Harnessing AI's power, remember the crucial role and potential risk of prompting. Mind the risks and their mitigation. Learn more about safer AI applications here: https://
youtu.be/DW5PX-BWRlg
@whats_ai
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AI Power: Prompting Risks and Safer Application Strategies
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ChatGPT Security Breach: Dan Impersonation and Prompt Defense Techniques
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Security concerns arose after ChatGPT was hacked to impersonate "Dan", revealing restricted info. To prevent such issues, "prompt defense" techniques are used, establishing stricter task-specific prompts.
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Prompting Strategy: AI Model Efficiency and Security Vulnerabilities
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Curious about the AI tech easing your daily tasks? It hinges on 'prompting', a strategy for AI models like GPT-4. Today's app efficiency often depends on effectively using prompting. And those prompts that the user has access to are extra vulnerabilities to your app.
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ChatGPT Translation Security: Risks of Prompt Hacking Attacks
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ChatGPT's translation function is only as effective as the user's prompt. The potential risk here lies in 'prompt hacking', where the AI could be tricked into unwanted actions, posing privacy and security threats.
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Featuring Friends and Colleagues in AI Community
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Featuring many of my friends, including @SerranoAcademy @JayAlammar @cohere @wandb @bycloudai @altryne @jeremyphoward @learnprompting @towards_AI @activeloop @TDataScience @Gradio @huggingface @coursera @AndrewYNg @freeCodeCamp and more…
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Free Guide to Becoming a Large Language Models Expert
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Start with Large Language Models (LLMs) - Become an expert for free! My new curated list for getting into the #LLM world with the only prerequisite of a little Python knowledge.
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Prompt Engineering Techniques for Consistent LLM Results
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Use prompt engineering to tailor your LLMS to your needs. Use reliable system prompts, few-shot prompting, or chain-of-thought prompting for desirable, consistent LLM results.
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Mastering LLM Output Control and Model Parameter Tuning
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That's just the tip of the iceberg! To dig deeper into controlling your LLM outputs and optimally tuning your model's parameters, expand your knowledge with this newsletter iteration: https://
louisbouchard.substack.com/p/our-ai-tutor
-is-live
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Stop Sequences for Controlling LLM Output Length and Structure
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Stop sequences aid in managing the length and structure of model-generated text, useful when prompts require reasoning and referencing. This is key in the React framework where LLMs tackle simpler tasks sequentially to answer complex prompts.
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Model Behavior Optimization Through Examples and Parameter Tuning
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Identify your model's desired behavior. Create user-model interaction examples to assess its performance and identify improvement areas. Enhancements can be achieved through adjusting decoding parameters.