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@haizelabs
Haize Labs haizelabs
build ai systems you can trust.

United States of America

@DS4SD
IBM Deep Search DS4SD
Developer tools for IBM Deep Search

Switzerland

@stanford-oval
Stanford Open Virtual Assistant Lab stanford-oval
Research projects in the Stanford Open Virtual Assistant Lab

Stanford, CA

@astral-sh
Astral astral-sh
High-performance developer tools for the Python ecosystem.

United States of America

@romanlutz
Roman Lutz romanlutz
Responsible AI Engineer | AI Red Teaming | Open Source

Microsoft Greater Seattle Area, WA, USA

@rdheekonda
Raja Sekhar Rao Dheekonda rdheekonda
Experienced software engineer specializing in building security of AI tools and services, as well as applying AI to security data.

Microsoft Bellevue

@FlagOpen
FlagOpen
FlagOpen, an open-source initiative by the Beijing Academy of Artificial Intelligence (BAAI), aims to foster an open-source ecosystem for AI technologies.
@NVIDIA
NVIDIA Corporation NVIDIA

2788 San Tomas Expressway, Santa Clara, CA, 95051

@mixedbread-ai
Mixedbread mixedbread-ai
AI Research & Development
@hongchaodeng
Hongchao Deng hongchaodeng
Engineer - Ray.io - Kubernetes

Anyscale San Francisco, CA

@deepset-ai
deepset deepset-ai
Building enterprise search systems powered by latest NLP & open-source.

Berlin, Germany

@TrentBrick
Trenton Bricken TrentBrick
Member of Technical Staff at Anthropic

San Francisco

@cohere-ai
Cohere cohere-ai
Cohere builds secure, scalable, and private enterprise-grade AI solutions for real-world business problems.

Canada

@taskswithcode
Tasks With Code taskswithcode
ML researchers & practitioners are the true catalysts of AI progress. Consider investing in researchers/practitioners who open-source paper implementations
@jina-ai
Jina AI jina-ai
Your Search Foundation, Supercharged!

Germany

@lucidrains
Phil Wang lucidrains
Working with Attention. It's all we need

San Francisco

@NielsRogge
NielsRogge
ML @huggingface. Interested in deep learning, NLP. Contributed 40+ models to HuggingFace Transformers

HuggingFace Belgium

@rafaelvalle
Rafael Valle rafaelvalle
My research focuses on machine listening and improvisation. During my PhD at Berkeley I was advised mainly by Sanjit Seshia and Edmund Campion.