Reflecting on for.ai...

Cohere · Beginner ·📄 Research Papers Explained ·3y ago

Key Takeaways

The video discusses the origins and experiences of the for.ai research collaboration, a distributed research group founded by Aidan Gomez and Ivan Zhang, and its impact on the members' careers and research experiences. It highlights the importance of community, dedication, and exploration in research and development.

Full Transcript

foreign [Music] [Music] computer science slack group about like I have this idea I want to do a project on some machine translation work and people who are interested are welcome to join and I remember there's like maybe 12 15 of us came up in the first meeting and he just gave us like a small task and he put us through this like Hunger Games trial where we all had to complete this like tensorflow tutorial at the time I never even wrote a line of like tensorflow in my life so um I just remember I actually stayed up like all night doing the challenge not because I was worried about submitting it on time but it's more just like out of pure curiosity and interest and I found myself like yeah being pretty surprised that I would be this interested in something I barely knew about um so I think that was like very inspiring after he filtered that out we met up in this actual room in this was me sneaking a picture of that meeting I feel like I would want to remember this one day yeah that lack of the first research research project I've ever done and there was an article written by the university about this project um there's a there's a picture of us let me show you yeah so when we our first paper we like I I almost didn't even believe it but like our first paper it was accepted into iclr and Not only was it accepted as a as a poster it wasn't like it was like the top 20 best papers at the conference or something it was like oh my God I couldn't believe it like we were just a bunch of kids like a bunch of undergrads you know doing this on the side like it didn't feel like we belonged you know like when I was at LCL I was like had like such an events imposter syndrome you know I was in this poster Hall with all these like crazy PhD people I'm supposed to like answer questions about this paper like are you kidding me like yeah I think I think after that conference it was like uh it's like damn like this is like a real field you know like not like a we can actually do this and then after that project we decide to you know continue this work and then maybe you can invite more people especially people who are in the undergrad or don't have much um research experience to work together and that's when we created for AI I think earliest memories was I think it was me Sid Aiden and Ivan um we just sit in this little wework room and work on like whatever research project that we had at the time at the time tpus were also relatively new so I remember all the days we spent debugging those those horrible things but yeah I just really enjoyed those those like days when I was an undergrad and I was just trying to learn how to do research it was my intro into research I never had any research experience in the past I never thought about research to begin with so yeah everything was very new for me it was very fresh and I quite enjoyed it I mean so much so that switched my you know entire career path and now I'm doing my PhD and so on so hopefully I don't require any future yeah so far so good and it got me started with ML research as well which is something I continue to do every day um and yeah obviously I ended up making some of the greatest friends of my life through poor AI I don't think I've seen anything similar to what we created back then yeah I think it's just very welcoming I guess less intimidating to get into the field whenever you know is in the same boat as you it just felt like you belonged somewhere and people care about your progress and your learning um yeah I don't know that's that's just something I really liked I think it was just like irrational dedication to something because like like I think we were all weirdly motivated to work on this project but I like it's not like we were getting paid like most people already have full-time jobs and then they're like doing this on top of it um and like pretty dedicated as well so I think that that just like was really motivating for me to to do the same and to stay committed to something and mostly to stay committed to learning and developing more skills because you could never have enough as a researcher I think the best advice I've ever given to anyone is just like invest in your like workbench you know like make sure you can you can actually make mistakes really easily and then like figure out what what went wrong and then like repeat the experiment again and again again um so I'd say like invest a lot in your tooling because ultimately that that decides how fast you're learning and how fast you're getting better at this field yeah I would say just like explore a lot I think it's very easy to optimize for one thing and and have some goal and be like if I'm gonna ignore everything and only you know work on this but I think having breaths of experience and like not being afraid to fail and to struggle I think it's like really important especially as a researcher because I think most things don't work on your first try or at all sometimes I think for many of us in the original crew we got to where we are at the research industry mostly because of either project or connection we made in this group so one of my advice for the existing member of newcomers for this in this group in particular is to utilize the connection we have within this group I think people in general are pretty low ego um I think that Stouts a lot because like it's it's kind of a privilege I think to have opportunities um especially if you came from like a really good school or like had a lot of resources at your disposal I think many of four ai's members might not have come from like you know American schools mostly International and I think having a lot of people from different backgrounds like all very curious about one thing together is what kind of drove the community I definitely want to scale this access the opportunity that I had the fortune of being able to take advantage of right like you know I I dropped out of school I've never been like academically inclined really like my parents don't work in Academia so there was like really no way for me to break in right and so uh I felt like I feel like that is such an important opportunity to have for people who just want to work really hard and you know make something of themselves in this field um so I I'm hoping to provide like sort of pay it forward in a sense yeah I'm like really grateful that I happened to come across for you guys [Music]

