Zapata Computing, the quantum software company spun out from Harvard in 2017, yesterday announced plans to go public and reposition itself as a provider of industrial generative AI software. This is a marked departure from its earlyaspirations of delivering quantum advantage on current NISQ devices, but it is in keeping with fundamental strengths in quantum-inspired AI software approaches that the company possesses.

The new company, Zapata AI,will go public via the so-calledSPAC route. Heres more from yesterdays announcement: Andretti Acquisition Corp. (NYSE: WNNR), a publicly traded special purpose acquisition company, announced today that they have entered into a definitive business combination agreement that will result in Zapata AI becoming a U.S. publicly listed company. Upon closing of the transaction, the combined company is expected to be listed on the New York Stock Exchange under the new ticker symbol ZPTA.

The boards of directors of each of Zapata and Andretti Acquisition have approved the transaction, which is expected to close in the first quarter of 2024. Other quantum companies D-Wave,IonQ,Rigetti have also gone public via SPACs with varying resultstwo briefly faced delisting. The big challenge hasnt so much been the pace of quantum progress but the stretching time-to-payoff.

Christopher Savoie, CEO of Zapata AI, said in the official announcement, Our engineers and scientists have spent years building, testing, and refining our proprietary software to put Zapata AIand our customersat the forefront of the generative AI revolution. We believe generative AI is shaping a once-in-a-generation opportunity, and the capital and relationships afforded through this business combination will only strengthen our market position. We are participating in an enormous total addressable market where we have the potential to create disproportionate value for our customers and our investors.

Quantum watchers suggest many young quantum software specialists are likely reassessing business plans. While quantum computing advances have been steady, demand has focused on POC and exploratory projects. Current NISQ near-term intermediate scale quantum devices are still too error-prone for use in most production environments, and this is extending expected timelines for quantum payoff. Meanwhile, generative AI has taken off following ChatGPTs success, prompting some quantum software specialists to pivot or expand their strategies.

The initial hype that surrounded quantum computing resulted in a flood of investments even though the technology was still in the early stages of development. While quantum computing software will be necessary for running quantum computing applications, the promises made by some software vendors early on were perhaps too early. However, because generative AI can be used for similar use cases, it may be possible for organizations to leverage some of these applications now without having to wait for quantum to scale, said Heather West, research manager within IDCs Enterprise Infrastructure Practice and lead on quantum computing.

Here are a few financial details of the deal as discussed during the announcement call yesterday:

The transaction values Zapata at an implied pre-money equity value of $200 million, with existing Zapata shareholders set to roll over 100% of their equity into the combined entity, or 20.0 million shares at a price of $10.00. Andretti Acquisition Corp.s sponsors and certain investors that own or have the right to receive founder shares will own a combined 5.8 million shares, or an implied value of approximately $58 million. Andretti Acquisition Corp.s public shareholders currently hold approximately 7.9 million shares, all of which are subject to redemption. The pro forma equity value of the combined company (inclusive of the remaining cash in trust at Andretti Acquisition Corp. after redemptions) is expected to be between $281 million and $365 million, depending on the level of redemptions.

Zapata has been an active developer of IP and early products and says it had nearly twice as many international patent application filings as Meta or Google last year and over 100 global patents and patent applications covering various algorithms, use cases and supporting software and hardware.

The companys current product offerings include Zapata AI Prose, a large language model generative AI solution, and Zapata AI Sense, which generates new analytics solutions to complex industry problems. These industrial solutions, which uniquely process both text and numbers, run on Zapata AIs full-stack Quantum AI software platform, Orquestra, enabling Zapata to train and deliver AI models within customers hybrid cloud and multi-cloud environments, including Microsoft Azure, AWS, and others.

Zapata AIs plan is to provide enterprise-ready AI solutions and tools across a wide variety of industries, including life sciences, finance, chemicals, automotive, government/defense, aerospace and energy. The early emphasis is on creating custom models for industrial use cases, which Zapata AI says differ from consumer-grade LLM in term of required accuracy and security.

