Super Micro Shares Fall on Disappointing Profit Forecast

Super Micro's Q1 revenue fell 15% year-over-year to $5 billion, missing estimates of $6.09 billion. The company also forecasted a Q2 profit below expectations, leading to a more than 9% drop in its stock after hours.

Recent advancements in LLM Multi-Agent Systems are making it easier to manage numerous tools and sub-agents effectively. The introduction of Tool-to-Agent Retrieval aims to enhance agent selection by providing a clearer understanding of tool functionalities, leading to better orchestration and improved performance.

Tool Zero introduces an innovative approach to training language models using pure reinforcement learning from scratch. This method aims to enhance the capabilities of language models for complex tasks, overcoming the limitations of traditional supervised fine-tuning that often struggles with unfamiliar scenarios.

VidEmo introduces a new approach to understanding emotions in videos, leveraging advancements in video large language models. This innovative method aims to tackle the complexities of emotional analysis, addressing the dynamic nature of emotions and their dependence on various cues.

The iFlyBot-VLA is an innovative Vision-Language-Action model that enhances robotic manipulation through a unique training framework. It features a dual-level action representation and a mixed training strategy, making it a significant advancement in the field.

A recent study explores the use of federated learning in cardiac CT imaging, addressing challenges with partially labeled datasets. By leveraging decentralized data while maintaining privacy, the research aims to enhance transformer architectures, making them more effective in scenarios with limited expert annotations.

The MVAFormer introduces an innovative approach to multi-view action recognition, leveraging RGB data and transformer technology to enhance performance. By effectively combining multiple camera views, it addresses challenges like occlusion from obstacles and crowds, paving the way for more accurate human action recognition.