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Zapata AI Research in Quantum-Enhanced Generative AI Published in Nature Communications

The paper demonstrates how quantum and classical techniques for generative AI can work synergistically to deliver advantages not possible with either approach in isolation.

Zapata Computing, Inc. (“Zapata AI”), the Industrial Generative AI company, today announced that its research in quantum-enhanced Generative AI has been published in the prestigious Nature Communications journal. The article, titled “Synergistic pretraining of parametrized quantum circuits via tensor networks,” demonstrates how quantum circuits can extend and complement the capabilities of classical generative AI.

The research was published online on December 15th and can be accessed here.

“We are extremely proud of the talented researchers who contributed to this groundbreaking work,” said Christopher Savoie, CEO and co-founder of Zapata AI. “Quantum techniques can bring tremendous advantages to enterprise generative AI applications, and this research shows how we can make the most of the resources we have today to realize those advantages. It is no longer a question of quantum vs. classical, but rather how the two can be used synergistically together to get better results, faster. We are looking forward to applying this research in our work with enterprise customers.”

The work builds on Zapata AI’s growing portfolio of quantum techniques for generative AI. These quantum techniques offer several advantages for enterprise problems, including compressing large, computationally expensive models; speeding up time-consuming and costly calculations; and more diverse, higher quality outputs for generative AI. More details on how quantum science can enhance generative AI can be found in a recent Zapata AI blog post.

“Our work combines the complementary strengths of quantum and classical computers to reach better results than either type of hardware on its own,” said Jacob Miller, Quantum Research Scientist at Zapata AI. “People often think that quantum and classical technologies are in competition with each other, but we show that classical methods can actually help overcome a major limitation in the optimization of quantum devices. We hope our “synergistic” approach can start to unlock the true potential of present-day quantum technologies for solving intractable computational problems.”

“In our Nature Communications article, we showcase how tensor networks, traditionally used in classical algorithms, form a critical bridge to quantum algorithms, offering a unique synergy,” said Jing Chen, a Senior Quantum Scientist at Zapata AI who authored the paper along with Manuel Rudolph, Jacob Miller, Daniel Motlagh, Atithi Acharya, and Alejandro Perdomo-Ortiz. “This integration not only enhances both fields but also notably alleviates the challenges of barren plateaus in quantum computing. Our approach fosters collaboration, leveraging the strengths of classical and quantum methods to address complex problems more effectively.”

About Zapata AI:

Zapata AI is the Industrial Generative AI company, revolutionizing how enterprises solve their hardest problems with its powerful suite of Generative AI software. By combining numerical and text-based solutions, Zapata AI empowers industrial-scale commercial, government and military/defense enterprises to leverage large language models and numerical generative models better, faster, and more efficiently—delivering solutions to drive growth, savings and unprecedented insight. With proprietary science and engineering techniques and the Orquestra® platform, Zapata AI is accelerating Generative AI’s impact in Industry. The Company was founded in 2017 and is headquartered in Boston, Massachusetts. On September 6, 2023, Zapata AI entered into a definitive business combination agreement with Andretti Acquisition Corp. (NYSE: WNNR), the consummation of which, subject to customary closing conditions, will result in Zapata AI becoming a publicly listed company on the New York Stock Exchange. To learn more, visit: https://www.zapata.ai

