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SAN FRANCISCO, June 6, 2023 Haiqu, a startup building software to enhance the performance of quantum processors, today announced it has closed a $4 million financing round led by MaC Venture Capital with participation from Toyota Ventures, SOMA capital, u.ventures, SID Venture Partners, and Roosh Ventures. The round also included private contributions from Paul Holland, Alexi Kirilenko, and Gordy Holterman.

We are accelerating the timeline to practical quantum computing by developing novel software that can extract value out of clumsy near-term quantum hardware, enabling quantum applications that were previously impossible, said Richard Givhan, co-founder and CEO at Haiqu. We are proud to be backed by investors with remarkable deep-tech ecosystems and a track record of supporting the commercialization of breakthrough tech.

The investment will drive the companys research and development efforts and the establishment of strategic partnerships to bring their product to market.

MaC is thrilled to be supporting Haiqu through their next stage of growth, said Adrian Fenty, Managing General Partner at MaC Venture Capital. We firmly believe that the future of quantum computing will fundamentally change the way we are able to solve meaningful problems. We hold deep convictions that Richard and Mykola are uniquely positioned to tackle these issues in order to accelerate the timeline that will enable quantum to get to widespread commercial adoption.

Jim Adler, founder and general partner at Toyota Ventures, commented, Haiqu caught our attention with their optimization software that boosts quantum hardware to solve practical industry problems. We are so thrilled to support the Haiqu team as they tackle this challenging and exciting frontier.

The startup was formed and incubated in the fall of 2022 within the Creative Destruction Lab Quantum stream in Toronto by Richard Givhan (CEO), a Stanford alumus and former EIR at Mitsubishi Electric, and Mykola Maksymenko (CTO), formerly a researcher at the Max Planck Society and the Weizmann Institute of Science and head of R&D at global consultancy SoftServe Inc.

Haiqu addresses the foundational bottlenecks precluding the adoption of quantum applications: a limited number of qubits and the high noise sensitivity of near-term quantum processors. The startup develops platform-agnostic technology that extends quantum hardware capability by orders of magnitude and enables a broader set of practical use-cases in finance, chemistry, life sciences, mobility and other domains.

We leverage our expertise in quantum complexity, AI, and high-performance computing to create a product that we believe can streamline the entire industry, said Mykola Maksymenko, co-founder and CTO at Haiqu. With past experience in building and scaling deep tech R&D in large corporations, we appreciate the challenges of bringing a complex technology to market. We are eager to get our tech into the hands of users as soon as possible.

Having started as a remote collaboration of co-founders, Haiqu is growing globally via a distributed team spanning the United States, Ukraine, Canada, Germany, and Switzerland. Given the scarcity of quantum talent, this provides the startup access to some of the worlds leading talent pools in quantum and software engineering.

About Haiqu Inc.

Haiqu Inc. is a quantum computing software startup focused on developing enabling technology enhancing the performance of modern quantum hardware. Their software addresses the adoption bottlenecks precluding scalable quantum applications and enables a broader set of practical use-cases in finance, life sciences, mobility and other domains. For more information, please visit http://www.haiqu.ai.

Source: Haiqu

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Haiqu Raises $4M in Pre-Seed Funding to Boost Adoption of Near-Term Quantum Computing - HPCwire

Selbyville, Delaware, June 04, 2023 (GLOBE NEWSWIRE) --

Automotive Quantum Computing Market is expected to cross a valuation of USD 3.5 billion by 2032, according to latest research report by Global Market Insights Inc.

The growing deployment of advanced battery management in electric as well as hybrid vehicles for improving the battery performance and lifespan will influence the market growth. Of late, the industry demand has gained immense ground as it helps in developing more advanced battery management systems for enhanced monitoring and controlling of battery performance while extending battery life in all-electric and hybrid applications. However, the higher costs of developing and integrating new automotive solutions may limit the market growth.

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Rising preference for on-premise computing

The automotive quantum computing market from the on-premise segment is poised to witness over 30% CAGR from 2023-2032. The growth can be attributed to the higher availability of customized solutions and the increasing affordability of quantum computing in the automotive sector. The ongoing developments in quantum computing technology has spurred the profitability of local solutions in automotive companies. The growing popularity of on-premise computing in large organizations that require more manpower and resources for investing in internal areas will also add to the segment growth.

