Software / AI

Modeling Paradigms in AI for Battery R&D Large Language Models LLMs and Large Quantitative Models LQMs Different AI model classes address different layers of the battery R&D workflow, from information processing to physics-based prediction

LLMs

Marketing copy

Customer service

Software code

Media

LQMs

Cathodes

Anodes

Electrolytes

Binders

LQMs integrate physics- and chemistry-based models with large-scale scientific datasets to support quantitative prediction of material and system behavior.

LLMs learn from large-scale language and media data to run tasks such as knowledge synthesis, communication, and software-assisted workflows

Text, images, video Internet content

Source: The World Economic Forum, Forbes, AIMultiple, Talbot West, IT Pro, Aviso AI

Chemicals, materials, formulations

Math, biology, chemistry, physics

Extracted from the PDF; charts and images may read imperfectly.