ML/AI-enhanced engineering design tools offer tremendous through their potential to accelerate engineering design processes.  

Such processes are iterative, and feature repeated attempts to hypothesize and evaluate potential solutions to problems with continued updates based upon the learnings associated with previous "failed" attempts. 

ML/AI offers tremendous potential to accelerate multiple aspects of this process, including --

1. Problem and potential solution data gathering and synthesis,

2. Hypothesis generation (& iterative update),

3. Concept evaluation, and

4. Generative design (ideally eliminate iteration)

sF working to develop each of the above capabilties to accelerate the development of Energy Transition technologies by leveraging in part LLM foundation models as well as more "traditional" ML techniques.