” Does bigger always equal better when it comes to language AI? Not necessarily. Having fewer parameters gives SLMs some major advantages: Agile Development: Easier to build, modify, and refine quickly based on small amounts of high-quality data. Reduces the chances of hallucinations: Due to simpler knowledge representations and narrower training data. Lightweight: Enable text generation and analysis on smartphones and edge devices with lower computing requirements. Controllable Risks: Avoid problems like bias, toxicity, and accuracy issues more prevalent in gigantic models. Interpretability: The inner workings of smaller models can be understood by developers, facilitating tweaks. Improve Latency: Have fewer parameters, which means they can process and generate text more quickly than larger models, reducing the time it takes to generate a response or perform.”