Generative Artificial Intelligence (AI) has revolutionized various fields, from creative arts to content generation. However, as this technology becomes more prevalent, it raises important considerations regarding data privacy and confidentiality. In this blog post, we will delve into the implications of Generative AI on data privacy and explore the role of Data Leak Prevention (DLP) solutions in mitigating potential risks.
I remember when the first iPhone was announced in 2007. This was NOT an iPhone as we think of one today. It had warts. A lot of warts. It couldn’t do MMS for example. But I remember the possibility it brought to mind. No product before had seemed like anything more than a product. The iPhone, or more the potential that the iPhone hinted at, had an actual impact on me. It changed my thinking about what could be.
The Biden Administration’s recent moves to promote “responsible innovation” in artificial intelligence may not fully satiate the appetites of AI enthusiasts or defuse the fears of AI skeptics. But the moves do appear to at least start to form a long-awaited framework for the ongoing development of one of the more controversial technologies impacting people’s daily lives. The May 4 announcement included three pieces of news.
Artificial intelligence (AI) made a larger-than-usual splash recently when word broke of an AI-powered password cracker. I have a bit of AI fatigue, but these stories immediately grabbed my attention — they had me at “passwords.”
CISA issues a joint advisory on Russia’s Snake malware operation, hackers use ChatGPT lures to spread malware on Facebook, and a new phishing-as-a-service tool appears in the wild.
The rise of low-code/no-code platforms has empowered business professionals to independently address their needs without relying on IT. Now, the integration of generative AI into these platforms further enhances their capabilities and eliminates entry barriers. However, as everyone becomes a developer, concerns about security risks arise.
