Please encourage your students to apply, if they are interested in pursuing a PhD at NTU. This is a great opportunity to meet their future advisors and establish connections. We especially welcome students from "non-traditional countries", which historically did not send a lot of students to NTU.
26.01.2025 12:49 — 👍 0 🔁 0 💬 0 📌 0
Given DeepSeek R1, the next major obstacle for AI is soft reasoning, or reasoning that requires common sense and does not have definite right or wrong answers. The RL reward becomes ill defined. One needs either RLHF or curated MCQs.
26.01.2025 08:16 — 👍 0 🔁 0 💬 0 📌 0
Today I saw this formula. It's not a student's work.
21.01.2025 13:44 — 👍 0 🔁 0 💬 0 📌 0
There is some hype about how using solved problems to train the next model (i.e., the data flywheel) will directly lead to AGI or superhuman AI.
While I don't believe the hype, here is a paper that may help you implement that data flywheel idea: arxiv.org/abs/2407.09985
20.01.2025 17:14 — 👍 1 🔁 0 💬 0 📌 0
If you think of reasoning as an algorithm, it would require some storage space, but that doesn't mean the algorithm is not important. Space is one way to characterize an algorithm but it's only one aspect. For example, algorithms can trade time for space, and vice versa.
17.11.2024 03:44 — 👍 0 🔁 0 💬 0 📌 0
Security and Privacy of Machine Learning at UofT, Vector Institute, and Google 🇨🇦🇫🇷🇪🇺 Co-Director of Canadian AI Safety Institute (CAISI) Research Program at CIFAR. Opinions mine
English PhD turned Machine Learning Researcher. I medicate my imposter syndrome with cold brews.
Current:
Foundation Models @ Apple
Prev:
LLMs/World Models @ Riot Games
RecSys @ Apple
Seattle 🏳️🌈
PhD student @ CMU LTI. efficiency/data in NLP/ML
PhD student @ CMU LTI
https://jiminmun.github.io/
CS PhD student at UT Austin in #NLP
Interested in language, reasoning, semantics and cognitive science. One day we'll have more efficient, interpretable and robust models!
Other interests: math, philosophy, cinema
https://www.juandiego-rodriguez.com/
PhD @ltiatcmu.bsky.social
previously @eleutherai.bsky.social
🌐 lintang.sutawika.com
PhD student @ CMU LTI. working on text generation + long context
https://www.cs.cmu.edu/~abertsch/
Working on #NLProc for social good.
Currently at LTI at CMU. 🏳🌈
Associate Professor of Machine Learning, University of Oxford;
OATML Group Leader;
Director of Research at the UK government's AI Safety Institute (formerly UK Taskforce on Frontier AI)
RS DeepMind. Works on Unsupervised Environment Design, Problem Specification, Game/Decision Theory, RL, AIS. prev CHAI_Berkeley
Assistant Professor of Statistics & Data Science at UChicago
Topics: data-intensive social science, Bayesian statistics, causal inference, probabilistic ML
Proud “golden retriever” 🦮
Associate Professor, CMU. Researcher, Google. Evaluation and design of information retrieval and recommendation systems, including their societal impacts.
Senior Lecturer at @CseHuji. #NLPROC
schwartz-lab-huji.github.io
NLP Researcher | CS PhD Candidate @ Technion
DeepMind Professor of AI @Oxford
Scientific Director @Aithyra
Chief Scientist @VantAI
ML Lead @ProjectCETI
geometric deep learning, graph neural networks, generative models, molecular design, proteins, bio AI, 🐎 🎶
Advocate for tech that makes humans better | Spatial Computing, Holodeck, and AI Futurist | Ex-Microsoft, Rackspace | Co-author, "The Infinite Retina."
Comp. sci. prof. @ American University, Washington DC. AI & games researcher with miscellaneous other interests. https://www.kmjn.org/
The 2025 Conference on Language Modeling will take place at the Palais des Congrès in Montreal, Canada from October 7-10, 2025
International Conference on Learning Representations https://iclr.cc/
Postdoc at UW NLP 🏔️. #NLProc, computational social science, cultural analytics, responsible AI. she/her. Previously at Berkeley, Ai2, MSR, Stanford. Incoming assistant prof at Wisconsin CS. lucy3.github.io/prospective-students.html