Original Description

Did you know? Our non-profit research lab, Cohere For AI, is built on the foundation of "for.ai," a distributed research collaboration begun in part by two of Cohere's co-founders: Aidan Gomez and Ivan Zhang. Learn about it from some of for.ai's original members: Bryan Li, Winnie Xu, and Ivan Zhang.
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Playlist

Uploads from Cohere · Cohere · 42 of 60

1 Andreas Madsen on Independent Research and Interpretability
Andreas Madsen on Independent Research and Interpretability
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2 Plex: Towards Reliability using Pretrained Large Model Extensions
Plex: Towards Reliability using Pretrained Large Model Extensions
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3 Independent Research Panel Discussion
Independent Research Panel Discussion
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4 The Future of ML Ops: Open Challenges and Opportunities
The Future of ML Ops: Open Challenges and Opportunities
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5 C4AI Special - Grad School Applications
C4AI Special - Grad School Applications
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6 Cohere For AI Fireside Chat: Samy Bengio
Cohere For AI Fireside Chat: Samy Bengio
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7 Cohere For AI - Scholars Program Information Session
Cohere For AI - Scholars Program Information Session
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8 Modular and Composable Transfer Learning with Jonas Pfeiffer
Modular and Composable Transfer Learning with Jonas Pfeiffer
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9 Jay Alammar Presents Large Language Models for Real World Applications
Jay Alammar Presents Large Language Models for Real World Applications
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10 Catherine Olsson - Mechanistic Interpretability: Getting Started
Catherine Olsson - Mechanistic Interpretability: Getting Started
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11 How To Prompt Engineer a Tech Interview App | TOHacks 2022 Winners
How To Prompt Engineer a Tech Interview App | TOHacks 2022 Winners
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12 C4AI Sparks: Samy Bengio
C4AI Sparks: Samy Bengio
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13 BERTopic for Topic Modeling - Maarten Grootendorst - Talking Language AI Ep#1
BERTopic for Topic Modeling - Maarten Grootendorst - Talking Language AI Ep#1
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14 Exploring News Headlines With Text Clustering | Jay Alammar
Exploring News Headlines With Text Clustering | Jay Alammar
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15 Scale TransformX | Fireside Chat: Aidan Gomez and Alexandr Wang
Scale TransformX | Fireside Chat: Aidan Gomez and Alexandr Wang
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16 Making Large Language Models Accessible | Scale AI Fireside chat with Bill MacCartney
Making Large Language Models Accessible | Scale AI Fireside chat with Bill MacCartney
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17 Intro to KeyBERT - BERTopic for Topic Modeling
Intro to KeyBERT - BERTopic for Topic Modeling
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18 Intro to PolyFuzz - BERTopic for Topic Modeling
Intro to PolyFuzz - BERTopic for Topic Modeling
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19 API Design Philosophy - BERTopic for Topic Modeling
API Design Philosophy - BERTopic for Topic Modeling
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20 Code demo of BERTopic - BERTopic for Topic Modeling
Code demo of BERTopic - BERTopic for Topic Modeling
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21 Short texts vs long texts in BERTopic- BERTopic for Topic Modeling
Short texts vs long texts in BERTopic- BERTopic for Topic Modeling
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22 How People can help BERTopic - BERTopic for Topic Modeling
How People can help BERTopic - BERTopic for Topic Modeling
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23 Cohere For AI: Training Sensorimotor Agency in Cellular Automata with Bert Chan
Cohere For AI: Training Sensorimotor Agency in Cellular Automata with Bert Chan
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24 Cohere API Community Demos | October 2022
Cohere API Community Demos | October 2022
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25 Perfect Prompt Demo By Arjun Patel
Perfect Prompt Demo By Arjun Patel
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26 Project Idea Generator Demo By Tobechukwu Okamkpa
Project Idea Generator Demo By Tobechukwu Okamkpa
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27 SuperTransformer Demo By Amir Nagri and Team Megatron
SuperTransformer Demo By Amir Nagri and Team Megatron
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28 Cohere For AI Fireside Chat: Pablo Samuel Castro
Cohere For AI Fireside Chat: Pablo Samuel Castro
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29 How Startups Can Use NLP to Build a Competitive Moat
How Startups Can Use NLP to Build a Competitive Moat
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30 Build Chatbots Faster with Large Language Models
Build Chatbots Faster with Large Language Models
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31 Tools to Improve Training Data - Vincent Warmerdam - Talking Language AI Ep#2
Tools to Improve Training Data - Vincent Warmerdam - Talking Language AI Ep#2
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32 Utku Evci - Sparsity and Beyond Static Network Architectures
Utku Evci - Sparsity and Beyond Static Network Architectures
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33 Adding human intelligence to ML models with human-learn #shorts #machinelearning #nlp
