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Generative AI

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Safeguarding Enterprise Software: Protecting Against Security Pitfalls of Generative AI and LLMs

Safeguarding Enterprise Software: Protecting Against Security Pitfalls of Generative AI and LLMs

In today’s digital landscape, the transformative power of artificial intelligence (AI) cannot be overstated. Enterprises across various industries are already exploring ways to leverage AI to improve productivity and enhance customer experiences. One area that has witnessed significant advancements is the usage of Generative AI and Large Language Models (LLMs). However, as cybersecurity professionals, it is crucial to understand the potential security pitfalls associated with their implementation. In this blog, we explore how generative AI and LLMs can be utilized in enterprise software, and discuss effective strategies to guard against the inherent risks.

OpenAI’s Privacy Fine Stresses Importance of Data Security Amidst AI Advancements

OpenAI’s Privacy Fine Stresses Importance of Data Security Amidst AI Advancements

As we venture further into the age of artificial intelligence, the phrase “you can’t put the genie back in the bottle” takes on profound significance. It describes a phenomenon that has become all too familiar with generative AI — once these systems learn and generate based on specific data sets, it’s almost impossible to unlearn or retrieve that information. This means that if personal or sensitive data is accidentally fed into these systems, the potential for misuse or exposure becomes a looming threat that is virtually impossible to mitigate after the fact.