Aleksander Madry @aleks_madry
Head of Preparedness at OpenAI and MIT faculty (on leave). Working on making AI more reliable and safe, as well as on AI having a positive impact on society. madrylab.mit.edu Cambridge, MA Joined July 2017-
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Our second (and final) blog post on model components is now out: we show that component attributions enable model editing! See the blog post for more: gradientscience.org/modelcomponent… Paper: arxiv.org/abs/2404.11534 (this time with no typos :) Code: github.com/MadryLab/model…
Our second (and final) blog post on model components is now out: we show that component attributions enable model editing! See the blog post for more: gradientscience.org/modelcomponent… Paper: arxiv.org/abs/2404.11534 (this time with no typos :) Code: github.com/MadryLab/model…
New work with @andrew_ilyas and @aleks_madry on tracing predictions back to individual components (conv filters, attn heads) in the model! Paper: arxiv.org/abs/2404.11534 Thread: 👇
New work with @andrew_ilyas and @aleks_madry on tracing predictions back to individual components (conv filters, attn heads) in the model! Paper: arxiv.org/abs/2404.11534 Thread: 👇
New work led by @harshays_ on studying how model components affect predictions! Paper link: arxiv.org/abs/2404.11534 Blog: gradientscience.org/modelcomponents
New work led by @harshays_ on studying how model components affect predictions! Paper link: arxiv.org/abs/2404.11534 Blog: gradientscience.org/modelcomponents
Interested in chatting at ICLR?forms.gle/dbtmF5EeyM5H1d…
We are really excited to host @aleks_madry from @OpenAI at the PASS seminar on 3/26, 2pm ET! Submit your questions about the Preparedness team: tinyurl.com/pass-question, and join our mailing list to receive notifications about talks: tinyurl.com/pass-mailing
We are really excited to host @aleks_madry from @OpenAI at the PASS seminar on 3/26, 2pm ET! Submit your questions about the Preparedness team: tinyurl.com/pass-question, and join our mailing list to receive notifications about talks: tinyurl.com/pass-mailing
The secret is out 👀
Very proud to be part of this Amazing MURI Team with Christos Papadimitriou @Columbia, Erik Demaine, @KonstDaskalakis, @aleks_madry @MIT, @zicokolter , @rsalakhu, Katia Sycara @CMU, Kamalika Chaudhuri @UCSD, and our own @FeiziSoheil @umdcs.
Very proud to be part of this Amazing MURI Team with Christos Papadimitriou @Columbia, Erik Demaine, @KonstDaskalakis, @aleks_madry @MIT, @zicokolter , @rsalakhu, Katia Sycara @CMU, Kamalika Chaudhuri @UCSD, and our own @FeiziSoheil @umdcs.
Congratulations @ShibaniSan, this is extremely well deserved!
Congratulations @ShibaniSan, this is extremely well deserved!
We are pleased to announce the 2021 AAAI/ACM SIGAI Dissertation Award Winner. Congratulations to Shibani Santurkar, Massachusetts Institute of Technology for her work entitled Machine Learning Beyond Accuracy: A Features Perspective On Model Generalization. And congratulations…
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Introducing the Instruction Hierarchy, our latest safety research to advance robustness for prompt injections and other ways of tricking LLMs into executing unsafe actions. More details: arxiv.org/abs/2404.13208
New work with @andrew_ilyas and @aleks_madry on tracing predictions back to individual components (conv filters, attn heads) in the model! Paper: arxiv.org/abs/2404.11534 Thread: 👇
How do model components (conv filters, attn heads) collectively transform examples into predictions? Is it possible to somehow dissect how *every* model component contributes to a prediction? w/ @harshays_ @andrewilyas, we introduce a framework for tackling this question!…
Very cool research — a space to watch.
How do model components (conv filters, attn heads) collectively transform examples into predictions? Is it possible to somehow dissect how *every* model component contributes to a prediction? w/ @harshays_ @andrewilyas, we introduce a framework for tackling this question!…
New work led by @harshays_ on studying how model components affect predictions! Paper link: arxiv.org/abs/2404.11534 Blog: gradientscience.org/modelcomponents
How do model components (conv filters, attn heads) collectively transform examples into predictions? Is it possible to somehow dissect how *every* model component contributes to a prediction? w/ @harshays_ @andrewilyas, we introduce a framework for tackling this question!…
Can you train a generative model using only noisy data? If you can, this would alleviate the issue of training data memorization plaguing certain genAI models. In exciting work with @giannis_daras and @AlexGDimakis we show how to do this for diffusion-based generative models.
