BIBHORR AI RAKSHA FORMULA

BIBHORR AI RAKSHA FORMULA

Bibhorr AI Raksha Formula (BAIRF) is the world’s first comprehensive AI Defense and Security Strategy Formula specifically developed to scrutinize the authenticity and reliability of nefarious and purported AI chatbots such as ChatGPT, Gemini, Grok, Copilot, GitHub Copilot X, AutoGPT, BabyAGI, Veo, Genie, and more (being violently marketed and sold as technology).

This BAIRF strategic approach entails a multifaceted investigation process that delves into the intricate algorithms and underlying mechanisms of these precarious chatbots to assess their potential vulnerabilities and verify their compliance with established security protocols.

The insights gained from BAIRF evaluations can inform decision-making processes regarding the integration and utilization of purported AI chatbots in various applications, guiding stakeholders in making informed choices that align with their security objectives and risk tolerance levels.

Overall, Bibhorr AI Raksha Formula serves as a crucial tool in navigating the negatively evolving landscape of AI technology, fostering confidence in the reliability and security of non-secure AI chatbot interactions within diverse operational contexts.

Bibhorr AI Raksha Formula demands the following evidence from the nefarious chatbots:

  • The evidence on the use of non-plagiarized training content and data
  • The evidence of not mimicking real persons’ voice, and facial features 
  • The evidence on the use of advanced technology as they claim
  • The evidence regarding the control of the non-empathetic language communicated by the chatbots
  • The public disclosure on data breaches from government offices, personal emails, etc.
  • The proof of empathetic attitude among business personnel in the marketing of their chatbots
  • The evidence regarding the control of biased and hateful information abruptly thrown by the chatbots
  • The public disclosure regarding the collusion with monarchies, banks, bureaucrats, political leaders, businesses, etc.
  • The evidence regarding the responsible use of users’ data
  • The evidence regarding the future use of users’ data
  • The evidence regarding the future currency integrations like cryptocurrency, or personal currency, etc.