Generative AI, ChatGPT and OpenAI, large language models (LLMs) — these are all now near-daily buzzwords and phrases heard in conversations across the cybersecurity community. It’s clear that chatbot-based artificial intelligence (AI) continues to fuel a particularly heady version of the technology hype cycle, but there’s also an astounding amount of practical activity.
To wit: Security vendors large and small have integrated AI chatbots into their offerings (looking at you, Charlotte from CrowdStrike); investment in GPT-based AI security is one of the most vibrant areas of funding in startups these days; and it’s impossible not to stumble across research outlining potential generative AI-related cybersecurity threats and how to combat them (phishing and deepfakes and malware, oh my!). It’s a lot. In this featured piece, Dark Reading leaves behind the hill of impossible expectations for a bit and takes a real-world look at how the security conversation around this new generation of AI is starting to deepen. That includes sober assessments from enterprise users and analysts; and a look at efforts to address some of the cyber-risk that came to light in the first flush of irrational exuberance that followed ChatGPT’s launch last November.
Full story : 6 Ways Cybersecurity Is Gut-Checking the ChatGPT Frenzy.