Robust adoption in autonomous driving

The industry size from autonomous driving applications is estimated to record more than 40% growth rate from 2023-2032 due to the surging need for improved safety worldwide. Automotive computing can be touted as an integral part of autonomous driving as it offers processing power and algorithms required for interpreting the sensor data for making realistic driving decisions. The increasing prominence of this technology for improving road safety and limiting accidents caused by human error will also drive the business development.

Europe to emerge as a major market

Europe automotive quantum computing industry size may cross USD 1 billion by 2032. The growth can be attributed to the strong presence of multiple car companies and government officials for supporting the development of quantum computing in the region. For instance, the European Union introduced the Quantum Flagship program in a bid to introduce quantum technologies. The surging number of investments for helping companies to develop novel solutions for automotive development and cybersecurity will further accelerate the market trends.

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Automotive Quantum Computing Industry Competitive Landscape

Some of the prominent automotive quantum computing market participants include QC Ware Forge, Amazon Web Services, Inc.,D-Wave Systems Inc. , PASQAL ,PsiQuantum, Fujitsu Limited, Huawei Technologies Co., Ltd. , Google LLC, IonQ, ISARA Corporation , Microsoft Corporation, Q-CTRL , QpiAI Tech, Rigetti Computing, Inc., and Strangeworks, Inc. These firms are coming up with innovative strategies to widen their global presence. For instance, Zapata Computing, in August 2021, launched Orquestra, its new quantum computing software platform to assist researchers and developers in developing and testing quantum computing algorithms for several applications, including cars.

Partial Table of Contents (ToC) of the report:

Chapter 2Executive Summary 2.1 Automotive quantum computing market 360 synopsis, 2018 - 2032 2.2 Business trends 2.2.1 Total Addressable Market (TAM) 2.3 Regional trends 2.4 Component trends 2.5 Deployment trends 2.6 Application trends 2.7 Stakeholder type trends Chapter 3Automotive Quantum Computing Market Insights 3.1 Impact on COVID-19 3.2 Russia- Ukraine war impact 3.3 Industry ecosystem analysis 3.4 Vendor matrix 3.5 Profit margin analysis 3.6 Technology & innovation landscape 3.7 Patent analysis 3.8 Key news and initiatives 3.9 Regulatory landscape 3.10 Impact forces 3.10.1 Growth drivers 3.10.1.1 Increasing government investments in quantum research 3.10.1.2 Advancements in autonomous vehicle technology 3.10.1.3 Growing demand for electric and hybrid vehicles 3.10.1.4 Increasing complexity of automotive systems 3.10.2 Industry pitfalls & challenges 3.10.2.1 High cost of quantum computing hardware and software 3.10.2.2 Technical complexity 3.11 Growth potential analysis 3.12 Porters analysis 3.13 PESTEL analysis

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About Global Market Insights Inc.

Global Market Insights Inc., headquartered in Delaware, U.S., is a global market research and consulting service provider, offering syndicated and custom research reports along with growth consulting services. Our business intelligence and industry research reports offer clients with penetrative insights and actionable market data specially designed and presented to aid strategic decision making. These exhaustive reports are designed via a proprietary research methodology and are available for key industries such as chemicals, advanced materials, technology, renewable energy, and biotechnology.

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Automotive Quantum Computing Market to hit $3.5 Bn by 2032, Says ... - GlobeNewswire

On Wednesday of this week the House Science Committee will hold a hearing as part of the reauthorization effort for the U.S. National Quantum Initiative Act passed in 2018. In recent years, the global race to achieve quantum computing has reached what sometimes feels like a fever pitch as nations and regions ramp up quantum spending and development. The NQIAs initial authorization runs through September 2023.

Frank Lucas (R-OK) is the chair of the House Science Committee, which is gathering information as part of the reauthorization process. The recent CHIPS Act had already made some modifications and additions to NQIA; for example, the creation of nine microfabrication hubs as part of the Microelectronics Commons (MEC) program. Given the current wrangling over budget issues, its not clear whether changes will be considered.

Last week, theNational Quantum Initiative Advisory Committee (NQIAC)weighed in by publishing its first independent assessment of the National Quantum Initiative (NQI) program. Perhaps not surprisingly, the report calls for reauthorizing NQIA for at least another five years.