Consistent Diffusion Meets Tweedie. Our latest paper introduces an exact framework to train/finetune diffusion models like Stable Diffusion XL solely with noisy data. A year's worth of work breakthrough in reducing memorization and its implications on copyright 🧵
Big congratulations to Avi Wigderson of IAS Princeton for winning the Turing Award in CS. Truly an all-time great in theoretical computer science and discrete math. Also one of the nicest human beings I know --friend and mentor to so many (including me) tinyurl.com/fz5vxxaf
We just released improvements to GPT-4 Turbo
Majorly improved GPT-4 Turbo model available now in the API and rolling out in ChatGPT.
If you haven't disabled voice authentication for your bank account and had a conversation with your family about AI voice impersonation yet, now would be a good time.
We're sharing our learnings from a small-scale preview of Voice Engine, a model which uses text input and a single 15-second audio sample to generate natural-sounding speech that closely resembles the original speaker. openai.com/blog/navigatin…
I was quite curious what OpenAI's preparedness unit is working on, and @aleks_madry gave a good high-level view in our Princeton Alignment and Safety seminar youtube.com/watch?v=pe3XF0… Kudos to @SadhikaMalladi and @YangsiboHuang for interesting followup Q&A
Looking forward to understanding from @aleks_madry about @OpenAI 's thinking on near-term AI risks, responsibility of the preparedness unit. Tune in to the seminar tomorrow (Tuesday) 2pm EST!
REMINDER PASS seminar: Tomorrow at 2pm ET @aleks_madry from @OpenAI will speak on AI Preparedness! Live: youtube.com/@PrincetonPLI/… Submit questions: tinyurl.com/pass-question Recordings later at: youtube.com/@PrincetonPLI
@zacharylipton SGD is an alignment technique for randomly initialized weights
We are really excited to host @aleks_madry from @OpenAI at the PASS seminar on 3/26, 2pm ET! Submit your questions about the Preparedness team: tinyurl.com/pass-question, and join our mailing list to receive notifications about talks: tinyurl.com/pass-mailing
PASS seminar on 3/26 2pm ET! Speaker: Aleksander Madry @aleks_madry from @OpenAI Topic: AI Preparedness Live: youtube.com/@PrincetonPLI/… Submit questions: tinyurl.com/pass-question Recordings later at: youtube.com/@PrincetonPLI
Huh, seems like this AGI stuff was all a ruse so that OpenAI could build up a legit CS Theory department.
One year since GPT-4 deployment: From GPT-1 and 2 establishing the language model paradigm, through GPT-3's scaling predictions, to GPT-4 showing how complex systems emerge, mimicking nature’s unpredictable patterns from simple elements. An exploration from observation to deep,…
Very proud to be part of this Amazing MURI Team with Christos Papadimitriou @Columbia, Erik Demaine, @KonstDaskalakis, @aleks_madry @MIT, @zicokolter , @rsalakhu, Katia Sycara @CMU, Kamalika Chaudhuri @UCSD, and our own @FeiziSoheil @umdcs.
.@UofMaryland's CS Department joins a @DeptofDefense-selected team for the 2024 MURI program. @MTHajiaghayi & @FeiziSoheil are part of the team exploring "Algorithms, Learning & Game Theory," focusing on decision-making in multi-agent systems. Read more: go.umd.edu/MURI
There'd be less brain drain if more schools enabled the sort of fundamental curiosity-driven research that should be academia's strength. If the only viable research style is make-number-go-up, you might as well do that at a company.
Academic brain drain is definitely a part of the story with ongoing regulatory capture for AI.
i'm very happy to welcome our new board members: fidji simo, sue desmond-hellmann, and nicole seligman, and to continue to work with bret, larry, and adam. i'm thankful to everyone on our team for being resilient (a great openai skill!) and staying focused during a challenging…
Governance of an institution is critical for oversight, stability, and continuity. I am happy that the independent review has concluded and we can all move forward united. It has been disheartening to witness the previous board’s efforts to scapegoat me with anonymous and…
Can hazardous knowledge be unlearned from LLMs without harming other capabilities? We’re releasing the Weapons of Mass Destruction Proxy (WMDP), a dataset about weaponization, and we create a way to unlearn this knowledge. 📝arxiv.org/abs/2403.03218 🔗wmdp.ai
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