The chapter explores the rapid advancements in AI and ML technology, focusing on topics like adjusting temperature settings in AI models for creativity and randomness, controlling model output using parameters like temperature and top P, and techniques like prompt engineering for optimizing AI interactions. It also discusses concepts such as streaming, embeddings, and OpenAI evaluations, highlighting the use of tools like Lang chain, PyTorch, and TensorFlow for developing and fine-tuning machine learning models.
In this episode of Syntax, Wes and Scott talk about understanding the integration of different components in AI models, the choice between traditional models and Language Learning Models (LLM), the relevance of the Hugging Face library, demystify Llama, discuss spaces in AI, and highlight available services.
Show Notes
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