Heres are the overarching recommendations excerpted from the report:

The devil, of course, is in the details. This new phase will necessitate a ramp up of investments in fundamental research across engineering, systems integration, software, and applications discovery in order to mature and scale quantum systems into relevant technologies, reads the report. The NQIAC has developed nine detailed recommendations for achieving these objectives, described in the following sections. To summarize, they are: 1. Reauthorize and appropriate the NQI Act; 2. Expand research; 3. Fund industry-led partnerships; 4. Invest in equipment and infrastructure; 5. Promote international cooperation;6. Promote and protect U.S. QIST R&D; 7. Strengthen supply chains; 8. Develop domestic talent; and 9. Attract and retain foreign talent.

Scheduled speakers at Wednesdays hearing include:

As HPCwire has reported in the past, the U.S. NQIA is a complicated $2B-plus effort. One of its centerpieces was the creation of five QIS research centers, based at Department of Energy national laboratories. The centers are charged with advancing QIS (quantum information science) research, collaborating with industry, and helping to develop the workforce required to sustain QIS writ large. On the commercial side, the creation of the Quantum Economic Development Consortium (QED-C) was also called for by NQIA, and it is broadly being overseen by NIST. QED-Cs mission to provide a forum for industry to look at uses cases, standards, best practices, etc.

If youre a quantum watcher, you know there are similar efforts around the world. Just this year, the U.K issued its own 2.5B, 10-yearnational quantum strategy. China, the EU, Japan, and others have all joined the quantum race. At ISC23 last week, quantum computing advocates outlined many of Europes rapidly expanding plans, which are being overseen as part of the EuroHPC Joint Undertaking (EuroHPC JU).

In Estela Suarezs closing keynote (presented with Thomas Sterling), she noted, There is a huge investment in Europe in the integration of quantum computing and HPC. What you see here (slide below) are some of the [planned] installations. [They] will be in different cities and will all be federated with each other. Different sites will have different quantum technologies, by federating them all together, a user can try different kinds of machines and find out which users are more suitable for which kind of technologies. In parallel to that, there is a research agendathat has very aggressive very in the targets for the 2030 timeframe.

The race to achieve practical quantum computing is in full-force worldwide despite the many technical hurdles remaining. In light of the recent budget deal to avoid a U.S. government shutdown, it will be interesting to monitor what is eventually added (or removed) in NQIAs reauthorization.

Link to live webcast of the Congressional hearing scheduled to begin at 10 am on Wednesday, https://science.house.gov/hearings?ContentRecord_id=7684AFE7-D1EB-4079-B9A8-3941F0CCAF24

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Congressional Hearing on U.S. National Quantum Initiative ... - HPCwire

Exploring the Synergy between Neuromorphic Computing and Quantum Computing for Advanced AI Applications

The rapid advancements in artificial intelligence (AI) and machine learning (ML) have created a significant demand for powerful computing systems that can handle the massive amounts of data and complex algorithms involved in these fields. Traditional computing architectures, such as those based on the von Neumann model, are reaching their limits in terms of energy efficiency and processing capabilities. This has led researchers to explore alternative computing paradigms, such as neuromorphic computing and quantum computing, which hold the potential to revolutionize the way we process and analyze information.

Neuromorphic computing is a novel approach that aims to mimic the structure and function of the human brain in order to create more efficient and adaptive computing systems. It is based on the idea of using artificial neural networks, which are composed of interconnected artificial neurons, to process and store information. These networks can be implemented in hardware, using specialized electronic components, or in software, running on conventional computing platforms. Neuromorphic systems are designed to be highly parallel, fault-tolerant, and energy-efficient, making them well-suited for AI and ML applications.

Quantum computing, on the other hand, is a fundamentally different approach that relies on the principles of quantum mechanics to perform computations. Unlike classical computers, which use bits to represent information as either 0 or 1, quantum computers use quantum bits, or qubits, which can exist in multiple states simultaneously due to a phenomenon known as superposition. This allows quantum computers to perform certain types of calculations much faster than classical computers, potentially enabling them to solve problems that are currently intractable.

The synergy between neuromorphic computing and quantum computing is an exciting area of research that could lead to the development of advanced AI applications that were previously thought to be impossible. By combining the strengths of both paradigms, researchers hope to create hybrid systems that can tackle complex problems in areas such as natural language processing, pattern recognition, and decision-making.

One of the key challenges in developing such hybrid systems is finding ways to integrate neuromorphic and quantum components in a seamless and efficient manner. Researchers are exploring various techniques to achieve this, such as using quantum-inspired algorithms to train neuromorphic networks, or employing neuromorphic hardware to control and read out the states of qubits in a quantum processor.

