Every year, JFrog brings the DevOps community and some of the world’s leading corporations together for the annual swampUP conference, aimed at providing real solutions to developers and development teams in practical ways to prepare us all for what’s coming next.

Today’s software applications power almost every aspect of our lives, and ensuring the security of these applications is paramount. Threat actors can cause devastating consequences for companies, leading to financial losses, reputational damage, and legal repercussions. Companies building commercial or in-house applications must adopt robust security measures throughout their software development lifecycle to avoid releasing vulnerable code.

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.

When scanning packages, CVE (Common Vulnerabilities and Exposures) scanners can find thousands of vulnerabilities. This leaves developers with the painstaking task of sifting through long lists of vulnerabilities to identify the relevance of each, only to find that many vulnerabilities don’t affect their artifacts at all.