Rohan Bavishi @code_monet
Applied Scientist @ Amazon AGI. Previously @AdeptAILabs. Ph.D. @Berkeley_EECS. Undergrad @IITKanpur. Trying to automate boring tasks. I like art too. rbavishi.github.io Indianapolis, IN Joined April 2010-
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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.
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.
We’re open-sourcing a multimodal model: Fuyu-8B! Building useful AI agents requires fast foundation models that can see the visual world. Fuyu-8B performs well at standard image understanding benchmarks, but it also can do a bunch of new stuff (below) adept.ai/blog/fuyu-8b
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
🕵🏽♂️
After much hard work, we’re excited about a series of releases coming up this fall! We’re starting with a small appetizer: we’re open-sourcing Persimmon-8B, the most capable fully permissively-licensed language model with <10B parameters. Details here: adept.ai/blog/persimmon…
We've raised $350M in new funding as part of our Series B led by @generalcatalyst and co-led by @sparkcapital adept.ai/blog/series-b (1/4)
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
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 https://t.co/KI6XRLGlW2
This might have gotten lost, but this vid demonstrates voice input! Complaints to me if you don’t like the voice in question :)
This might have gotten lost, but this vid demonstrates voice input! Complaints to me if you don’t like the voice in question :)
Come see what our team is building!
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! 😁]
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
We made a fun video of some of the earliest things our system can do! If you want to help us build useful general intelligence, please reach out -- we are hiring. vimeo.com/705939460/af6e…
I love statically-typed functional programming (STFP)! OCaml! Elm! Haskell! F#! You name it! But… why haven't there been studies about how we actually *write code* in these languages? Here are my efforts to change that! (an ad for my OOPSLA '21 paper with @sarahchasins 😄) 🧵
So excited that our work "Gauss: Program Synthesis by Reasoning over Graphs", led by @code_monet, will be making its appearance at OOPSLA 2021 next week! Full paper: rbavishi.github.io/docs/oopsla202… 1/5
I have openings for 2-3 postdocs to work on: 1. Whitebox fuzzing 2. Explore approaches to creating scientific software targeting distributed, heterogeneous, HPC platforms. 3. Fast data-engineering using program synthesis, AI, and semantic code search. Email me if interested.
Our second paper, "VizSmith: Automated Visualization Synthesis by Mining Data-Science Notebooks", collaboration with @code_monet , @ShadajL , @koushik77 and Hiroaki Yoshida, also accepted to @ASE_conf !!

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