Another important aspect of this research is the development of new materials and fabrication techniques that can support the implementation of neuromorphic and quantum devices. For example, researchers are investigating the use of superconducting materials, which can carry electrical currents without resistance, to create energy-efficient neuromorphic circuits and qubits. They are also exploring the potential of nanoscale structures, such as quantum dots and nanowires, to enable the miniaturization and integration of these devices.

As the field of neuromorphic-quantum computing continues to evolve, it is expected to have a profound impact on the future of AI and ML. By harnessing the power of both neuromorphic and quantum computing, researchers aim to develop systems that can learn and adapt in real-time, allowing them to handle complex tasks with greater speed and accuracy than ever before. This could lead to breakthroughs in areas such as robotics, autonomous vehicles, and personalized medicine, among others.

In conclusion, the synergy between neuromorphic computing and quantum computing holds great promise for the future of AI and ML applications. By exploring the potential of these two emerging paradigms, researchers are paving the way for the development of advanced computing systems that can tackle some of the most challenging problems in science and technology. As we continue to push the boundaries of what is possible with AI and ML, the integration of neuromorphic and quantum computing will undoubtedly play a crucial role in shaping the future of these fields.

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The Role of Neuromorphic Computing in the Future of Quantum ... - CityLife

BOSTON, June 6, 2023 Zapata Computing today announced that it has published research with Insilico Medicine, Foxconn, and the University of Toronto which explores the use of hybrid quantum-classical generative adversarial networks (GAN) for small molecule discovery. Not only could the quantum-enhanced GANs generate small molecules, but these molecules had more desirable properties than those generated by purely classical GANs.

As detailed in the research paper, the teams leveraged artificial intelligence and quantum computing techniques to replace each element of GAN with a variational quantum circuit (VQC). The molecules generated by the quantum-enhanced GANs were then compared with those generated by a purely classical GAN according to three qualitative metrics (validity, uniqueness, and novelty) and three quantitative properties (drug-likeness (QED), solubility, and synthesizability (SA)). Researchers found that the small molecules created through the use of a VQC frequently had better physicochemical properties and performance in the goal-directed benchmark than the classical counterpart.

At Insilico Medicine, were always seeking new ways to transform drug design and development through artificial intelligence to help bring life-saving medications to patients, said Alex Zhavoronkov, PhD, founder and CEO of Insilico Medicine. The drug discovery pipeline is traditionally a long and costly process, but recent advances in machine learning and deep learning technologies have proven to help reduce time and costs for pharmaceutical research and development. By working with Zapata and Foxconn, we were able to uncover molecule designs with viable structures that were comparable to those from classical methods.

We are pleased to achieve this milestone in the collaboration with Insilico Medicine. Quantum computing can be used to solve complex computational problems. The application of quantum computing in drug discovery will potentially help reduce the time and lower the cost of research and development, said Min-Hsiu Hsieh, PhD, Director of the Quantum Computing Research Center of Hon Hai Technology Group, Foxconn.

This work with Insilico Medicine and Foxconn is a great example of how quantum-enhanced generative AI can be used to solve real-word problems more effectively, said Yudong Cao, CTO and co-founder at Zapata Computing. Weve seen encouraging evidence that demonstrates the potential of quantum and quantum-inspired generative models, and were excited to see how these quantum-inspired techniques could help further advance the pharmaceutical industry, as well as other industries looking to overcome complex design challenges.

Zapata has a track record of breakthrough research in quantum generative AI. In 2021, Zapata researchers were the first to generate high-resolution images using quantum generative models. In more recent work with BMW, Zapata researchers demonstrated how quantum-inspired generative models could improve upon best-in-class traditional optimization solutions for a vehicle manufacturing scheduling problem.

For more information about Zapatas research with Insilico Medicine, Foxconn, and the University of Toronto, please click here.

About Zapata Computing

Zapata Computing, Inc. builds solutions to enterprises most computationally complex problems. It has pioneered proprietary methods in generative AI, machine learning, and quantum techniques that run on classical hardware (CPUs, GPUs). Zapatas Orquestra platform supports the development and deployment of better, faster, more cost-effective modelsfor example, Large Language Models, Monte Carlo simulations, and other computationally intense solutions. Zapata was founded in 2017 and is headquartered in Boston, Massachusetts.

Source: Zapata Computing

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Zapata, Foxconn, Insilico Medicine, and University of Toronto Study ... - HPCwire