I’ve just dropped a fresh piece on Medium that’s pretty close to my tech-geek heart. It’s all about the double-edged sword of Large Language Models (LLMs) and the privacy puzzles they bring to the table.
Here’s the techy scoop:
So, I’ve been noodling over how these LLMs are genius at churning out human-like text, thanks to gobbling up ginormous data meals. But here’s the kicker – sometimes they snack on sensitive info, and that’s where things get dicey. In my article, I dive into this whole privacy brouhaha, talking about how these clever bots can accidentally spill the beans on personal deets.
I also chat about some brainy works that dig into this stuff, like the research by Carlini and his crew in 2019, and the deep dive into Differential Privacy by Abadi and pals in 2016. Plus, I get into the nitty-gritty of privacy-preserving algorithms and the trade-offs between keeping things hush-hush and making the models super useful.
Why should you care?
Well, if you’re slinging code for these LLMs or just curious about how your secrets are kept secret in the age of AI, this is for you. It’s not just about the “what” – it’s about the “how” and the “why” we need to keep user trust on lock in this wild west of tech.
Check out my full thoughts and let’s get into the weeds of AI and privacy together. Catch the full article here and let’s get this convo going!
The post Exploring User Privacy in the Age of Language Models first appeared on Farid Fadaie - Engineering, Product and life.
Top comments (0)