you can train multiple concepts at once. e.g i can have me as concept 1 and my dog as concept 2. then i can generate images with both concepts in it
PROMPT ENGINEERING
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BLOOM+1 Performance on Multilingual Prompting Benchmarks
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I wonder how well BLOOM+1 would do on the multilingual prompting benchmarks proposed here:
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Iterative Optimization: Trial and Error in AI Creative Process
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Lots and lots of trying and Googling. Trying words, camera lenses, lighting etc. Just try infinite times
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Automated Generation of Yes-No Questions for LM Behavior Evaluation
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We explored approaches with varying amounts of automation and human effort. In the simplest case, we generated thousands of yes-no questions for diverse behaviors just by instructing an LM (and filtering out bad examples with another LM).
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ChatGPT Frontend Automation Now Widely Hacked
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Everyone already hacked the front end of ChatGPT to automate it yes, super easy
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Are ChatGPT-style replies becoming common on social media?
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Increasingly seeing ChatGPT style replies to my tweets, did AI write this?
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FITM definition for Copilot’s cursor placeholder
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FITM = fill-in-the-middle, models trained to generate text to fill in a placeholder within the prompt rather than complete it from the end. For Copilot, the placeholder is the cursor.
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Copilot’s stage play: a subtle art RLHF aims to replace.
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Nothing I’ve posted to Twitter will teach you as much as this prompt. Every Copilot completion is a tiny stage play for an LLM audience, with your file on stage and a backdrop curtain designed by a procedural script. A masterpiece of the subtle art form RLHF aims to replace.
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GitHub Copilot’s implicit prompt engineering creates a competitive moat
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When you hit tab in GitHub Copilot, you’re FITM-completing a prompt of your file with an implicit comment header added, and it takes pages to describe what might be in that header. That’s prompt engineering. That’s a moat.
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GPT-3/LLM prompts as assembly code, need prompt compilers
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I increasingly see GPT‑3/LLM prompts as assembly code, not as human interface. We shouldn’t be writing prompts, but prompt compilers. A template string is not a moat.