, it’ll take practice to become an expert product builder.

To get started, try this: re-watch D-Wave’s Save On Foods case study and identify which parts of the video fit in the CIRCLE Method^TM framework. (Hint: timestamps 0:00-3:07 in the video will give you the information you’ll need for step one.)

While you won’t be an expert from doing that alone, it’ll be a step in the right direction. And even though it may take a while, remember that this process will make it easier for you to stand out from your competition and be relevant to your prospective clients, which will grab their attention and make you memorable.

It doesn’t end there, though. Once you’ve started to figure out your product, you’ll need to decide how you’ll price, place, and promote it.

Over the coming months, I’ll put out more thought leadership on those topics because everyone at the Quantum Strategy Institute wants to see the consumer adoption of quantum computing grow. And a key driver of that growth will be quantum computing vendors who can meet their customers’ needs.

What is post-quantum cryptography

by quantumstrategyinstitute with No Comment Joe Ghalbouni Joe Ghalbouni Quantum Risk Quantum Strategy

Post-quantum cryptography’s concept is to make use of encryption algorithms that are proven to be too complex to break for both classical and quantum computers.