In 1940, a British physicist named Patrick Blackett assembled a genuinely odd team, physicists, mathematicians, a couple of biologists, and reportedly at least one lawyer, and set them loose on a very unglamorous problem: where exactly should radar stations be…
Fine-tuning an LLM means updating a pretrained model’s weights on your own examples so the new behaviour is built into the model instead of described in a prompt. In 2026 the practical stack is three layers: supervised fine-tuning (SFT) teaches…
In the SLM vs LLM comparison, a small language model is any model small enough to run on a single consumer device, which in practice means under roughly 10 billion parameters, while a large language model needs cloud infrastructure. SLMs…
The most common gen ai interview questions cover seven areas: transformer and attention mechanics, RAG versus fine-tuning, chunking and embedding selection, hallucination mitigation, evaluation methodology, agent and tool design, and cost or latency optimisation. RAG and evaluation together make up…
