Large Language Models
Explains large language models as a technology category: what they are, which capabilities make them the foundation of AI applications, the key dimensions to check when choosing one, and where their limits lie.
Explains large language models as a technology category: what they are, which capabilities make them the foundation of AI applications, the key dimensions to check when choosing one, and where their limits lie.
When AI gets slower the longer you chat, first open a new conversation and restate the key background. In most cases the speed comes straight back, be...
The KV cache holds intermediate results a model keeps while generating text. Each time the model produces a token, it stores the related Key and Value...
GitHub published its 2026 Octoverse report on October 28, 2026, covering the 12 months ending September 30, 2026, across public and private repositori...
When AI long-form writing keeps contradicting earlier settings, stop and build a settings sheet first, then write in sections and check each section a...
In-context learning is the ability of a large model to complete a new task from a few examples in the prompt, without updating its parameters. The mod...
Gamma has introduced Gamma 5 in its September–October changelog. The message, dated October 27, 2026 in Beijing time, is that this is no longer just a...
When AI movie recommendations never match your taste, first give it three movies you truly like and three you clearly dislike, then state your prefere...
When an AI-written resume always looks like a template, do not rush to change the wording. First replace the clichés with your own facts, then revise ...