We explain that these vulnerabilities derive from the fundamental properties of AR-LLMs and from how users interact with them through natural language-based instructions. We argue that these vulnerabilities--when coupled with how they are developed and distributed by commercial providers and as open-source releases--risk creating a systemic cybersecurity crisis. We offer seven recommendations designed to improve awareness of AR-LLMs' vulnerabilities, how they can be used

For the past decade, artificial intelligence has been used to recognize faces, rate creditworthiness and predict the weather. At the same time, increasingly sophisticated hacks using stealthier methods have escalated. The combination of AI and cybersecurity was inevitable as both fields sought better tools and new uses for their technology. But there's a massive problem that threatens to undermine these efforts and could allow adversaries to bypass digital defenses undetected. The danger is data poisoning: manipulating the information used to train machines offers a virtually untraceable method to get around AI-powered defenses.

You don't need to have been victimized by the WannaCry ransomware--or worried about hack attacks on presidential elections--to understand that cybersecurity is the most pressing technology problem of our time and may soon become the biggest problem, period. Fending off the onslaught of attacks is a nearly insurmountable task for security professionals. But it's a perfect job for machines that can parse thousands of logs a second and identify potential threats a human might not even see. That's why artificial intelligence (AI) has become a key weapon in the fight against cyber crooks, rogue hackers, and aggressive nation states. But experts also warn that AI is not a magic fix.

Alan Turing was the mastermind whose role in cracking the Nazi Enigma code helped the Allies win World War II. He built a machine to do the calculations necessary to decipher enemy messages and today is hailed as the father of the com puter and artificial intelligence. He's also widely believed to have been autistic. Kevin Pelphrey (@KevinPelphrey) is Carbonell Family Professor and director of the Autism and Neurodevel opmental Disorders Institute at George Washington University in Washington, DC. Turing was not diagnosed in his lifetime, but his mathematical genius and social inelegance fit the profile for autism spectrum disorder (ASD).