I discovered 10 ChatGPT-4o prompts that write better copy than most humans. Here’s how you can use them to revolutionize copywriting:
PROMPT ENGINEERING
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Production Readiness of RAG and Agent Applications
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The rag example is very similar to rag apps in production, the data enrichment one same (for a lot of the spreadsheet agents). The react agent one need specific prompt and tools. Ooc – why do you they’re not production ready?
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Clarifying LLM token counting behavior
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I agree and I clarify below I’m only claiming to disprove the (common I think) misunderstanding that LLMs normally do count tokens well, just not letters as a special case
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On LLM tokenization and misgeneralization
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Some people do take “LLMs see tokens not letters” at face value — i.e. the mental model is LLMs can of course count repetitions of a *token*, but a naive tokenizer makes letters an unnecessarily difficult task. Misgeneralization during training is different and more plausible.
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Tokenization isn’t the only cause of LLM counting errors
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Many LLM errors *are* downstream of tokenization oddities, surely. But the folk wisdom that two-R’s-in-strawberry mistakes happen *only* because the letters in “strawberry” are combined into longer prompt tokens before the model can count them is demonstrably not true.
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LLM counting errors: ChatGPT-4o miscounts repeated tokens
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Another clue: LLM counting errors occur even when counting words instead of letters. Here, ChatGPT 4o miscounts just 4 repetitions of “horse” in a 3-line text, despite care to ensure each “horse” maps consistently to the same single token (20998, “horse” with a leading space):
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Similar responses from o1-mini and Claude 3.5 Sonnet
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Similar responses responses to the same prompt can be seen from o1-mini and Claude 3.5 Sonnet. Other models left as an engagement-bait exercise for the reader.
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GPT-4o tokenization splits ‘strawberry’ into single-character tokens
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In both the prompt and response above, each letter in “strawberry” is assigned by the GPT-4o tokenizer to a separate single-character token, instead of being combined into subword-length tokens like “st” “raw” “berry” etc.:
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Dispelling letter-counting myth by asking ChatGPT about strawberry
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Dispelling a popular myth about letter-counting issues in LLMs by asking ChatGPT: h·o·w m·a·n·y R’s a·r·e i·n “s·t·r·a·w·b·e·r·r·y”?
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Remixing AI Generations from Gallery: Cool Feature Guide
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one of the coolest features is being able to remix generations from the gallery!
— KREA AI (@krea_ai) 19 septembre 2024
here's how you can do it. pic.twitter.com/sdZPr3xf9yone of the coolest features is being able to remix generations from the gallery! here's how you can do it.