Privacy in the age of generative AI
The core challenge posed by generative AI right now is that unlike conventional applications, LLMs have no “delete” button.
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privacy
Privacy-friendly machine learning data sets: synthetic data
Statistically-relevant data, but not actually exploitable.
Privacy is a moving target. Here’s how engineering teams can stay on track (Ep. 453)
On this sponsored episode of the podcast, we talk with Rob Picard and Matt Cooper of Vanta.
Using synthetic data to power machine learning while protecting user privacy
On this episode, we talk to John Myers, CTO and cofounder of Gretel, a company that provides synthetic data for training machine learning models without exposing any of their customers personally identifiable information.
Privacy is an afterthought in the software lifecycle. That needs to change.
The key to combining privacy and innovation is baking it into the SDLC. Analogous to application security's (AppSec) upstream shift into the development cycle, privacy belongs at the outset of development, not as an afterthought. Here's why.
Podcast 260: Silicon Valley Exodus
The center of gravity for software is shifting. Tik Tok is a Chinese-born, consumer-facing, global hit. Meanwhile, developers are fleeing San Francisco as the pandemic rages on.
Podcast 232: Can We Decentralize Contact Tracing?
Are there lessons to be learned from South Korea that could work in other countries?