Everyday AI Podcast – An AI and ChatGPT Podcast EP 208: Small Language Models - What they are and do we need them?
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Feb 15, 2024 The discussion revolves around the intriguing world of small language models, highlighting their efficiency compared to larger ones. Listeners learn about the practical applications and benefits, particularly for mobile usage. Innovations like NVIDIA's local model and partnerships like Samsung and Google’s Gemini Nano showcase the evolving landscape. Insights on the energy-efficient nature of these models and their potential in everyday tasks make for a captivating exploration of AI's future.
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Evolving Definition of Small Language Models
- Small language model (SLM) definitions constantly evolve alongside large language model advancements.
- Previously, SLMs had under 100M parameters, but now, even billion-parameter models are considered "small."
LLMs vs. SLMs: Parameters and Capabilities
- Large language models (LLMs) like GPT-4 and Gemini Ultra boast trillions of parameters, enabling diverse complex tasks.
- Small language models (SLMs) have fewer parameters, prioritizing efficiency and specific tasks or local device use.
Understanding Parameters in Language Models
- Language model parameters are variables used for prediction, adapting based on training data.
- More parameters mean more complexity, cost, and training difficulty, like large language models.