AI and machine learning (ML) have hit the mainstream as the tools people use everyday – from making restaurant reservations to shopping online – are all powered by machine learning. In fact, according to Morgan Stanley, 56% of CIOs say that recent innovations in AI are having a direct impact on investment priorities. It’s no surprise, then, that the ML Engineer role is one of the fastest growing jobs.
Phishing attacks have always been detected through broken English, but now generative artificial intelligence (AI) tools are eliminating all those red flags. OpenAI ChatGPT, for instance, can fix spelling mistakes, odd grammar, and other errors that are common in phishing emails. This advancement in AI technology has made it easier for even amateur hackers to analyze vast amounts of publicly available data about their targets and create highly personalized and convincing emails within seconds.
Imagine an AI overlord sitting in a dark basement, plotting world domination through cybercrime. While the idea might seem like a sci-fi flick, it’s actually closer to reality than we think. AI has emerged as a game changer in a constantly evolving cyber landscape. AI algorithms can learn and adapt to security measures quickly, making them the ultimate cyber villains.
Welcome to our cheat sheet covering the OWASP Top 10 for LLMs. If you haven’t heard of the OWASP Top 10 before, it’s probably most well known for its web application security edition. The OWASP Top 10 is a widely recognized and influential document published by OWASP focused on improving the security of software and web applications. OWASP has created other top 10 lists (Snyk has some too, as well as a hands-on learning path), most notably for web applications.
AI is one of the hottest topics in tech right now. More than half of consumers have already tried generative AI tools like ChatGPT or DALL-E. According to a Gartner poll, 70% of executives say their business is investigating and exploring how they can use generative AI, while 19% are in pilot or production mode. Business use cases for AI range from enhancing the customer experience (38%), revenue growth (26%), and cost optimization (17%).
