it was actually fine – I just asked "what are they key reasons why company X (from the pdf I uploaded) would succeed or fail" and it generated totally reasonable Qs that a VC takes 10 years to learn 🙂
PROMPT ENGINEERING
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Exploring DreamBooth for Futuristic AI Image Generation
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All of them are really nice 😛 there’s this one futuristic one that i like Gonna try dreambooth today
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Using AI Models for Comparative Analysis: Tools and Platforms
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Anyone know of a way to use an AI model to compare apples and oranges?(Metaphorically.) I’ve got a few idea for comparing/contrasting some stuff, but not sure which platforms/tools/etc might be helpful or even feasible.
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Lennybot: ChatGPT-4 Chatbot Trained on Newsletter and Podcasts
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Announcing the new and improved Lennybot A ChatGPT-4 powered chatbot that is trained on all of my newsletter content AND now all of my podcast transcripts. Also, includes links to all of the content it references. Ask it:
✓ How do I get better at strategy?
✓ How do I -
Techniques for Constructing Prompts Command Model
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Prompts can be as simple as a one-liner, or they can be as complex as multiple layers of specific information. In this article, we look at some techniques for constructing prompts for the Command model. https://
short.cohere.ai/construct?utm_
source=twitter&utm_medium=social
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Explore Different Steps, Schedulers and Guidance Scales
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Try out different steps, schedulers and guidance scales pic.twitter.com/mp6Gb1GcAt
— Replicate (@replicate) 28 juillet 2023Try out different steps, schedulers and guidance scales
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Interactive Guide to Using SDXL for Image Generation
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We've put together an interactive guide on how to use SDXL.
Or, how we learned to make really weird cats. Interactively explore resolutions, guidance scales, steps, schedulers and refiner settings. https://
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A/B Testing Strategies and Best Practices Episode
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Today's episode with @ronnyk is killing it. Don't miss it.
— Lenny Rachitsky (@lennysan) 27 juillet 2023
Whether you're just getting started with A/B testing, looking to fine-tune your existing approach, or even just thinking about it, there's a lot to learn here. The stories alone are worth the price of admission. pic.twitter.com/Sa6Wv6mi75Today's episode with @ronnyk is killing it. Don't miss it. Whether you're just getting started with A/B testing, looking to fine-tune your existing approach, or even just thinking about it, there's a lot to learn here. The stories alone are worth the price of admission.
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Visual Foundation Models: Architectures, Training, and Prompting Survey
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Foundational Models Defining a New Era in Vision: A Survey and Outlook A comprehensive survey of visual foundation models. Covers emerging architectures(for vision+other modalities), training objectives, pre-training datasets, fine-tuning mechanisms, and the common prompting
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LLM Text Adversarial Problems Easier Than Vision Recognition
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I do agree that trying to solve this within LLM will be hard. But the problem seems easier to solve in practice than vision, unless people come up with a way to make an adversarial string that reads like natural language