Security and privacy are particularly important when it comes to AI because confidential data is often at the heart of AI and ML projects.
This blog post focuses on securing the following high-level notebook flow at all relevant security layers.
Google Cloud is adding to their portfolio of blueprints with the publication of their Protecting confidential data in AI Platform Notebooks blueprint guide and deployable blueprint, which can help us apply data governance and security policies that protect our AI Platform Notebooks containing confidential data.
From our JupyterLab environment to AI Platform Notebook and its security perimeter!
Awesome, right? What do you think?