Zapata AI’s Groundbreaking Research on Generative AI Optimisation Published in Nature Communications

Zapata AI’s research on generator-enhanced optimization (GEO) has been published in Nature Communications. The study introduces GEO, a new optimization method that uses generative modeling to suggest solutions to complex optimization problems. The research tested GEO for financial portfolio optimization and found it often outperforms existing algorithms. Zapata AI’s CEO, Christopher Savoie, believes generative AI is the next frontier in business analytics. The company has applied GEO to real-world problems, including work with BMW and MIT to improve manufacturing plant schedules. Zapata AI researchers also used quantum-enhanced generative AI to generate viable cancer drug candidates.

Zapata AI’s Research on Generative AI for Optimization Published in Nature Communications

Zapata Computing Holdings Inc., also known as Zapata AI, has had its research on generator-enhanced optimization (GEO) published in the prestigious Nature Communications journal. The research, titled “Enhancing Combinatorial Optimization with Classical and Quantum Generative Models,” introduces a novel optimization method that uses generative modeling to suggest high-quality solutions to complex optimization problems. This is the second paper on generative AI by Zapata AI to be published in Nature Communications since December 2023.

The research paper discusses the application of GEO in financial portfolio optimization, a common problem among investors who aim to allocate their capital to maximize their returns for a given level of risk (or minimize their risk for a desired level of returns). Despite years of study, this problem remains a computational challenge for financial institutions, especially when more assets are involved. The paper presents the results of a pioneering effort to apply generative AI to portfolio optimization and other optimization problems.

Generative AI: A New Frontier in Business Analytics

Generative AI, often associated with large language models (LLMs), has potential applications beyond language tasks. According to Christopher Savoie, CEO and co-founder of Zapata AI, generative AI could be the next frontier in business analytics. It could be used to generate data for variables that couldn’t otherwise be measured or recommend better ways to solve optimization problems.

The research paper demonstrates one of the many ways generative AI can be applied to industrial problems. Since the research paper was initially submitted to ArXiv in 2021, GEO has been applied to real-world industrial problems. In 2022, GEO was used in collaboration with BMW and the Center for Quantum Engineering at MIT to find more efficient manufacturing plant operating schedules, minimizing idle time between steps in the manufacturing process while meeting production targets.

Quantum Science and Generative AI

Zapata AI has established a growing portfolio of quantum techniques for generative AI since GEO was first developed. For instance, Zapata AI researchers recently used quantum-enhanced generative AI to generate viable cancer drug candidates for the first time. Quantum science could offer several advantages for enterprise problems, including compressing large, computationally expensive models; speeding up time-consuming and costly calculations; and generating more diverse, higher quality outputs for generative AI.

Zapata AI is a company specializing in Industrial Generative AI, revolutionizing how enterprises solve complex problems with its powerful suite of Generative AI software. By combining numerical and text-based solutions, Zapata AI enables industrial-scale enterprises and government entities to leverage large language models and numerical generative models better, faster, and more efficiently delivering solutions to drive growth, cost savings, and operational insight. The Company was founded in 2017 and is headquartered in Boston, Massachusetts.