After months of testing local LLMs, I found that productivity depends on tools, not just models.

It used to be that memory and storage space were so precious and so limited of a resource that handling nontrivial amounts of text was a serious problem. Text compression was a highly practical ...

Large language models (LLMs) are lowering the entry barriers to working with exciting data sources that used to require strong data science skills, such as handwritten ledgers, text, images, or sound ...

As a result, researchers are exploring ways to embed better logic into AI. The goal isn’t so much to make LLMs smarter; it’s ...

Overview:  Large language models may dominate headlines, but modern NLP tools remain essential for text processing, ...

A popular way to explain how current LLMs work is to say that “all” they do is predict the next most likely word in a sentence. From one perspective, this is correct. Trained on all human language, ...

Chain-of-Thought (CoT) prompting has enhanced the performance of Large Language Models (LLMs) across various reasoning tasks. However, CoT still falls short in dealing with complex math word problems, ...