Zapata Computing Holdings Inc. (Nasdaq: ZPTA), the Industrial Generative AI company, announced that its foundational research on generator-enhanced optimization (GEO) has been published in the esteemed Nature Communications journal. The research, titled “Enhancing Combinatorial Optimization with Classical and Quantum Generative Models,” introduces Generator-Enhanced Optimization (GEO), a novel optimization method that leverages the power of generative modeling to suggest high-quality candidate solutions to complex optimization problems.
Nature Communications Publishes Zapata AI Research on Generative AI for Optimization
Deeplite Accelerates AI on Arm CPUs Using Ultra-Compact Quantization
Deeplite, a provider of AI optimization software designed to make AI model inference faster, more compact and energy-efficient, today announced Deeplite Runtime (DeepliteRT), a new addition to its platform that makes AI models even smaller and faster in production deployment, without compromising accuracy. Customers will benefit from lower power consumption, reduced costs and the ability to utilize existing Arm CPUs to run AI models.
From Storage to Story: Delivering New Value by Unlocking the Power of Data
Our friends over at Kin+Carta know that optimizing the full value of data and figuring out where to start can be difficult. That is why the company has authored this whitepaper on ways to make data work in four clear ways, while helping you take yours from Storage to Story, from modernization through to product optimization. The company’s approach is focused on creating digital products with data to enhance customer and business outcomes.
Redistricting with Optimization
This contributed article discusses how optimization is the most transparent and fair method of creating political districts. However, optimization is a highly challenging process that seeks the ideal answer to a problem with hundreds of millions of possible solutions. The enormity of the problem can be addressed in 2021 because states like Michigan and Virginia are now seriously addressing the gerrymandering issue, while advances in computer software and hardware have made the necessary large-scale optimization possible.
Cambridge Quantum Algorithm Solves Optimization Problems Significantly Faster, Outperforming Existing Quantum Methods
In a development that is likely to set a new industry standard, scientists at Cambridge Quantum (CQ) have developed a new algorithm for solving combinatorial optimization problems that are widespread in business and industry, such as traveling salesman, vehicle routing or job shop scheduling, using near-term quantum computers.
Gurobi Publishes Inaugural State of Mathematical Optimization Report
Gurobi Optimization, LLC – which produces the fast mathematical optimization solver, the Gurobi Optimizer – today released the inaugural edition of its annual State of Mathematical Optimization Report. The report highlights the business impact of mathematical optimization, revealing how companies across more than 42 industries are using this AI technology to solve a broad range of business problems and achieve a variety of business objectives, including maximizing revenue, minimizing costs, and maximizing resource utilization.