For the past two years, artificial intelligence strategy has largely meant the same thing everywhere: pick a large language model, plug it into your workflows, and start experimenting with prompts.

The proliferation of edge AI will require fundamental changes in language models and chip architectures to make inferencing and learning outside of AI data centers a viable option. The initial goal ...