During the call, held jointly with Andretti, Savoie said, We have developed a suite of custom, industrial generative AI solutions that can harness the power of language and numerical models for critical, sensitive industrial grade applications. Our solutions are fine-tuned for our customers domain-specific problems.

Perhaps with a nod to the difficulty of attaining near-term success in the still nascent quantum computing market, he added, Our technology is derived from math-inspired quantum physics. The hard part is turning that discipline of physics into useful technology. Fortunately, our work in this area has many transferable and positive implications for generative AI. Being experts at quantum math is one of the surprise differentiators. It allows us to enhance key desirable qualities of generative models. Namely, quantum statistics can enhance generative models ability to generalize or extrapolate missing information, generate new, high-quality information, as well as their ability to generate a more varied range of solutions.

Except for acknowledging its technical expertise in quantum-inspired software, there wasnt any substantive discussion of Zapatas ongoing strategy in the quantum computing arena. Like other quantum software specialists, Zapata had been growing its emphasis on hybrid classical-quantum solutions for some time, as well as its emphasis on all things AI.Indeed, generative AI is generating gold rush aspirations from all quarters.

While the link with Andretti (of motorsport fame) may seem a bit unusual, the two companies have been collaborating for quite a while, exploring the use of Orquestra and other tools for analytics in connection with Andretti racing.

In the official announcement, Michael Andretti, Co-CEO of Andretti Acquisition Corp., said, Zapata AIs Industrial Generative AI solutions have demonstrated their applicability helping enterprises across a range of industries solve complex problems and make better business decisions we have experienced this firsthand in the AI-driven race strategy solutions and advanced analytics capabilities they are delivering to Andretti Autosport. [B]ased on our understanding of its vast capabilities, compelling go-to-market strategy, and ambitious growth plan, we believe there is tremendous enterprise revenue opportunity.

Time will tell.

Read the original post:
Quantum Hopeful Zapata to go Public and Pivot to Industrial ... - HPCwire

LOS ANGELES, CA - (NewMediaWire) - September 8, 2023 - (InvestorBrandNetwork via NewMediaWire) - IBN, a multifaceted financial news, content creation and publishing company, is utilized by both public and private companies to optimize investor awareness and recognition.

D-Wave Quantum (NYSE: QBTS), a leader in quantum computing systems, software and services, was spotlighted in a recent article from The New Stack titled "D-Wave Suggests Quantum Annealing Could Help AI." The article notes that the effect of quantum computing on artificial intelligence ("AI") could be as understated as it is profound. According to the article, some say quantum computing is necessary to achieve general artificial intelligence, and "certain expressions of this paradigm, such as quantum annealing, are inherently probabilistic and optimal for machine learning."

The article points out that the most pervasive quantum annealing use cases center on optimization and constraints, which are challenges that traditionally involve nonstatistical AI approaches such as rules, symbols and reasoning. "With quantum computing, a lot of times we're talking about what will it be able to do in the future," observed Mark Johnson, D-Wave SVP of Quantum Technologies and Systems Products. "But no, you can do things with it today."

To view the full article, visit https://ibn.fm/cX09d

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. The company's mission is to unlock the power of quantum computing today to benefit business and society. D-Wave does 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 is being used by some of the world's most advanced organizations, including Volkswagen, Mastercard, Deloitte, Davidson Technologies, ArcelorMittal, Siemens Healthineers, Unisys, NEC Corporation, Pattison Food Group Ltd., DENSO, Lockheed Martin, Forschungszentrum Jlich, University of Southern California and Los Alamos National Laboratory. For more information about the company, please visit http://www.DWaveSys.com.

