⏪ Reverse Engineering PromptsPlus: No More NonCompete Contracts. + Microsoft's Phi-3 Small Language Models Lead the Way.Get in Front of 50k Tech Leaders: Grow With Us In Partnership with Diffuse: Unlimited Personalized AI Videos. Please help us by filling out this form to get to know you better.
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Reverse Engineering PromptsReverse prompting is a technique used in interacting with AI models, particularly those involved in text generation, but can also be done with images, bu uploading an image and asking for a prompt to create such an image. It involves starting with the desired output or answer and working backward to create a prompt that will lead the AI to produce that specific outcome. This method can be particularly useful when you want the AI to generate content that aligns closely with specific goals or formats.
Step 1: Identify Desired Output
Step 2: Extract Core Elements
Step 3: Construct the Prompt
Step 4: Test and Refine
This technique is akin to an image search where you seek specific elements within an image that text searches fail to identify. By creatively using images, you can craft prompts to design similar products or concepts. Similarly, in text applications, this approach enables you to uncover more detailed and in-depth information about a particular topic.
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Creators and everyday users love it - we see a 50% content share rate and many creators using it on IG and TT. No More NonCompete Contracts.The US Federal Trade Commission (FTC) has issued a final rule that bans most noncompete agreements, aiming to increase job mobility and wage growth. This change is expected to generate 8,500 new businesses annually and increase average worker wages by $524 per year. Particularly impactful in the tech sector, where 36% of engineers and 35% of tech workers are currently restricted by noncompetes, the rule could boost innovation and entrepreneurship. While it may face legal challenges, such as those anticipated by the US Chamber of Commerce, it aligns with trends in states like California, where the absence of noncompetes has supported tech industry growth. Microsoft's Phi-3 Small Language Models Lead the WayThe Phi-3 small language models (SLMs) from Microsoft offer cost-effective and flexible AI solutions, requiring less computational power and functioning offline. They excel in tailored tasks and are scalable to various devices. However, they may not handle complex tasks as well as larger language models (LLMs) and might lack the same depth of knowledge and generalization. Despite this, Phi-3 models represent a strategic addition to AI tools, providing specific advantages where speed and flexibility are crucial. Microsoft's Phi-3 series promises significant advancements in AI accessibility and performance, inspired by children's learning and trained on high-quality datasets. These models, like Phi-3-mini with 3.8 billion parameters, are ideal for environments with limited connectivity or strict data privacy requirements. Available in the Microsoft Azure AI Model Catalog and on Hugging Face, a platform for machine learning models, as well as Ollama, a lightweight framework for running models on a local machine. 📰 Publications I am currently reading and recommending:
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Wednesday, April 24, 2024
⏪ Reverse Engineering Prompts
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