Does ChatGPT Actually Know Things, or Just Guess? How ChatGPT Works: Tokens, Training, Hallucination
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Does ChatGPT Actually Know Things, or Just Guess? How ChatGPT Works: Tokens, Training, Hallucination
16 просмотров · 14 ч назад
AlgoInsight
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16 просмотров · 14 ч назад
See how ChatGPT actually works - prediction, training, and hallucination - and learn exactly when to trust its answers.
You type a question into ChatGPT and get a clean, confident paragraph in seconds, but where does that answer actually come from? This video walks through Google's crawl, index and rank pipeline, then contrasts it with how ChatGPT predicts tokens one at a time using attention and RLHF. You see real hallucination cases: a lawyer fined $5,000 for fake legal cases, Google Bard's error that wiped $100 billion off Alphabet, a fake book list in the Chicago Sun-Times, and an Air Canada chatbot that invented a refund policy. You end with a checklist for when to trust AI answers.
What you'll learn:
Distinguish Google's retrieval (crawl, index, rank) from ChatGPT's token-by-token generation
Explain why attention, not a database, decides which words a model focuses on
Spot the eight red flags of hallucination, from fake quotes to suspiciously round numbers
Apply the open-book trick: paste source text so ChatGPT reads instead of recalls
Recall six real hallucination cases, including a lawyer fined $5,000 for fake citations
Explain why RLHF makes models confident, sycophantic, and prone to guessing over refusing
Test knowledge cutoff and recognize when you need live search or RAG instead of memory
Chapters:
0:00 The question
5:31 How search answers
15:31 How a model answers
29:21 Training and the cutoff
34:08 From base model to assistant
46:29 Hallucination
1:11:50 Tools and RAG
1:23:56 How to trust it
Key concepts: crawl index rank, tokens and tokenizers, attention mechanism, knowledge cutoff, base model vs assistant, RLHF, sycophancy, hallucination, RAG, context window vs weights
Who this is for: Developers and students who use ChatGPT daily and want to know exactly when its answers can be trusted.
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