AutoML for Embedded is available now on Visual Studio Code Marketplace and GitHub.

An international team led by Einstein Professor Cecilia Clementi in the Department of Physics at Freie Universität Berlin ...

This paper proposes Auto-Ensemble (AE) to collect checkpoints of deep learning model and ensemble them automatically by adaptive learning rate scheduling algorithm. The advantage of this method is to ...

Discover Kimi K2, the open-source AI model with one trillion parameters, redefining innovation and accessibility in ...

Embedded AI combines machine learning with edge devices for local, real-time intelligence.Courses range from beginner to advanced, covering TinyM ...

Multi-modal prompt learning is a high-performance and cost-effective learning paradigm, which learns text as well as image prompts to tune pre-trained vision-language (V-L) models like CLIP for ...

PLDT and Smart Communications, Inc. are reaffirming their commitment to inclusive education by supporting the integration of ...

Learn about data quality, model evaluation, model explainability, and model reliability aspects to consider when working with AI and machine learning models.

The open benchmark competition will evaluate the ability of AI-powered virtual cell models to generalize to new cell contexts for therapeutic applications.