This article explores the significance of machine learning in generative AI.

This article discusses the combination of quantum computing properties with a classic Machine Learning technique called Support Vector Machine (SVM). The author explores the concept of SVM, the use of kernels for classification, and introduces quantum kernels. An example using Pennylane and scikit-learn’s SVC is provided, showing that the performance of a quantum kernel didn’t…

The KDD conference in Long Beach, CA showcased various topics, but the highlights were Large Language Models (LLMs) and Graph Learning. The LLM Revolution keynote by Ed Chi of Google discussed the ways LLMs are bridging the gap between human intelligence and machine learning. Other presentations focused on techniques and challenges in LLM development, including…

Researchers from Carnegie Mellon University, Shanghai Jiao Tong University, and Honda Research Institute have developed the Open Whisper-Style Speech Model (OWSM), an open-source solution for transparent speech recognition training. OWSM replicates whisper-style training using publicly available data and a toolbox. It aims to improve upon existing models like Whisper and plans to explore using more…

We are launching Open X-Embodiment dataset, a resource for general-purpose robotics learning. With data from 22 robot types, the dataset allows for skills transfer across various robot embodiments. Additionally, we are releasing the RT-1-X, a trained robotics transformer model derived from RT-1.