This is tricky: To do this, we’ll need ways for the human who’s supervising the model to use any relevant knowledge or skills that the model already has, even though they can’t trust the model to be reliably helpful.
PROMPT ENGINEERING
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Cohere NLP JumpStart Webinar with TechCrunch and Google Cloud
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Cohere is helping developers and startups build meaningful apps with language AI. Join us for an #NLPJumpStart session with Kemi Tijani, who will host the @TechCrunch webinar available on November 10, 2022, in partnership with @gcloudpartners
. → https://
hubs.li/Q01rFN3w0 -
HOLOSHEET and GPT3 Google Sheet for Deforum Prompts Demo
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@fabianstelzer will be demo’ing HOLOSHEET and a GPT3 powered Google Sheet for Deforum prompts. Check it out on Fabian’s Twitter:
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Demo Day: GPT-3 Powered Tools and Innovations
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Spend Friday at Demo Day with us, @fabianstelzer
, and Diwank Singh. We’ll be demo’ing GPT3 powered prompt generators on Google Sheets, satirical pitch decks, and more. Join our Discord to be a part of it: -
Few-shot Prompt Setup Notes for Scaling Law Experiments
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Some setup notes (cc @EthanJPerez
) – We used the exact 2-shot prompt for Quote Repetition, which is already U-shaped for Gopher/Chinchilla – We used fewer shots for Hindsight – We did few-shot instead of 0-shot for Negation QA – We also showed inverse scaling up to PaLM 62B -
U-shaped Scaling and the Limitations of Inverse Scaling Tasks
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Implications: 1. U-shaped scaling means that inverse scaling may not hold when extrapolated to larger models. 2. The term “inverse scaling task” is underspecified. A task can be inverse scaling for one type of prompting and positive or U-shaped for another type of prompting.
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CoT Prompting Defends Against Inverse Scaling in Math Tasks
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Second, we show that CoT prompting can defend against inverse scaling. For instance, CoT prompting achieves 100% on 7 out of 8 subtasks for Redefine Math.
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Large Language Models Achieve Human-Level Prompt Engineering
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Large Language Models Are Human-Level Prompt Engineers Zhou et al.: https://
arxiv.org/abs/2211.01910 #MachineLearning #DeepLearning #ArtificialIntelligence -
Using StableBoost to refine image generation through visual selection
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e.g. I used stableboost for this earlier tweet 🙂 – the prompt by itself gives bad, too diverse, not amazing results, but once I generated ~1000 I could visually narrow in on the composition I liked. Not sure how I'd get that by tuning the prompt alone