Story continues

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. Forward-looking statements in this press release include, but are not limited to, statements regarding the relationship between quantum computing and AI, and annealing quantum computing and machine learning. These forward-looking statements are subject to a number of risks and uncertainties, including, among others, various factors beyond management's control, including general economic conditions and other risks; our ability to expand our customer base and the customer adoption of our solutions; risks within D-Wave's industry, including anticipated trends, growth rates, and challenges for companies engaged in the business of quantum computing and the markets in which they operate; the outcome of any legal proceedings that may be instituted against us; risks related to the performance of our business and the timing of expected business or financial milestones; unanticipated technological or project development challenges, including with respect to the cost and/or timing thereof; the performance of our products; the effects of competition on our business; the risk that we will need to raise additional capital to execute our business plan, which may not be available on acceptable terms or at all; the risk that we may never achieve or sustain profitability; the risk that we are unable to secure or protect our intellectual property; volatility in the price of our securities; the risk that our securities will not maintain the listing on the NYSE; and the numerous other factors set forth in D-Wave's Annual Report on Form 10-K for its fiscal year ended December 31, 2022 and other filings with the Securities and Exchange Commission. 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.

About IBN

IBN has introduced 50+ distinct investor-focused brands over the last 15+ years and has leveraged these unique brands to amass a collective audience of millions of social media followers. In conjunction with 5,000+ syndication partnerships, IBN's broad-based investor-facing brands help fulfill the diverse demands and needs of our rapidly growing base of client-partners. IBN will continue to expand our branded network of highly influential properties, harnessing the energy and experience of our team of specialized experts to exceed the expectations of each of our client-partners.

Please see full terms of use and disclaimers on the InvestorBrandNetwork website applicable to all content provided by IBN, wherever published or re-published: http://IBN.fm/Disclaimer

Corporate Communications

IBN (InvestorBrandNetwork)Los Angeles, California

http://www.InvestorBrandNetwork.com310.299.1717 OfficeEditor@InvestorBrandNetwork.com

Go here to see the original:
D-Wave Quantum Featured in The New Stack Article Discussing Potential Impact of Quantum Computing on AI - Yahoo Finance

Fundamentally, the cost of producing insurance products remains too highbut this could be transformed by evolving technologies, including generative artificial intelligence (gen-AI) and quantum computing. This will in the long term allow the industry to automate activities that today require human intervention, look at a significant amount of data and derive conclusions, and consequently to assess and price risk better. All this could help the industry in closing the protection gap.

This is the view of Moses Ojeisekhoba (pictured), chief executive officer of Global Clients and Solutions at Swiss Re. An advocate for embracing new technology, he told Intelligent Insurer that gen-AI and quantum computing are very much evolvingand they have the potential to transform parts of the industry.

He added that it will be important to build understanding and trust around such technologies. Digital trust is super-important. You can build it and hope they will come, but sometimes you build it, and nobody comes. The main difference between those two outcomes is trust.

More technology can support greater resilience in society, Ojeisekhoba says, and it can also play a key role in narrowing the protection gap in certain areas.

Our vision is to make the world more resilient. Moses Ojeisekhoba, Swiss ReSome of the biggest reasons for the protection gap can be addressed through advancements in technology. Things such as access, affordability, product designthese are all areas where the application of technology allows you to design products in a completely different way, he explains.

Such developments could make insurance much more affordable and enable insurers to reach people in a different way, addressing the issue of accessibility, he adds.

Quantum computing, for example, once fully operational, is expected to enable re/insurers to use the full spectrum and volume of data that is available today and in the future. This will allow re/insurers to derive much more accurate solutions, he says.

Almost everything we interact with has dataset capture in one form or another. Quantum computing will significantly advance the ability to synthesise this data so that you can build scenarios to determine the right pricing.

This will make the product better priced and much more affordable, somewhere down the road. It is not going to come tomorrow but we can clearly see the paths.

Such improvements will allow the industry to address things such as contract certainty where theres been leakage over time, in first party as well as in third party coverage.

Generative AI allows you to apply it to digital contracts and address the topic of leakage, Ojeisekhoba adds.

Swiss Re is investing significantly in gen-AI and is making sure that the reinsurer acquires the right datasets, he says. We are early adopters of this advancement and trying to find a way to ensure that we can improve the product set that we make available to our customers.

These developments are timely in todays challenging world, although Ojeisekhoba believes the re/insurance industry has proved its resilience in the face of adversity.

If you take whats been thrown at the industrywhether its a natural catastrophe, or macroeconomic challenges, geopolitics or broader socioeconomic issuesso far, the reinsurance industry has been resilient. We work extremely hard to ensure that we can anticipate some of the headwinds to ensure that our resilience continues to be in place, he says.

