When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

What separates a mediocre large language model (LLM) from a truly exceptional one? The answer often lies not in the model itself, but in the quality of the data used to fine-tune it. Imagine training ...

NVIDIA’s RTX 50 Series graphics cards have enough VRAM to load Gemma 4 models, and a range of others. Their Tensor Cores help ...

Two popular approaches for customizing large language models (LLMs) for downstream tasks are fine-tuning and in-context learning (ICL). In a recent study, researchers at Google DeepMind and Stanford ...

Fine-tuning an AI model can feel a bit like trying to teach an already brilliant student how to ace a specific test. The knowledge is there, but refining how it’s applied to meet a particular ...

When non-DBAs think about what it is that a DBA does, performance monitoring and tuning are usually the first tasks that come to mind. This should not be surprising. Almost anyone who has come in ...

Databases are the most common cause of poor application performance, making performance optimization critical for any production database, according to Guy Harrison, co-author of a new book, titled ...