AI and machine learning are reshaping how brands interact with their audiences and redefining campaign management, customer engagement and data-driven decision making.

Most approaches to machine learning-based inverse design require large amounts of simulation or experimental data, which are costly and time-consuming, especially for microscale and nonlinear systems.

In a recent advance, a multi-disciplinary team of researchers developed a machine learning framework that adapts to changes ...

Researchers have developed a new machine learning algorithm that excels at ... However, interpreting spectral data can be difficult and time consuming, especially when differences between samples ...

Data science platform Kaggle is hosting a Wikipedia dataset that’s specifically optimized for machine learning applications. Data science platform Kaggle is hosting a Wikipedia dataset that ...

Mixture-of-Experts (MoE) models are revolutionizing the way we scale AI. By activating only a subset of a model’s components ...

Finally, he threads ethical guardrails into machine-learning workflows. Model cards declare data provenance, training drift metrics, and fairness audits. Deployment pipelines block models lacking ...

Artificial Intelligence (AI) and Machine Learning (ML ... AI into UX design means understanding how personalization works. At its core, AI uses data to create experiences that adjust to user ...