Forward-Looking Statements

Certain statements made herein are not historical facts but are forward-looking statements for purposes of the safe harbor provisions under The Private Securities Litigation Reform Act of 1995. Forward-looking statements generally are accompanied by words such as “believe,” “may,” “will,” “estimate,” “continue,��� “anticipate,” “intend,” “expect,” “should,” “would,” “plan,” “predict,” “potential,” “seem,” “seek,” “future,” “outlook,” and similar expressions that predict or indicate future events or trends or that are not statements of historical matters. These forward-looking statements include, but are not limited to, statements regarding future events, the transaction, the estimated or anticipated future results and benefits of the combined company following the transaction, including the likelihood and ability of the parties to successfully consummate the transaction, future opportunities for the combined company, and other statements that are not historical facts. These statements are based on the current expectations of Andretti Acquisition Corp.’s and Zapata AI’s management and are not predictions of actual performance. These forward-looking statements are provided for illustrative purposes only and are not intended to serve as, and must not be relied on, by any investor as a guarantee, an assurance, a prediction, or a definitive statement of fact or probability. Actual events and circumstances are difficult or impossible to predict and will differ from assumptions. Many actual events and circumstances are beyond the control of Andretti Acquisition Corp. and Zapata AI. These statements are subject to a number of risks and uncertainties regarding Zapata AI’s businesses and the transaction, and actual results may differ materially. These risks and uncertainties include, but are not limited to, ability to meet the closing conditions to the transaction, including approval by stockholders of Andretti Acquisition Corp. on the expected terms and schedule and the risk that regulatory approvals required for the transaction are not obtained or are obtained subject to conditions that are not anticipated; delay in closing the transaction or failure to close the transaction within the period permitted under its governing documents; failure to realize the benefits expected from the proposed transaction; a decline in the price of Andretti Acquisition Corp’s securities following the transaction if it fails to meet the expectations of investors or securities analysts; the amount of redemption requests made by Andretti Acquisition Corp.’s public stockholders; the ability of Andretti Acquisition Corp. or the combined company to issue equity or equity-linked securities in connection with the transaction or in the future; the effects of pending and future legislation; risks related to disruption of management time from ongoing business operations due to the proposed transaction; business disruption following the transaction; risks related to Andretti Acquisition Corp.’s and Zapata AI’s indebtedness; other consequences associated with mergers, acquisitions, and divestitures and legislative and regulatory actions and reforms; Zapata’s ability to maintain its current rate of growth; maintenance and renewal of customer contracts and subscriptions; competition in Zapata AI’s industries; Zapata AI’s ability to raise additional capital; the successful integration of potential targets, products, or technologies; Zapata AI’s ability to improve its operational, financial, and management controls; Zapata AI’s failure to maintain and enhance awareness of its brand; increased costs associated with being a public company; cybersecurity incidents; ability to prevent fraudulent activities by Zapata AI’s customers, employees, or other third parties; potential interruptions or delays in third-party services; protection of proprietary rights; intellectual property infringement, data protection, and other losses; compliance with federal, state, and local laws as well as statutory and regulatory requirements; risks of implementing controls and procedures required for public companies following the transaction; and the ability of Zapata AI’s or the combined company to issue equity or equity-linked securities with the proposed business combination or in the future; and those factors discussed in Andretti Acquisition Corp.’s Form 10-K for the year ended December 31, 2022, under Risk Factors in Part I, Item 1A and other documents of Andretti Acquisition Corp. filed, or to be filed, with the SEC.

If any of these risks materialize or if assumptions prove incorrect, actual results could differ materially from the results implied by these forward-looking statements. There may be additional risks that Andretti Acquisition Corp. or Zapata AI presently do not know or that Andretti Acquisition Corp. or Zapata currently believe are immaterial that could also cause actual results to differ from those contained in the forward-looking statements. In addition, forward-looking statements provide Andretti Acquisition Corp.’s or Zapata AI’s expectations, plans, or forecasts of future events and views as of the date of this communication. Andretti Acquisition Corp. or Zapata AI anticipate that subsequent events and developments will cause their assessments to change. However, while Andretti Acquisition Corp. or Zapata AI may elect to update these forward-looking statements at some point in the future, Andretti Acquisition Corp. or Zapata AI specifically disclaim any obligation to do so. These forward-looking statements should not be relied upon as representing Andretti Acquisition Corp.’s or Zapata AI’s assessments as of any date subsequent to the date of this communication. Accordingly, undue reliance should not be placed upon the forward-looking statements.

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