The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions ...

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...

The rise of AI has given us an entirely new vocabulary. Here's a list of the top AI terms you need to learn, in alphabetical order.

Industrial AI deployment traditionally requires onsite ML specialists and custom models per location. Five strategies ...

An interatomic potential is a set of mathematical rules that describes the complex dance of forces between atoms — how atomic ...

Training artificial intelligence models is costly. Researchers estimate that training costs for the largest frontier models ...

B, an open-source AI coding model trained in four days on Nvidia B200 GPUs, publishing its full reinforcement-learning stack ...

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited AI expertise in industrial fields such as factories, medical, and ...

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

Edward Khomotso Nkadimeng receives funding from the National Research Foundation. In most industries, maintenance is a waiting game. Things are fixed when they break. But in the 21st century, an age ...