To build a chatbot, you can take a machine learning approach or a linguistic rules-based approach. Here are the pros and cons of each.

The rise of FML allows systems to become progressively more intelligent and autonomous by using on-device data and sharing only encrypted model updates.

In this talk, we will introduce a state-of-the-art scientific machine learning paradigm - differentiable physics (DiffPhys). DiffPhys can be considered a system identification paradigm that can be ...

A recent study introduce a novel paradigm combining ChatGPT with machine learning (ML) to significantly ease the application of ML in environmental science.  ...

Federated Learning (FL) has gained significant attention as a novel distributed machine learning paradigm that enables collaborative model training while preserving data privacy.

AI/ML systems intersect with machine learning theory and software engineering. The system should scale to large data sets, train models reliably and cost-effectively, and serve the model ...

More efficient machine learning could upend the AI paradigm Smaller algorithms that don’t need mountains of data to train are coming.

Here’s how to build a PC for AI and machine learning workloads, so you can keep your data secure and private, and ensure the AI is always ready and waiting for you.

AI luminary Andrew Ng wants AI practitioners to shift their focus from model development to data quality.