What do you get when you combine artificial intelligence (AI) and cybersecurity? If you answered with faster threat detection, quicker response times and improved security measures... you're only partially correct. Here's why.
Today, we’re excited to announce a new integration with Amazon SageMaker! SageMaker helps companies build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. By leveraging JFrog Artifactory and Amazon SageMaker together, ML models can be delivered alongside all other software development components in a modern DevSecOps workflow, making each model immutable, traceable, secure, and validated as it matures for release.
Keeping up with threats is an ongoing problem in the constantly changing field of cybersecurity. The integration of artificial intelligence (AI) into cybersecurity is emerging as a vital roadmap for future-proofing cybersecurity, especially as organizations depend more and more on digital twins to mimic and optimize their physical counterparts.
Artificial Intelligence (AI) and machine learning have become integral tools for organizations across various industries. However, the successful adoption of these technologies requires a careful balance between business objectives and security requirements.
The future is notoriously hard to see coming. In the 1997 sci-fi classic Men in Black — bet you didn’t see that reference coming — a movie about extraterrestrials living amongst us and the secret organization that monitors them, the character Kay, played by the great Tommy Lee Jones, sums up this reality perfectly: While vistors from distant galaxies have yet to make first contact — or have they? — his point stands.