Adding human intelligence to ML models with human-learn #shorts #machinelearning #nlp
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34 Iterating on your data with doubtlab - Tools to Improve Training Data
Iterating on your data with doubtlab - Tools to Improve Training Data
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35 Adding Human Intelligence to ML models with Human learn - Tools to Improve Training Data
Adding Human Intelligence to ML models with Human learn - Tools to Improve Training Data
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36 Scikt Learn embeddings helpers with Embetter - Tools to Improve Training Data
Scikt Learn embeddings helpers with Embetter - Tools to Improve Training Data
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37 Building Cohere API Demo App With Streamlit | Adrien Morisot
Building Cohere API Demo App With Streamlit | Adrien Morisot
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38 Rosanne Liu - career creation for non-standard candidates
Rosanne Liu - career creation for non-standard candidates
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39 Giving computers many human languages with Cohere's multilingual embeddings
Giving computers many human languages with Cohere's multilingual embeddings
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40 Learning by Distilling Context with Charlie Snell
Learning by Distilling Context with Charlie Snell
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41 Sentence Transformers and Embedding Evaluation - Nils Reimers - Talking Language AI Ep#3
Sentence Transformers and Embedding Evaluation - Nils Reimers - Talking Language AI Ep#3
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Reflecting on for.ai...
Reflecting on for.ai...
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43 Create a Custom Language Model with Surge AI and Cohere
Create a Custom Language Model with Surge AI and Cohere
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44 Cohere API Community Demos | November 2022
Cohere API Community Demos | November 2022
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45 Cohere API Community Demos | December 2022
Cohere API Community Demos | December 2022
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46 Cohere For AI Presents: Colin Raffel
Cohere For AI Presents: Colin Raffel
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47 Lucas Beyer - FlexiViT: One Model for All Patch Sizes
Lucas Beyer - FlexiViT: One Model for All Patch Sizes
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48 What is Neural Search? Nils Reimers - Sentence Transformers and Embedding Evaluation
What is Neural Search? Nils Reimers - Sentence Transformers and Embedding Evaluation
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49 Evaluating Information Retrieval with BEIR
Evaluating Information Retrieval with BEIR
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50 Evaluating Embeddings with MTEB Massive text embeddings benchmark - Nils Reimers
Evaluating Embeddings with MTEB Massive text embeddings benchmark - Nils Reimers
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51 High quality text classification with few training examples with SetFit
High quality text classification with few training examples with SetFit
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52 Multilingual and cross lingual embeddings - Nils Reimers
Multilingual and cross lingual embeddings - Nils Reimers
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53 Developing open-source software: lessons, benefits, and challenges - Nils Reimers
Developing open-source software: lessons, benefits, and challenges - Nils Reimers
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54 Ask Me Anything with Ed Grefenstette, Head of Machine Learning at Cohere
Ask Me Anything with Ed Grefenstette, Head of Machine Learning at Cohere
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55 HyperWrite Powers Its Generative AI Service with Cohere
HyperWrite Powers Its Generative AI Service with Cohere
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56 EMNLP 2022 Conference Special Edition - Talking Language AI #4
EMNLP 2022 Conference Special Edition - Talking Language AI #4
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57 Cohere API Community Demos | January 2023
Cohere API Community Demos | January 2023
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58 C4AI Sparks: Rosanne Liu on Career Creation for Non-Standard Candidates
C4AI Sparks: Rosanne Liu on Career Creation for Non-Standard Candidates
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59 Michael Tschannen -  Image-and-Language Understanding from Pixels Only
Michael Tschannen - Image-and-Language Understanding from Pixels Only
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60 How to Add AI to your App
How to Add AI to your App
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The video discusses the for.ai research collaboration and its impact on the members' careers and research experiences. It highlights the importance of community, dedication, and exploration in research and development. Viewers can learn about the benefits of research collaboration, community building, and dedication to research.

Key Takeaways
  1. Join a research collaboration or community
  2. Participate in research projects and experiments
  3. Read and understand research papers
  4. Apply research skills to real-world problems
  5. Explore different areas of research and development
💡 The importance of community, dedication, and exploration in research and development cannot be overstated. Research collaboration and community building can provide valuable opportunities for learning, growth, and career development.

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