Brian Cheung (@thisismyhat) 's Twitter Profile
Brian Cheung

@thisismyhat

This is my hat, there are many like it, but this one is mine.

@MIT_CSAIL ๐Ÿงข / ex: @berkeley_ai ๐ŸŽ“ Google Bฬถrฬถaฬถiฬถnฬถ DeepMind ๐ŸŽฉ

ID: 3312108981

linkhttps://briancheung.github.io/ calendar_today07-06-2015 17:48:42

231 Tweet

4,4K Followers

573 Following

fly51fly (@fly51fly) 's Twitter Profile Photo

[LG] How to guess a gradient U Singhal, B Cheung, K Chandra, J Ragan-Kelley, J B. Tenenbaum, T A. Poggio, S X. Yu [UC Berkeley & MIT] (2023) arxiv.org/abs/2312.04709 - Backpropagation has limitations in memory usage and hardware efficiency when training large models. This

[LG] How to guess a gradient
U Singhal, B Cheung, K Chandra, J Ragan-Kelley, J B. Tenenbaum, T A. Poggio, S X. Yu [UC Berkeley & MIT] (2023)
arxiv.org/abs/2312.04709

- Backpropagation has limitations in memory usage and hardware efficiency when training large models. This
Phillip Isola (@phillip_isola) 's Twitter Profile Photo

Distributed training using parallel LoRAs, infrequently synced. My fav part is the analogy to git, where lots of coders can work together on a project, coordinated by simple operators like pull, commit, merge. Potential implications toward community training of big models.

Distributed training using parallel LoRAs, infrequently synced. 

My fav part is the analogy to git, where lots of coders can work together on a project, coordinated by simple operators like pull, commit, merge.

Potential implications toward community training of big models.
Brian Cheung (@thisismyhat) 's Twitter Profile Photo

Interesting set of evaluations for Claude 3 in the model card: --Autonomous Replication and Adaption --Biological Evaluations --Cyber Evaluations www-cdn.anthropic.com/de8ba9b01c9ab7โ€ฆ

Interesting set of evaluations for Claude 3 in the model card:
--Autonomous Replication and Adaption
--Biological Evaluations
--Cyber Evaluations

www-cdn.anthropic.com/de8ba9b01c9ab7โ€ฆ
Phillip Isola (@phillip_isola) 's Twitter Profile Photo

New paper: The Platonic Representation Hypothesis In which we posit that _different_ foundation models are converging to the _same_ representation of reality. paper: arxiv.org/abs/2405.07987 website: phillipi.github.io/prh/ code: github.com/minyoungg/platโ€ฆ 1/8

Vighnesh Subramaniam (@su1001v) 's Twitter Profile Photo

New paper๐Ÿ’ก! Certain networks can't perform certain tasks due to lacking the right prior ๐Ÿ˜ข. Can we make these untrainable networks trainable ๐Ÿค”? We can, by introducing the prior through representational alignment with a trainable network! This approach is called guidance. (1/8)

New paper๐Ÿ’ก!

Certain networks can't perform certain tasks due to lacking the right prior ๐Ÿ˜ข. Can we make these untrainable networks trainable ๐Ÿค”? We can, by introducing the prior through representational alignment with a trainable network! This approach is called guidance. (1/8)
Brian Cheung (@thisismyhat) 's Twitter Profile Photo

Learn about aligning minds and machines. Call for papers is live nowโ€”join us at ICLR 2025 #ICLR2025. representational-alignment.github.io/2025/

Learn about aligning minds and machines.

Call for papers is live nowโ€”join us at <a href="/iclr_conf/">ICLR 2025</a> #ICLR2025.

representational-alignment.github.io/2025/
Camera Culture Group (@cameraculture) 's Twitter Profile Photo

๐Ÿ”ฌโœจ Experience the First Signs of Vision at MIT Museum After Dark! Step into evolution & relive the 540-million-year journey from light-sensitive cells to modern sight. eyes.mit.edu/exhibitions/miโ€ฆ ๐Ÿ“… April 10, 2025 | โฐ 6-9 PM | ๐Ÿ“ MIT Museum | Tickets

Siddharth Suresh (@siddsuresh97) 's Twitter Profile Photo

๐Ÿ”„โœจ Come join us at the Second edition of the Re-Align workshop ICLR 2025! ๐Ÿš€๐Ÿง  The workshop explores the fascinating question of how artificial and biological systems align in their representations of the world. #ReAlign #ICLR2025

๐Ÿ”„โœจ Come join us at the Second edition of the Re-Align workshop <a href="/iclr_conf/">ICLR 2025</a>! ๐Ÿš€๐Ÿง  The workshop explores the fascinating question of how artificial and biological systems align in their representations of the world.  #ReAlign #ICLR2025