Michael Aerni
@aemai.bsky.social
AI privacy and security | PhD student in the SPY Lab at ETH Zurich | Ask me about coffee ☕️
Reposted by Michael Aerni
Recent LLM forecasters are getting better at predicting the future. But there's a challenge: How can we evaluate and compare AI forecasters without waiting years to see which predictions were right? (1/11)
January 11, 2025 at 1:53 AM
Recent LLM forecasters are getting better at predicting the future. But there's a challenge: How can we evaluate and compare AI forecasters without waiting years to see which predictions were right? (1/11)
I am in beautiful Vancouver for #NeurIPS2024 with those amazing folks!
Say hi if you want to chat about ML privacy and security
(or speciality ☕)
Say hi if you want to chat about ML privacy and security
(or speciality ☕)
SPY Lab is in Vancouver for NeurIPS! Come say hi if you see us around 🕵️
December 10, 2024 at 7:48 PM
I am in beautiful Vancouver for #NeurIPS2024 with those amazing folks!
Say hi if you want to chat about ML privacy and security
(or speciality ☕)
Say hi if you want to chat about ML privacy and security
(or speciality ☕)
🔥 I'm thrilled that I'll be spending next year in the group of @floriantramer.bsky.social at ETH Zurich, working on privacy and memorization in ML 🔥
(Not an announcement, just what I usually do. It's a really great group full of incredibly amazing people that I am thrilled to work with every day!)
(Not an announcement, just what I usually do. It's a really great group full of incredibly amazing people that I am thrilled to work with every day!)
Come do open AI with us in Zurich!
We're hiring PhD students, postdocs (and faculty!)
We're hiring PhD students, postdocs (and faculty!)
Zurich is a great place to live and do research. It became a slightly better one overnight! Excited to see OAI opening an office here with such a great starting team 🎉
December 6, 2024 at 4:29 PM
🔥 I'm thrilled that I'll be spending next year in the group of @floriantramer.bsky.social at ETH Zurich, working on privacy and memorization in ML 🔥
(Not an announcement, just what I usually do. It's a really great group full of incredibly amazing people that I am thrilled to work with every day!)
(Not an announcement, just what I usually do. It's a really great group full of incredibly amazing people that I am thrilled to work with every day!)
If it's curated by @javirandor.com then you know it's amazing!
I am curating a list of researchers working on AI Safety and Security here go.bsky.app/BcjeVbN.
Reply to this post with your user or other people you think should be included!
Reply to this post with your user or other people you think should be included!
AI Safety and Security
Join the conversation
go.bsky.app
December 4, 2024 at 12:46 PM
If it's curated by @javirandor.com then you know it's amazing!
Reposted by Michael Aerni
Zurich is a great place to live and do research. It became a slightly better one overnight! Excited to see OAI opening an office here with such a great starting team 🎉
Ok, it is yesterdays news already, but good night sleep is important.
After 7 amazing years at Google Brain/DM, I am joining OpenAI. Together with @xzhai.bsky.social and @giffmana.ai, we will establish OpenAI Zurich office. Proud of our past work and looking forward to the future.
After 7 amazing years at Google Brain/DM, I am joining OpenAI. Together with @xzhai.bsky.social and @giffmana.ai, we will establish OpenAI Zurich office. Proud of our past work and looking forward to the future.
December 4, 2024 at 9:46 AM
Zurich is a great place to live and do research. It became a slightly better one overnight! Excited to see OAI opening an office here with such a great starting team 🎉
Reposted by Michael Aerni
Ensemble Everything Everywhere is a defense against adversarial examples that people got quite exited about a few months ago (in particular, the defense causes "perceptually aligned" gradients just like adversarial training)
Unfortunately, we show it's not robust...
arxiv.org/abs/2411.14834
Unfortunately, we show it's not robust...
arxiv.org/abs/2411.14834
Gradient Masking All-at-Once: Ensemble Everything Everywhere Is Not Robust
Ensemble everything everywhere is a defense to adversarial examples that was recently proposed to make image classifiers robust. This defense works by ensembling a model's intermediate representations...
arxiv.org
November 25, 2024 at 8:38 AM
Ensemble Everything Everywhere is a defense against adversarial examples that people got quite exited about a few months ago (in particular, the defense causes "perceptually aligned" gradients just like adversarial training)
Unfortunately, we show it's not robust...
arxiv.org/abs/2411.14834
Unfortunately, we show it's not robust...
arxiv.org/abs/2411.14834