Generative AI creates original content from data, while classic AI focuses on predictions; examples include AI chatbots like OpenAI's ChatGPT and Google's Gemini.

These advanced chatbots can execute complex tasks but may produce errors or 'hallucinations' without sufficient training data.

Large language models (LLMs) are a subset of generative AI, trained on vast text corpora to comprehend and produce human-like language.

Semiconductors, or AI chips, are crucial for electronic devices; TSMC dominates the market, but the US is investing to localize production and compete with China.

GPUs have evolved from gaming to bolster deep learning, whereas TPUs are specialized for AI tasks, surpassing CPUs and GPUs in performance for AI applications.

The interplay of generative AI, AI chips, and the need to mitigate AI errors is central to the AI field's advancement, with broad implications across industries.