Context: Recently, just a few days after Meta revealed its Llama 3 Large Language Model (LLM), Microsoft introduced the latest iteration of its 'lightweight' AI model the Phi-3-Mini.
Large Language Model
- About: It is an artificial intelligence (AI) program designed for text recognition and generation, among other functions.
- Data Training: LLMs undergo training on massive datasets, hence their designation as "large", to enhance their capabilities.
PHI-3-Mini
- About: It stands out as the inaugural release among Microsoft's trio of compact models, promising notable advancements in performance.
- Performance Comparison: It has demonstrated superior performance compared to models of similar and larger sizes across various benchmarks.
- Application in AI: Language models like Phi-3-Mini are fundamental to AI applications such as ChatGPT, Claude, Gemini, etc.
- Features:
oAvailability: Phi-3-mini, boasting a 3.8B parameter count, is accessible via Microsoft Azure AI Studio, HuggingFace, and Ollama.
oVariation: The context window, determining an AI's reading and writing capabilities, is measured in tokens.
oVariant Offerings: Microsoft offers two variants of Phi-3-mini, with context lengths of 4K and 128K tokens respectively.
oImproved Text Processing: Longer context windows empower models to analyze extensive text content such as documents, web pages, and code more effectively.
How is Phi-3-mini different from LLMs?
- Phi-3-mini is an SLM. Simply, SLMs are more streamlined versions of large language models.
- When compared to LLMs, smaller AI models are also cost-effective to develop and operate, and they perform better on smaller devices like laptops and smartphones.