The Digital Press

The article commentary expresses frustration over the broad use of the term "AI" for both scientific machine learning and consumer-focused large language models (LLMs), emphasizing that neither is truly "intelligent." It also highlights the funding challenges faced by scientific machine learning researchers compared to the booming investment in generic LLMs.

Why it matters: Mislabeling different AI applications confuses the public and undervalues scientific research contributions.

The stakes: Reduced funding for scientific machine learning could hinder advances that benefit humanity beyond consumer tech.

The big picture: Scientific machine learning struggles for support amid a surge in interest and resources for generic LLMs and image generation.

Commenters say: Many sympathize with the funding imbalance and call for clearer distinctions between AI types and their real-world impact.