Laura O'Mahony @_lauraaisling
Maths + ML PhD Candidate at SFI CRT in foundations of data science in UL 📚🇮🇪 lauraaisling.github.io Cork, Ireland Joined November 2018-
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Most AI systems today follow the same predictable pattern: they're built for specific tasks and optimized for objectives rather than exploration. Meanwhile, humans are an open-ended species—driven by curiosity and constantly questioning the unknown. From inventing new musical…
AI is so smart, why are its internals 'spaghetti'? We spoke with @kenneth0stanley and @akarshkumar0101 (MIT) about their new paper: Questioning Representational Optimism in Deep Learning: The Fractured Entangled Representation Hypothesis. Co-authors: @jeffclune @joelbot3000
📣 New 📝! Under Alex’s great leadership, we identified a unification under QDC measures that exist to bridge synthetic data and open-endedness (OE) in AI, toward generating data for model training, distillation, self-improvement, etc. 📚 🧵What I’ve learned (inspired by QD)👇
📣 New 📝! Under Alex’s great leadership, we identified a unification under QDC measures that exist to bridge synthetic data and open-endedness (OE) in AI, toward generating data for model training, distillation, self-improvement, etc. 📚 🧵What I’ve learned (inspired by QD)👇
It was a pleasure to have been part of this project led by @Dahoas1 With synthetic data being so important in training LLMs these days, this survey on the impacts of QDC of synthetic data for LLM performance is timely.
It was a pleasure to have been part of this project led by @Dahoas1 With synthetic data being so important in training LLMs these days, this survey on the impacts of QDC of synthetic data for LLM performance is timely.
I love this paper as it finally tackles something I’ve been confused about for the last few years since I started working on interpretability!
I love this paper as it finally tackles something I’ve been confused about for the last few years since I started working on interpretability!
This clip from The Journey of Aya documentary features @DeividasMat, @singhshiviii, @luisa_moura_, @muhaksim, and @_lauraaisling. Find the full video at cohere.com/research/aya
Why do varied DNN designs yield equally good models of human vision? Our preprint with @michaelfbonner shows that diverse DNNs represent images with a shared set of latent dimensions, and these shared dimensions turn out to also be the most brain-aligned. arxiv.org/abs/2408.12804
Fascinating paper!
To help explain the weirdness of LLM Tokenization I thought it could be amusing to translate every token to a unique emoji. This is a lot closer to truth - each token is basically its own little hieroglyph and the LLM has to learn (from scratch) what it all means based on…
Is bigger always better? 🐘 The idea that scaling more than any other ingredient has driven progress has become formalized as the “bitter lesson” Is Sutton right? 📜arxiv.org/abs/2407.05694…
Time to study #llama3 405b, but gosh it's big! Please retweet: if you have a great experiment but not enough GPU, here is an opportunity to apply for shared #NDIF research resources. Deadline July 30: ndif.us/405b.html You'll help @ndif_team test, we'll help you run 405b
Time to study #llama3 405b, but gosh it's big! Please retweet: if you have a great experiment but not enough GPU, here is an opportunity to apply for shared #NDIF research resources. Deadline July 30: ndif.us/405b.html You'll help @ndif_team test, we'll help you run 405b
OMG a gift from heaven! I so need this.
OMG a gift from heaven! I so need this.
Gymnastics is the Turing test of video generation models
Perhaps my favorite jailbreak: making a harmful request in the past tense (How to create Y? →How did people create Y?). Works on surprisingly many models :-) including the new Gemma-2. I think it tells us something fundamental about the representations that these models learn.
🔥New work on multilinguality + safety + mech interp! We show that DPO training in only English can detoxify LLM in many other languages. We also give a mechanistic explanation on how cross-lingual safety transfer happens. (1/n 🧵) 📃 Paper: arxiv.org/abs/2406.16235
Aya took 14 months involving 3000 + collaborators and was as much a protest about how research is done as it was a movement to improve the state of multilingual progress. 🎉 Grateful to see it recognized at @aclmeeting and everyone who has supported along the way.
Aya took 14 months involving 3000 + collaborators and was as much a protest about how research is done as it was a movement to improve the state of multilingual progress. 🎉 Grateful to see it recognized at @aclmeeting and everyone who has supported along the way.
🌱 We’re very excited that our work "Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning" was also accepted! Congrats to authors @singhshiviii, @freddie_v4, @mrdanieldsouza, @tellarin, @freakynut, @weiyinko_ml, @krypticmouse, @rv__init__, @DeividasMat,
How can LLMs automatically generate meaningfully diverse, high-quality text responses in creative domains (like generating stories and poems)? Introducing Quality-Diversity through AI Feedback (QDAIF)! 🌐: qdaif.github.io 📜: arxiv.org/abs/2310.13032 👇 Thread (1/11)
Jardux @Jardux0258
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Mátyás Vincze @vinczematyas_
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Anjani K D @kd_anjani
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ARC Prize @arcprize
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Sarah Wiegreffe @sarahwiegreffe
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Eric Elmoznino @EricElmoznino
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Jakob Foerster @j_foerst
21K Followers 974 Following Assoc Prof in ML @UniofOxford @StAnnesCollege @FLAIR_Ox/ RS @MetaAI, 2x dad. Ex: (A)PM @Google, DivStrat @GS, ex intern: @GoogleDeepmind, @GoogleBrain, @OpenAI
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54K Followers 0 Following We are building a world class AI R&D company in Tokyo. We want to develop AI solutions for Japan’s needs, and democratize AI in Japan. https://t.co/1q07mb3TzE
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Conference on Languag... @COLM_conf
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