Machine Learning

Our work from AAAI 2023 is now on arxiv (very overdue)! The idea is really simple -- predicting language instructions during training improves generalization at test-time, particularly for combinatorial tasks. https://t.co/um35rn7vEv

— Joey Hejna (@JoeyHejna) June 27, 2023

Lambda Co-founder and CEO @stephenbalaban sat down with @pabbeel on the latest @therobotbrains episode to talk about the current state of the GPU cloud market and our journey to building the largest and most cost-effective GPU cloud in the world: https://t.co/KeKCTpX1iV

— Lambda (@LambdaAPI) June 23, 2023

📢Our work X-RiSAWOZ: High-Quality End-to-End Multilingual Dialogue Datasets and Few-shot Agents accepted at @aclmeeting 🎉 Collaboration b/w @Stanford @TJU1895 @i_hanyang @UnivParisSaclay @indiamsr @karya_inc @iiit_hyderabad.
Paper: https://t.co/MkDJasE3aA
Findings 🧵👇🏽#NLProc pic.twitter.com/0kr3qylA94

— Ponnurangam Kumaraguru “PK” (@ponguru) June 22, 2023

MPT-30B is here! Same MPT architecture, 30B parameters, > 1T tokens, 8k context window, trained on H100s, great perf (esp on coding), single-GPU inference, commercially usable, and massively upgraded instruct and chat datasets. Take it for a spin! https://t.co/nZZ9RNuld1

— Jonathan Frankle (@jefrankle) June 22, 2023

That's what economists have kept telling us. https://t.co/WCaBF3G7Ba

— Yann LeCun (@ylecun) June 23, 2023