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Wait.... tokens? When using a large language model like ChatGPT, tokens really matter. But hardly no one understands them. And NOT knowing how tokens work is causing your ChatGPT output to stink. We'll help you fix it.
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Related Episodes: Ep 253: Custom GPTs in ChatGPT – A Beginner’s Guide
Ep 318: GPT-4o Mini: What you need to know and what no one’s talking about
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Topics Covered in This Episode:
1. Tokenization in ChatGPT
2. Comparison of Different AI Models
3. Importance of Tokenization and Memory in AI Models
4. Limitations of ChatGPT
5. Explanation of Tokenization Process
Timestamps:
02:10 Daily AI news
07:00 Introduction to tokens
10:08 Large language models understand words through tokens.
12:05 Understanding tokenization in generative AI language models.
16:35 Contextual analysis of words for language understanding.
19:15 Different models have varying context window sizes.
23:57 Misconception about GPT-4. Detailed explanation follows.
26:38 Promotion of PPP course, common language mistakes.
28:57 Excess text to exceed word limit intentionally.
33:19 Keeping up with ever-changing AI rules.
36:50 Recall important information by prompting chat GPT.
40:37 Highlight information, use quotation button, request summary.
43:41 Clear communication is crucial for ChatGPT.
Keywords:
Jordan Wilson, Bears football team, personal information, Carolina blue, deep dish pizza, token counts, memory limitations, ChatGPT, tokenization, language models, generative AI, controlling response, token range, memory recall, AI models, GPT, anthropic Claude, Google Gemini, context window, book interaction, large language models, OpenAI's GPT 4.0, transcript summary, Everyday AI, Google's Gemini Live AI assistant, new Pixel 9 series, XAI's Grok 2, OpenAI's GPT 4 update, importance of tokens in chatbots, podcast promotion.
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