It did just suggest I "pip install sqlite3" in a Python prompt I ran through it though, which is a new mistake that I've not actually seen from other GPT-4 level models
PROMPT ENGINEERING
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Extracting AI System Prompts: Challenges and Hallucination Risks
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I'm not sure that's the real system prompt – looks to me like it could be a hallucination based on training data. My own attempts to extract the system prompt have so far failed:
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LLMs are poor judges of ASCII art, votes should be excluded
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Human preference LLM arenas are poorly suited for evaluating ASCII art because the ASCII art that most impresses a human is often verbatim regurgitation of an existing human work and this is rarely true for text. Votes on ASCII art should be detected and thrown out IMO.
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AI Model Hallucination-Free Responses Challenge
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I don't see any hallucinated details in here at all, which never happens with these kinds of ego-prompts for me
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Constrained Sampling Forces Model Function Calls
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Constrained sampling to ensure that a model calls a function:
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Prompt Engineering for Vision Models: Generation, Editing, Detection
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In Prompt Engineering for Vision Models, taught by @anmorgan2414 @JacquesVerre and @KaiserFrose of @Cometml , you’ll learn how to prompt and fine-tune vision models for personalized image generation, image editing, object detection and segmentation. The prompts you'll use for… pic.twitter.com/sXis2waFDH
— Andrew Ng (@AndrewYNg) 29 avril 2024In Prompt Engineering for Vision Models, taught by @anmorgan2414 @JacquesVerre and @KaiserFrose of @Cometml , you’ll learn how to prompt and fine-tune vision models for personalized image generation, image editing, object detection and segmentation. The prompts you'll use for
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Custom Instructions for ChatGPT: Free Pack with 12 Commands
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Custom Instructions for ChatGPT are INSANE. But 98% don't know how to use them right. So I made Custom Instructions Pack with 12 powerful commands. And for the next 48 hours, it's FREE! (Normally $37) To get it, simply: • Like & RT
• Reply "GPT"
• Follow (I will DM you) -
LLMs can outperform humans via recall and fungible intelligence
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It’s for sure googlable, and many others could be reversed with rainbow tables. It is recall. Widespread fungibility of intelligence and recall means LLMs can at times zoom past human performance even on tasks the designers never considered. That’s what calculators don’t do.
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LLMs can outperform humans and keep improving
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I’m sure a machine made the hash but, yes, a human did copy and paste it into a webpage. The point stands the LLM is better at this task than that human, or any other human. More generally, LLMs do not always converge to human-level performance and then stop getting better.
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Sharing AI Prompts and Responses for Learning Purposes
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I wouldn't credit as co-authors, but I tend to share my prompts and responses when I use them for something interesting – more to
help other people learn how to use them than anything else