Rohan Bavishi @code_monet

Code @ Anthropic. Previously Amazon AGI Autonomy, @AdeptAILabs. Ph.D. @Berkeley_EECS. Undergrad @IITKanpur. rbavishi.github.io Indianapolis, IN Joined April 2010

Tweets

73
Followers

612
Following

201
Likes

937

Anthropic @AnthropicAI

4 months ago

A statement on the comments from Secretary of War Pete Hegseth. anthropic.com/news/statement…

3K 6K 42K 17.8M 5K

View Details

Introducing Claude Opus 4.5: the best model in the world for coding, agents, and computer use. Opus 4.5 is a step forward in what AI systems can do, and a preview of larger changes to how work gets done.

1K 2K 19K 7.8M 3K

View Details

Rohan Bavishi @code_monet

2 years ago

@josepablocam All the best for your future endeavors! I'm glad we overlapped at Prose!

0 0 1 156 0

View Details

Rohan Bavishi @code_monet

2 years ago

Bonus: We DPO'ed Fuyu-Heavy on the public Ultrafeedback dataset and got competitive results on MT-Bench and AlpacaEval 1.0! Plus it powers the model used in the chat demo you see here, underlining the balance between image and language modeling that Fuyu-Heavy achieves.

3 4 47 9K 8

View Details

AI Engineer @aiDotEngineer

3 years ago

From spreadsheets to Airbnb listings, the ability to 'zoom out' using AI lets us quickly understand and act. It's not just about more data; it's about clearer, concise, actionable insights. A look into what zooming out could look like from @Wattenberger and @AdeptAILabs

4 9 82 21K 36

View Details

Rohan Bavishi @code_monet

3 years ago

🕵🏽‍♂️

0 0 5 440 0

View Details

Rohan Bavishi @code_monet

3 years ago

@zongheng_yang @joe_hellerstein @pabbeel Congrats!

0 0 1 91 0

View Details

Rohan Bavishi @code_monet

3 years ago

@duskybomb @Stanford Congratulations! :)

1 0 1 459 0

View Details

Rohan Bavishi @code_monet

3 years ago

@ElectronicKiwi @ASPLOSConf Congrats on the acceptance!

0 0 1 72 0

View Details

Tri Dao @tri_dao

3 years ago

I’ve been working with @AdeptAILabs and we’ve made FlashAttention even faster for long sequences! For seqlen 8K, FlashAttention is now up to 2.7x faster than a standard PyTorch implementation even at small batch, making it easier to train better LMs with longer context 1/7

Tri Dao @tri_dao

4 years ago

Announcing FlashAttention, a fast and memory-efficient attention algorithm with no approximation! 📣 w/ @realDanFu By reducing GPU memory reads/writes, FlashAttention runs 2-4x faster & requires 5-20x less memory than PyTorch standard attention, & scales to seq. length 64K. 1/

30 338 2K 0 616

7 82 591 229K 170

View Details

Maxwell Nye @Maxwell_Nye

4 years ago

This might have gotten lost, but this vid demonstrates voice input! Complaints to me if you don’t like the voice in question :)

2 3 27 0 2

View Details

Rohan Bavishi @code_monet

4 years ago

Come see what our team is building!

0 0 9 0 0

View Details

Justin Lubin @jplubin

4 years ago

Are you an #Elm programmer interested in furthering our understanding of how programmers write code? If so, you may be interested in taking part in my study! Non-binding sign-up: forms.gle/iNfBWeYvUuy3oo… So, why should you care about my study? 🧵 (1/13) [RTs appreciated! 😁]

3 24 31 0 5

View Details

Rohan Bavishi @code_monet

4 years ago

@StringChaos @MSFTResearch @Berkeley_EECS Congrats and good luck!

1 0 1 0 0

View Details

Shishir Patil @shishirpatil_

4 years ago

Train BERT on Smartphones 🤩 Announcing POET 📢 Find out how we train memory-hungry SOTA models on smartphones! #ICML2022 Thu 21 Jul 3:45 pm EDT at Room 327 🧵👇 Paper: arxiv.org/abs/2207.07697 Web: poet.cs.berkeley.edu