MLC is a community for the genuinely curious people who are interested in getting better at doing machine learning research, for whatever reason. To that end, the community building aspect of MLC is creating a place to 1) develop and train relevant skills for maturing into a researcher, 2) find kindred spirits, friends and collaborators along the way, 3) produce serious research, and 4) give back to society.

To serve each individual's different communication style, comfortability, time commitment and social need, we have constructed a few types of communities.

Open Collab Community

Making AI research more inviting, inclusive, and accessible is a difficult task, but the movement to do so is close to many researchers' hearts. Progress toward democratizing AI research has been driven by open-access resources: by MOOCs, by accessible code and papers, and by blogs, videos and podcasts making research more understandable.

However, open, online resources are only part of the equation. Growth as a researcher requires not only learning by consuming accessible information, but hands-on practice whiteboarding, coding, plotting, debugging, and writing. One's growth along these dimensions is often critically enabled by working with and directly learning from collaborators, whether mentors or peers. We learn the most important lessons from each other. And a lot of times success has less to do with our own talent than being with the right people at the right time.

The Open Collab community is a marriage between community building and research training, where we bring the open, diverse, and nurturing culture into the traditionally rigid academic training.

I'm in. What do I do?

Here's how to participate. It's pretty informal.

  1. Join the Open Collab Discord to chat about research or find collaborators. First step: intro yourself in the #introductions channel!
  2. Join the reading group if you like. Reading group papers are discussed in the #dlct channel on Discord each week.
  3. Most announcements are posted on the @ml_collective Twitter, posted in the #general channel, and sent to the reading group email list.
  4. Make an RFP contribution to help aspiring researchers get started!
  5. Attend one of the upcoming events to hang out live, chat about research, and maybe show people what you're working on!

The Lab

The Lab is the part of MLC that's most similar to a traditional academic or industrial research lab. Members pursue research directions individually or in small teams, and we hold regular group meetings for people to present research updates. We all hang out, stare at plots, complain about axes and baselines, and ideate on next steps. Due to COVID and our distributed nature, our meetings are held over Zoom, which sadly means that everyone has to bring their own group meeting snacks.

To keep research focused and active, we ask that prospective researchers interested in joining do so with a specific research project in mind and with a commitment to presenting progress updates on it. If that sounds like you, drop us an email at hello AT mlcollective DOT org to schedule your entry presentation! If you have not yet converged on a research direction or project, or you are unsure about whether your project idea is valid, you can ask for feedback at the Open Collab discord or try pitching it at our research jam.

Experienced researchers looking to dedicate time to mentor projects and give advice to starters should consider joining the lab, with a light commitment of joining our regular research meetings where research updates are presented.

Ready to work on science with these folks?

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Rosanne Liu

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Josh Roy

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Ankit Jain

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Robin Tibor Schirrmeister

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Behnam Neyshabur

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Gregory Clark

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Brian Cheung

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Zach Nussbaum

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Daniel D'souza

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Yaroslav Bulatov

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Marcos Pereira

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Chirag Agarwal

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Chloe Hsu

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Jonathan Frankle

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Sebastian Ruder

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Stephanie Sher

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Sara Hooker

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Jane Hung

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Andrea Madotto

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Thomas Miconi

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Eric Frank

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Yariv Sadan

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Sam Greydanus

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Rui Wang

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Janice Lan

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Hattie Zhou

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Xinyu Hu

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Piero Molino

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Niel Teng Hu

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Mitchell Wortsman

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Jason Yosinski