Such testing conditions have brought tailwinds in the form of a much greater public and client understanding of the need for more re/insurance cover. This has pushed up demand. Meanwhile, interest rate rises have bolstered investment yields, strengthening net income as well as the overall balance sheet.

A strategy of resilience

Addressing the needs of clients and partners in the context of the protection gap sits at the heart of Swiss Res strategic framework, says Ojeisekhoba.

Its not just about risk transfer, its also about understanding the risk.When we look at the broader environment, our vision is to make the world more resilient. To do that we need to address the protection gap and ensure that theres enough cover for people who need it.

That means helping clients grow their businesses, and address growth- and profitability-related issues, often driven by the need to transfer risk or for greater risk insight.

We are focused on making sure that we have the strength of balance sheet to provide capacity to our clients, and to ensure that the intellectual property we generate, combined with our technology, can be extended to our clients. We want them to have resilience in their respective businesses, Ojeisekhoba explains.

Swiss Re applies this strategy across the entire insurance value chain. Its not just about risk transfer, its also about understanding the risk. For partners, its one of the main reasons for our existence. Thats a significant part of what we do in terms of our relationships with our clients, he says.

Weve spent a significant amount of resources, financial and otherwise, trying to understand risk better and build assets that allow us to deal with the risk.

This work goes beyond traditional risk transfer to provide insights, as well as risk partnerships, which Ojeisekhoba refers to as the other two legs of overall strategy at Swiss Re.

As an example, he points to property insurance and natural catastrophes, where clients have questions for their customers that include: Are they building in the right places? Do they understand their risks when they build? If a loss occurs, How do they assess that damage relatively quickly?.

Swiss Re provides insurance capacity for nat cat on a global basis, and it continues to grow the capacity that it deploys globally, but what Swiss Re offers its clients goes beyond capacity, Ojeisekhoba says.

He says that Swiss Re has assets, for example its web-based natural hazard analysis and mapping tool, CatNet, that it provides to clients for any particular risks they may have.

They lock the location of that risk in and CatNet gives them geospatial information that tells them the risks that exist, and allows them to understand how they should underwrite that risk and how to price it.

If a loss occurs, the reinsurer can deploy rapid damage assessment capabilities, which include drone, satellite and plane support that can map the area of damage relatively quickly.

It helps our clients very quickly determine where they should send a loss adjuster, as well as the degree of damage incurred at individual risk and portfolio level.

These types of risk insights are part of the overall value chain, Ojeisekhoba says, adding: We are not just providing capacity and paying claims, we do so much more.

Did you get value from this story?Sign up to our free daily newslettersand get stories like this sent straight to your inbox.

Swiss Re, Moses Ojeisekhoba, Global clients, Solutions, AI, Technology, Insurance, Reinsurance, Global

Read the rest here:
AI and quantum computing could transform the protection gap ... - Intelligent Insurer

This article has been reviewed according to ScienceX's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility:

fact-checked

peer-reviewed publication

trusted source

proofread

close

Researchers from the RIKEN Center for Quantum Computing have used machine learning to perform error correction for quantum computersa crucial step for making these devices practicalusing an autonomous correction system that despite being approximate, can efficiently determine how best to make the necessary corrections.

The research is published in the journal Physical Review Letters.

In contrast to classical computers, which operate on bits that can only take the basic values 0 and 1, quantum computers operate on "qubits", which can assume any superposition of the computational basis states. In combination with quantum entanglement, another quantum characteristic that connects different qubits beyond classical means, this enables quantum computers to perform entirely new operations, giving rise to potential advantages in some computational tasks, such as large-scale searches, optimization problems, and cryptography.

The main challenge towards putting quantum computers into practice stems from the extremely fragile nature of quantum superpositions. Indeed, tiny perturbations induced, for instance, by the ubiquitous presence of an environment give rise to errors that rapidly destroy quantum superpositions and, as a consequence, quantum computers lose their edge.

