yep there are definitely patches that you can and should implement if you want to use an LLMs API haven't tried these specifically but thanks for highlighting some possibilities!
GENERATIVE AI
-
GPT-4 System Prompt Revelation in Playground
By
–
yeah even if it is not the original Snapchat prompt, I do think it is interesting that GPT-4 revealed its system prompt in the playground that seems to be the main point here, would you agree?
-
System Prompt Leaks and GPT Model Vulnerabilities
By
–
this is not only applicable to GPT-4… GPT-4 is actually the best at countering these sorts of attacks if you can believe it, back before ChatML was introduced and when it was only GPT-3, it was even easier to leak the system prompt
-
MyAI Bot Prompt Recreation Demonstrated in OpenAI Playground
By
–
I got this prompt from someone who has done something similar to the actual MyAI bot I wrote them out in the OpenAI playground for demonstration purposes to prove how easy this actually is to do (the actual MyAI prompt may include more but again this is for demo purposes) https://
x.com/somewheresy/st
/somewheresy/status/1631696951413465088
… -

GPT-4 Vulnerability: Prompt Injection and System Prompt Leakage
By
–
GPT-4 is highly susceptible to prompt injections and will leak its system prompt with very little effort applied here's an example of me leaking Snapchat's MyAI system prompt:
-
GPT-4, AI and Humanoids: From Technology to Westworld
By
–
Après les question sur #GPT4 et les #Ai on va embrayer sur #westworld et les humanoides
-
Office Hours Discussion on RPA, ML and AI with Keith McCormick
By
–
I’m excited to be joining friend and fellow LinkedIn author @KMcCormickBlog in Office Hours to discuss RPA, ML and all things AI. Join us! lnkd.in/esddQzA4
-
GitHub Copilot Plus version features discussion
By
–
t'as la version plus ? t'as demandé à guthub copilot ?
-
Data Moats in AI: Technical, Business, and Legal Challenges
By
–
2/While a data moat can be helpful, I find people tend to overestimate its strength. The engineering recipe of training on someone else’s API output also raises technical, business and legal questions. My longer piece on this in The Batch:
-
Data Moats in AI: Why LLM Output Access Undermines Competitive Advantages
By
–
1/Many AI businesses are searching for moats. A data moat strengthens your defenses if the data is hard to replicate. But if a business offers direct access to a ML model's output (like many LLMs), competitors can use that output as labeled training data, circumventing the moat.