LLMと脳活動の一致度は30億パラメータ付近で頭打ちとの報告

これまで「AIは大きければ大きいほど人間の脳に近づく」と考えられてきましたが、その常識に修正を迫る報...

AIチームは最優秀メンバー単独に劣る、妥協と同調が原因

Appleやスタンフォード大学などの研究者らによると、AIチームを作っても、チームの中で一番優秀なA...

AI同士の「うわさ話」で利己的なエージェントまで協力する現象

AI同士のコミュニティに「うわさ話」システムを導入したところ、意外にも自己中心的に振る舞うエージェン...

GPT-4 Technical Report

OpenAI

We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs. While less capable than humans in many real-world scenarios, GPT-4 exhibits human-level performance on various professional and academic benchmarks.

Diffusion Models Beat GANs on Image Synthesis

Prafulla Dhariwal, Alex Nichol

We show that diffusion models can achieve image sample quality superior to the current state-of-the-art generative models. We achieve this on unconditional image synthesis by finding a better architecture through a series of ablations.

LoRA: Low-Rank Adaptation of Large Language Models

Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen

We propose Low-Rank Adaptation, or LoRA, which freezes the pre-trained model weights and injects trainable rank decomposition matrices into each layer of the Transformer architecture, greatly reducing the number of trainable parameters for downstream tasks.