Infleqtion to Develop Machine Learning Models Under DARPA Quantum Program

The Defense Advanced Research Projects Agency has selected Infleqtion to participate a program to develop quantum algorithms for generative machine learning.

The Imagining Practical Applications for a Quantum Tomorrow program is driven by quantum information processing advancements such as Noisy Intermediate-Scale Quantum devices, Infleqtion said Tuesday.

DARPA is exploring how hybrid quantum and classical computing systems can address complex problems. Infleqtion said it will utilize quantum capabilities to develop models of genomic sequence data to advance analysis and personalized medicine.

Teague Tomesh, the lead for Infleqtion’s proposal, explained that his team’s goal is to model long-range correlations to advance ML usage in genomics and sentiment analysis.

The company noted that long-range correlations can be identified in datasets for natural language, finance and other areas, indicating the potential for quantum ML models to optimize data analysis.

Earlier in October, DARPA awarded Rigetti Computing a contract to develop a problem-solving solution under the IMPAQT program.