PolymathicAI
@PolymathicAI
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The Polymathic AI Collaboration. Shared account.
Joined September 2023
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Announcing:
*The Polymathic AI Initiative*
We are researching a new class of foundation models for scientific *data*, developing models that share scientific concepts across disciplines.
Site:
News:
Thread: 👇
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We're thrilled to be at
@NeurIPSConf
for the first time since we formed a few months ago!
If you're there, we'd love to chat with you about our team and AI/ML research!
Reach out and be sure to check out our accepted papers👇
#NeurIPS2023
#AI4Science
and we are HIRING 🥳
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Very excited to share that our team's "Multiple Physics Pre-training" paper won the Best Paper Award at
@AI_for_Science
workshop at NeurIPS this year!
Congrats to the team and to
@mikemccabe210
,
@BrunoRegaldo
@liamhparker
and
@oharub
for leading the effort! 🥳
Congratulations to the best paper award winners at NeurIPS AI for Science 2023 workshop!
@mikemccabe210
@kchonyc
@cosmo_shirley
Andres M Bran
@SamCox822
@andrewwhite01
@pschwllr
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Are you a student looking for an internship this summer or fall?
Want to build foundation models for science in NYC?
Join us at
@PolymathicAI
at
@FlatironInst
!
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There's much preliminary research required to build a foundation model for scientific data. This week are releasing three papers on the fundamentals of this space:
(1) xVal: continuous tokenization for numbers
(2) Multiple Physics Pre-training
(3) AstroCLIP
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AstroCLIP thread:
8/8
Excited to share some of our recent work at
@polymathicAI
! With AstroCLIP we are bringing multimodal contrastive pretraining to astrophysics!
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Our aim with the Polymathic AI initiative is to accelerate the development of versatile foundation models tailored for machine learning tasks in *science*. A breakthrough in this field would mark a significant shift analogous to the one seen in the domains of vision and NLP.
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xVal thread:
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1/ Did you know LLMs like ChatGPT struggle with number manipulation and data analysis? They make up answers and fail to generalize.
Today I am excited to share xVal, a continuous and efficient number encoding scheme with better generalization performance.
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Our team, led by
@cosmo_shirley
, comprises both pure machine learning researchers and domain scientists, covering a wide array of disciplines:
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Check out our oral presentation of Multiple Physics Pretraining (MPP) at
#AI4Science
workshop!
MPP is a group of techniques for pretraining on a diverse set of time-dependent physics to learn models that can be fine-tuned for multiple problems.
Very excited to present Multiple Physics Pretraining!
MPP is a group of techniques for pretraining on a diverse set of time-dependent physics to learn models that can be fine-tuned for multiple problems.
Blog:
Paper:
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We are hiring a software engineer or software-focused researcher to embark with us on this journey of changing how science is done with large foundation models!
Reach out if you are excited!
A large number of our team is at NOLA this week!
Find us :
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MPP thread:
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Very excited to present Multiple Physics Pretraining!
MPP is a group of techniques for pretraining on a diverse set of time-dependent physics to learn models that can be fine-tuned for multiple problems.
Blog:
Paper:
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We are graciously supported with funding from
@SimonsFdn
@FlatironInst
.
Additional participating institutions include
@nyuniversity
,
@Cambridge_Uni
,
@SchmidtFutures
,
@Princeton
, and
@BerkeleyLab
.
4/n
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Polymathic AI is guided by a scientific advisory group of world-leading experts:
@ylecun
@hardmaru
Leslie Greengard
@DavidSpergel
@laurezanna
Colm-cille Caulfield
@OlgaTroyanskaya
and Stephane Mallat.
3/n
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Finally, check out our work on bringing multi-modal astronomical data into a common embedding at
#AI4Science
workshop!
Blog:
Excited to share some of our recent work at
@polymathicAI
! With AstroCLIP we are bringing multimodal contrastive pretraining to astrophysics!
1
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And got problems with numerics with LLMs?
Check out our xVal presentation at
#AI4Science
Workshop! where we discuss how to get efficient numeric encoding that generalizes well!
Blog:
1/ Did you know LLMs like ChatGPT struggle with number manipulation and data analysis? They make up answers and fail to generalize.
Today I am excited to share xVal, a continuous and efficient number encoding scheme with better generalization performance.
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234
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