▸ We are a cross-lab MIT AI graduate student collective focusing on Algorithms That Learn and Scale.
▸ The group is open to all MIT affiliates, and to participate, contact the organizer. We currently host bi-weekly seminars and will have research socials in the future.
▸ Our coffee ☕ + baked goods 🍰 are currently funded by generous donations from Phillip Isola and Yoon Kim.
▸ We are looking for sponsors to increase our seminar snack capacity, fund research socials, and reimburse speaker travels. Please contact the organizers if interested.
Discussion Schedule
- (TBD) Towards a Machine Capable of Learning Everything Hao Liu (BAIR)
- 04/17 Adapting LLMs with Reinforcement Learning Idan Shenfeld
- 04/03 The Quest to build an (O)pen (L)anguage (Mo)del Luca Soldaini (AI2)
- 03/20 Efficient Deep Learning with Sparsity: Algorithms, Systems, and Applications Zhijian Liu
- 03/12 Building and Deploying Large Language Model Applications Efficiently and Verifiably Ying Sheng (Stanford)
- 03/06 In-Context Language Learning and N-gram Heads Ekin Akyürek
- 02/21 Neurons, norms and number systems Jeremy Bernstein
- 11/28 Sparsity in Transformers Shobhita Sundaram
- 10/18 Large-Scale RNNs in the era of Transformers Bailin Wang
- 11/01 Critical batch-size in deep learning Minyoung Huh (Jacob)
- 10/18 Tensor Program Synthesis Han Guo
- 10/04 Mixture of Experts (MOEs) Jyo Pari
- 09/13 Speculative Decoding Aniruddha Nrusimha