To overcome this obstacle, sophisticated methods for quantum error correction have been developed. While they can, in theory, successfully neutralize the effect of errors, they often come with a massive overhead in device complexity, which itself is error-prone and thus potentially even increases the exposure to errors. As a consequence, full-fledged error correction has remained elusive.

In this work, the researchers leveraged machine learning in a search for error correction schemes that minimize the device overhead while maintaining good error correcting performance. To this end, they focused on an autonomous approach to quantum error correction, where a cleverly designed, artificial environment replaces the necessity to perform frequent error-detecting measurements.

They also looked at "bosonic qubit encodings", which are, for instance, available and utilized in some of the currently most promising and widespread quantum computing machines based on superconducting circuits.

Finding high-performing candidates in the vast search space of bosonic qubit encodings represents a complex optimization task, which the researchers address with reinforcement learning, an advanced machine learning method, where an agent explores a possibly abstract environment to learn and optimize its action policy.

With this, the group found that a surprisingly simple, approximate qubit encoding could not only greatly reduce the device complexity compared to other proposed encodings, but also outperformed its competitors in terms of its capability to correct errors.

Yexiong Zeng, the first author of the paper, says, "Our work not only demonstrates the potential for deploying machine learning towards quantum error correction, but it may also bring us a step closer to the successful implementation of quantum error correction in experiments."

According to Franco Nori, "Machine learning can play a pivotal role in addressing large-scale quantum computation and optimization challenges. Currently, we are actively involved in a number of projects that integrate machine learning, artificial neural networks, quantum error correction, and quantum fault tolerance."

More information: Yexiong Zeng et al, Approximate Autonomous Quantum Error Correction with Reinforcement Learning, Physical Review Letters (2023). DOI: 10.1103/PhysRevLett.131.050601

Journal information: Physical Review Letters

Read more from the original source:
Machine learning contributes to better quantum error correction - Phys.org

The University of Arizona received a $30 million grant from the National Science Foundation to fund the UAs New Frontiers of Sound, a National Science Foundation Science and Technology Center.

This center will explore, in further depth, the study of topological acoustics, a field that lies at the intersection of condensed matter physics, mechanical structural design and acoustics engineering, according to the Nature Journal. The research done at this center will look at the geometry and landscape of sound, an unusual approach which in turn will uncover some of the extraordinary properties of sound, according to the New Frontier of Sound projects principal investigator and professor of materials science and engineering at the UA, Pierre Deymier.

The interaction with the extraordinary properties Deymier referenced will further other topics of research beyond just that of acoustics, some examples of which are biomedical and structural engineering, high speed quantum light computing and monitoring the impacts of climate change.

This elevated understanding of sound can be applied to so many facets of our everyday lives; new sensing capabilities can improve how we monitor aging, infrastructure or climate change. Enhanced telecommunications could mean better battery life in your cellphones. And as the University of Arizona is well aware, expedited computing is similar to whats happening with quantum networks, Gov. Katie Hobbs said at a Thursday press conference celebrating the center.

As Hobbs alluded, the study of topological acoustics applies to cellular technologies in a variety of ways, from lengthening battery life to increasing bandwidths.

Quite interestingly, sound serves a much more important role in the electronics of cellphones. We use sound and acoustic waves to actually filter and therefore select specific channels when we transmit or receive information. This is actually critical for all our wireless infrastructure, Andrea Al, project co-principal investigator and founding director of the advanced science research center at the City University of New York Graduate Center, said. We realize that the technologies that will extend battery life by making much more efficient processing of these acoustic signals [], and that will also realize a more efficient way of transmitting and receiving signals, [in] this way [will] extend the bandwidths. That means better data rates for the common user, that means streaming videos more reliably [].

This research also has environmental implications. The study of topological acoustics could be used as a powerful tool for sensing environmental changes and potentially predicting environmental disasters, according to Deymier.

We can develop sensing technologies that are going to be more sensitive than the current sensing technologies, and in the state of Arizona, we know with climate change we have issues with forest fires in the summer, for instance, when the ground is very dry. We will have the ability of monitoring the dryness of the ground using acoustic waves and perhaps preventing forest fires where they might occur, Deymier said.

