Texas A&M AgriLife scientists used data modeling to uncover new insights into how cattle fever ticks survive and spread ...

You can train your own image models for deployment on an ESP32-S3, and it's really easy.

Some cars invite you in with chrome and comfort. The Model T invites you into a time machine, hands you three pedals that mean the wrong things, and politely asks you to learn 1910s. Then it coughs, ...

Years ago, before the rise of the gig economy, people developed their careers over time, often more slowly than desired. Folks who became DBAs, Data Modelers, or Data Architects had a rule-following ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

The Opensource DeepSeek R1 model and the distilled local versions are shaking up the AI community. The Deepseek models are the best performing open source models and are highly useful as agents and ...

Abstract: Accurate modeling of Lithium-ion battery is essential in the development and testing of state estimation and lifetime prediction algorithms. The desired features of the model include ...

The Covid-19 pandemic reminded us that everyday life is full of interdependencies. The data models and logic for tracking the progress of the pandemic, understanding its spread in the population, ...

The algorithms behind generative AI tools like DallE, when combined with physics-based data, can be used to develop better ways to model the Earth’s climate. Computer scientists in Seattle and San ...