Advanced LLM modes like “research” and “thinking” depend heavily on web search, but they’re bounded by cost and scale. The quality of the search engine directly shapes the quality of the model’s output, giving LLM developers with strong search partners a clear edge in both accuracy and efficiency. Let’s take a closer look at how this all works.

Designing deceptively simple math problems to challenge (or troll) students and LLMs, and why it is crucial to include enough atypical variations in training datasets and textbooks.

Here, we explore how various LLMs perform in writing tasks, examining each one’s unique style and providing recommendations based on their strengths. Additionally, we delve into why Google’s Gemini is a misfit for writing, discussing the reasons behind its peculiar behavior.

Every 10 years the same comic strip comes up about the new technology: SQL database, blockchain, and now AI. When will be the next wave and what will it be about?…