Examining topological studies led to the discovery of analogies between sound waves and quantum mechanics, which affects the future of quantum computing. The study of acoustics requires far less stringent standards than quantum computing, making it easier for researchers in laboratories to study under normal conditions.

We can exploit these analogies between these acoustic waves and these quantum systems to perform massively parallel information processing which is analogous to what is done in quantum computing, without the drawback of quantum computing, because in quantum computing you need to have very low temperature, cryogenic temperature and very sophisticated equipment for achieving the computation, Deymier said. Acoustics is very forgiving and enables us to do a similar type of thing with less sophisticated equipment, and also very stable conditions in the laboratory as well.

Researchers leading the charge in the topological acoustics field are hopeful that it will lead to important economic developments, including the creation of more jobs and the development of new technologies.

We know the importance of acoustic microdevices for cell phones, and these are going to be manufactured and fabricated and designed by our team and eventually translated to industry, Deymier said. One of our partners is Intel Corporation, which is a very important industry in our state, and this partnership is going to help translate our inventions, innovations and technologies into products that the public can use.

As of January, Intel employs 13,000 people in Arizona, and has an economic impact of $8.6 billion, according to the company site.

We should be able to develop a number of technologies that are going to benefit the people of Arizona and benefit the economy of Arizona as well, Deymier said. But I want to make a point that our team is a national team, involving eight other universities in the nation, including on the east coast like CUNY or in [Boulder, Colorado] or in Alaska, and with these technologies we also create economic development in the entire nation.

The Center partners include California Institute of Technology, City University of New York, Georgia Institute of Technology, Spelman College, University of Alaska Fairbanks, UCLA, the University of Colorado Boulder and Wayne State University.

Student education and involvement emerged as a primary focus in the NewFOS project. Sara Chavarria, the project co-principal investigator and assistant dean of research in the University of Arizona College of Education, regarded the education and mentorship of students as a key element of topological acoustic research, and the educational programs offered through NewFOS reflect that sentiment.

NewFOS plans to offer a summer program for community college students and a year-long research experience that includes eight summer weeks in one of our institution labs, according to Chavarria.

There will also be a strong emphasis placed on mentorship.

We will take a collaborative mentoring approach so that our students will be mentored by a team of researchers, graduate students, post-docs and educators, Chavarria said. It is important for us to get mentoring right, because our students are the future researchers, educators and industry leaders of topological acoustics.

Relationships with community colleges in Tucson are a crucial component of NewFOS and a major focus of those involved is continuing to strengthen these relationships.

The thing that we fail to remember is that community college students are motivated students, talented individuals who dont often have access to STEM careers due to one reason or another, Janet Yowell, director of strategic community college STEM initiatives for the College of Engineering and Applied Science at the University of Colorado Boulder, said. Were going to reach out to those students to provide them with access to engage in the project and to learn new skills that they can [use to] enhance their STEM futures, particularly in physics and engineering. Through our community college relationships that exist currently, we will further their academic success by offering the peer-to-peer mentoring that was mentioned earlier.

While no new majors will be added in line with this field of research, Chavarria wants students to be involved in creating new curriculum to add to existing coursework.

They will also be able to participate in curriculum writing and work collaboratively with researchers on how to translate and create lessons that they want to learn and how they want to learn it, because they are going to be the translators of this new field as we grow the community, Chavarria said.

The millions in funding from the NSF will bolster this research and community engagement and reflects the influence of this burgeoning field of study.

An award like this is a testament to our states dominance in advanced technology, research and development, and we see societys biggest challenges as a chance to innovate, problem-solve and forge new horizons. This center will ensure researchers in Arizona and their collaborating institutions leverage this opportunity to embolden our state and nations position in the world, Hobbs said. Their work will write the book on this subject; the curriculum and textbooks that educators turn to will come from this center, serving as the gold standard for those wishing to work in the field, and this work will enable researchers to gain insights on information that hasnt always been accessible to us, but is critical to advancing some of todays greatest assets.

FollowtheDaily WildcatonInstagramandTwitter (X)

Here is the original post:
UA awarded $30M for sound science research The Daily Wildcat - Arizona Daily Wildcat