Unlocking Transformers’ Reasoning Abilities, FastGen Enhances LLM Efficiency

Discover how the 'chain of thought' approach makes transformers smarter and how FastGen cuts GPU memory costs without compromising LLM quality. Also, learn about Lory, a fully-differentiable MoE model for language model pre-training, and the release of the largest supervised fine-tuning open-sourced dataset by Alignment Lab AI.

Sources:
https://www.marktechpost.com/2024/05/12/how-chain-of-thought-makes-transformers-smarter/
https://www.marktechpost.com/2024/05/12/fastgen-cutting-gpu-memory-costs-without-compromising-on-llm-quality/
https://www.marktechpost.com/2024/05/12/researchers-from-princeton-and-meta-ai-introduce-lory-a-fully-differentiable-moe-model-designed-for-autoregressive-language-model-pre-training/
https://www.marktechpost.com/2024/05/12/alignment-lab-ai-releases-buzz-dataset-the-largest-supervised-fine-tuning-open-sourced-dataset/

Outline:
(00:00:00) Introduction
(00:00:45) How ‘Chain of Thought’ Makes Transformers Smarter
(00:03:23) FastGen: Cutting GPU Memory Costs Without Compromising on LLM Quality
(00:06:51) Researchers from Princeton and Meta AI Introduce ‘Lory’: A Fully-Differentiable MoE Model Designed for Autoregressive Language Model Pre-Training
(00:09:27) Alignment Lab AI Releases ‘Buzz Dataset’: The Largest Supervised Fine-Tuning Open-Sourced Dataset